CN113170408B - Method and device for determining location - Google Patents

Abstract

The present application discloses a method and device for determining a location. The method includes: determining the location of a first terminal device according to a first parameter, and the first parameter includes at least two of the following parameters: the first terminal The pseudo-range between the device and the satellite, the pseudo-range between the first terminal device and the network device, the angle between the first terminal device and the network device, the first terminal device and the second terminal The pseudorange between the devices, or the first parameter includes the pseudorange between the first terminal device and the second terminal device. The method can combine multiple measurement parameters to determine the position of the terminal device, and can improve the positioning accuracy compared with the solution of only using a single measurement quantity for positioning.

Description

Method and device for determining location

technical field

The embodiments of the present application relate to the communication field, and more specifically, to a method and device for determining a location.

Background technique

With the development of technology, more and more terminal devices need to be positioned, and users have higher and higher requirements for the positioning accuracy of the terminal devices.

How to achieve more accurate positioning of terminal equipment has become an urgent problem to be solved.

Contents of the invention

Embodiments of the present application provide a method and device for determining a position, which can realize precise positioning of a terminal device.

In a first aspect, a method for determining a location is provided, including: determining the location of a first terminal device according to a first parameter, where the first parameter includes at least two of the following parameters: the first terminal device and The pseudo-range between satellites, the pseudo-range between the first terminal device and the network device, the angle between the first terminal device and the network device, the angle between the first terminal device and the second terminal device The pseudorange between the first terminal device and the second terminal device, or the first parameter includes the pseudorange between the first terminal device and the second terminal device.

In a second aspect, a communication device is provided, and the communication device can execute the method in the foregoing first aspect or any optional implementation manner of the first aspect. Specifically, the communication device may include a functional module configured to execute the method in the foregoing first aspect or any possible implementation manner of the first aspect.

In a third aspect, a communication device is provided, including a processor and a memory. The memory is used to store a computer program, and the processor is used to call and run the computer program stored in the memory to execute the method in the above first aspect or any possible implementation manner of the first aspect.

In a fourth aspect, a chip is provided, configured to implement the method in the foregoing first aspect or any possible implementation manner of the first aspect. Specifically, the chip includes a processor, configured to call and run a computer program from the memory, so that the device installed with the chip executes the method in the above first aspect or any possible implementation manner of the first aspect.

In a fifth aspect, there is provided a computer-readable storage medium for storing a computer program, and the computer program causes a computer to execute the method in the above-mentioned first aspect or any possible implementation manner of the first aspect.

According to a sixth aspect, a computer program product is provided, including computer program instructions, where the computer program instructions cause a computer to execute the method in the above first aspect or any possible implementation manner of the first aspect.

In a seventh aspect, a computer program is provided, which, when running on a computer, causes the computer to execute the method in the above first aspect or any possible implementation manner of the first aspect.

In an eighth aspect, a communication system is provided, including a communication device, wherein the communication device is configured to: determine the position of the first terminal device according to a first parameter, and the first parameter includes at least two of the following parameters : the pseudo-range between the first terminal device and the satellite, the pseudo-range between the first terminal device and the base station, the angle between the first terminal device and the base station, the first terminal device and the second The pseudorange between the two terminal devices, or the first parameter includes the pseudorange between the first terminal device and the second terminal device.

The technical solution provided by the present application can combine multiple measurement parameters to determine the position of the terminal device, which can improve the positioning accuracy compared with the solution of only using a single measurement quantity for positioning. In addition, the embodiment of the present application also provides a positioning solution based on the pseudo-range between terminal devices, which can realize the positioning of the terminal device without the assistance of a base station or a satellite.

Description of drawings

Fig. 1 is a schematic diagram of a vehicle networking communication mode provided by an embodiment of the present application.

Fig. 2 is a schematic diagram of another communication mode of the Internet of Vehicles provided by the embodiment of the present application.

Fig. 3 is a schematic structural diagram of angle measurement performed by an antenna array provided by an embodiment of the present application.

Fig. 4 is a schematic flowchart of a method for determining a location provided by an embodiment of the present application.

Fig. 5 is a schematic block diagram of a communication device according to an embodiment of the present application.

FIG. 6 is a schematic structural diagram of another communication device according to an embodiment of the present application.

FIG. 7 is a schematic structural diagram of a chip according to an embodiment of the present application.

Fig. 8 is a schematic block diagram of a communication system according to an embodiment of the present application.

detailed description

The technical solutions in the embodiments of the present application will be described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, but not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the scope of protection of this application.

The technical solution of the embodiment of the present application can be applied to various communication systems, such as: Global System of Mobile communication (Global System of Mobile communication, GSM) system, Code Division Multiple Access (Code Division Multiple Access, CDMA) system, Wideband Code Division Multiple Access (Wideband Code Division Multiple Access, WCDMA) system, General Packet Radio Service (General Packet Radio Service, GPRS), Long Term Evolution (Long Term Evolution, LTE) system, LTE Frequency Division Duplex (Frequency Division Duplex, FDD) system, LTE Time Division Duplex (Time Division Duplex, TDD), Universal Mobile Telecommunication System (Universal MobileTelecommunication System, UMTS), Worldwide Interoperability for Microwave Access (WiMAX) communication system or 5G system, etc.

The network device mentioned in the embodiment of the present application may be a device that communicates with a terminal device (or called a communication terminal, terminal). A network device can provide communication coverage for a specific geographic area, and can communicate with terminal devices located within the coverage area. In one embodiment, the network device 110 may be a base station (Base Transceiver Station, BTS) in a GSM system or a CDMA system, or a base station (NodeB, NB) in a WCDMA system, or an evolved A type base station (Evolutional Node B, eNB or eNodeB), or a base station (gNB) in a new wireless system, or a wireless controller in a cloud radio access network (Cloud Radio Access Network, CRAN), or the network device can For mobile switching centers, relay stations, access points, vehicle-mounted devices, wearable devices, hubs, switches, bridges, routers, network-side devices in 5G networks or future evolution of public land mobile networks (PublicLand Mobile Network, PLMN) network equipment, etc.

The terminal device mentioned in this embodiment of the present application may be any terminal device that needs to determine location information. The terminal equipment may refer to an access terminal, a user equipment (User Equipment, UE), a subscriber unit, a subscriber station, a mobile station, a mobile station, a remote station, a remote terminal, a mobile device, a user terminal, a terminal, a wireless communication device, a user agent or user device. Access terminals can be cellular phones, cordless phones, Session Initiation Protocol (Session Initiation Protocol, SIP) phones, wireless local loop (Wireless Local Loop, WLL) stations, personal digital processing (Personal Digital Assistant, PDA), with wireless communication functions Handheld devices, computing devices or other processing devices connected to wireless modems, vehicle-mounted devices, wearable devices, terminal devices in 5G networks or terminal devices in future evolved PLMNs, etc.

The terminal device may be a vehicle-mounted terminal in the Internet of Vehicles, which requires very high position accuracy of the vehicle. Vehicles need to accurately determine their current location in order to better realize unmanned driving.

Terminal devices need to be positioned in various scenarios to better realize the functions of the terminal devices. For example, in the navigation system of the terminal device, the terminal device needs to accurately locate the current location, so as to plan a reasonable navigation route for the user and improve user experience.

The embodiments of the present application may be applicable to any terminal device-to-terminal device communication framework.

For example, vehicle to vehicle (vehicle to vehicle, V2V), vehicle to other equipment (vehicle to everything, V2X), device to device (device to device, D2D), etc.

The following introduces the application scenarios of the embodiments of the present application, mainly taking the Internet of Vehicles as an example.

In an implementation manner, in some embodiments of the present application, the embodiments of the present application may be applicable to transmission mode 3 and transmission mode 4 defined in 3rd generation partnership project (3rd generation partnership project, 3GPP) Rel-14.

Fig. 1 is a schematic diagram of mode 3 of the embodiment of the present application. Fig. 2 is a schematic diagram of mode 4 of the embodiment of the present application.

In transmission mode 3 shown in FIG. 1 , the transmission resource of the vehicle-mounted terminal (vehicle-mounted terminal 121 and vehicle-mounted terminal 122 ) is allocated by the base station 110, and the vehicle-mounted terminal transmits data on the sidelink according to the resources allocated by the base station 110 . Specifically, the base station 110 may allocate resources for a single transmission to the terminal, or may allocate resources for semi-static transmission to the terminal.

In the transmission mode 4 shown in FIG. 2 , the vehicle-mounted terminal (vehicle-mounted terminal 131 and vehicle-mounted terminal 132) adopts the transmission method of sensing and reservation, and the vehicle-mounted terminal independently selects the resources of the side link. Transfer resources for data transfer.

In the vehicle networking system, the vehicle needs to determine the current position in real time to avoid collisions with other objects.

At present, the commonly used positioning method is to use a base station for positioning, or use a satellite for positioning.

Base station positioning may be based on observed time difference of arrival (observed time difference of arrival, OTDOA). Satellite positioning can be based on a hyperbolic positioning algorithm for positioning. The principles of these two positioning methods are the same, and the following uses satellites as an example to illustrate their algorithms.

In general, the satellite can send a signal to the terminal device, and the terminal device can determine the signal arrival time difference according to the receiving time of the signal and the time when the satellite transmits the signal; according to the signal arrival time difference, determine the measurement between the terminal device and the satellite distance. When the terminal device determines the signal arrival time difference, because the clock of the terminal device is not synchronized with the satellite clock, there is a clock deviation, or in the process of signal transmission, due to the influence of factors such as signal noise and clock noise, the signal arrival time determined by the terminal device The time difference is not equal to the real signal transmission time, so the distance calculated from the time difference of arrival is not the real distance between the terminal device and the satellite. We can call this measured distance a pseudorange.

In this embodiment of the present application, the position of the terminal device may be determined according to the pseudo-range between the terminal device and the satellite. For example, a certain satellite can be used as a reference satellite, and the pseudorange of other satellites can be subtracted from the pseudorange of the reference satellite to obtain the difference between the pseudoranges of the two satellites. Since the difference can eliminate the influence of the clock bias of the terminal equipment, the difference in pseudo-range can more truly approximate the distance difference between two satellites and the terminal equipment. Further, the position estimation of the vehicle can be obtained by performing the least squares cost function on the plurality of distance differences, and using the first-order approximate Taylor algorithm.

However, with the development of 5G technology, terminal devices have higher and higher requirements for positioning accuracy. Especially in the Internet of Vehicles system, the requirements for positioning accuracy are more stringent.

The above least squares cost function is not accurate enough, and the first-order approximate Taylor algorithm is directly used for positioning, which will easily converge to the wrong position when the measurement error is large, so that the calculated position of the terminal device and the actual position The difference between The error is large and the positioning accuracy is not high.

In addition, due to its special high-altitude characteristics, the satellite system can only achieve meter-level two-dimensional plane accuracy, while the altitude positioning accuracy is very poor, reaching the ten-meter level. Although the positioning accuracy of the base station is higher than that of the satellite, the base station is easily blocked, resulting in a limited number of vehicles that can be obtained, and the vehicle cannot use the blocked base station for positioning; and the base station has co-frequency interference, and the signal of the base station in the distance is easy. It is interfered by the signal of the nearby base station, so the positioning accuracy of the base station is also limited, roughly at the level of ten meters. Traditional positioning algorithms only rely on a single satellite system or base station system, and only consider a single measurement, such as the pseudo-range of the base station or the pseudo-range of the satellite. Due to the small amount of measurement, it cannot take advantage of the different advantages of satellites and base stations, and cannot meet the sub-meter accuracy requirements of the Internet of Vehicles.

In addition, the antenna array at the base station can measure the angle, and the terminal equipment can also cooperate with each other to measure. These measurement items that can improve the system accuracy have not been added to the existing algorithm. Based on this, an embodiment of the present application provides a method for determining a position, which can improve the positioning accuracy of a terminal device.

As shown in FIG. 3 , the method for determining a location includes step S210.

S210. Determine the position of the first terminal device according to the first parameter, where the first parameter includes at least two of the following parameters: the pseudo-range between the first terminal device and the satellite, and the first terminal device The pseudo-range between the first terminal device and the network device, the angle between the first terminal device and the network device, the pseudo-range between the first terminal device and the second terminal device, or the first parameter includes the first A pseudorange between a terminal device and a second terminal device.

The first terminal device may be a vehicle-mounted terminal in the Internet of Vehicles system, such as a vehicle; it may also be a terminal device of another network, such as a mobile terminal, etc. The embodiment of the present application does not specifically limit the type of the first terminal device.

The second terminal device in this embodiment of the present application may refer to any other terminal device except the first terminal device.

The network device in this embodiment of the present application may be, for example, a base station. For ease of understanding, the network device is used as an example for description below.

The first parameter is a parameter obtained by measurement, such as a pseudorange measurement value and an angle measurement value. For some terminal devices, it may also implement angle measurement for the terminal devices. In this case, the first parameter may also include an angle measurement value between the terminal devices.

The technical solution provided by the embodiment of the present application can integrate the measurement quantities in the base station system, the satellite system and the terminal network system to locate the terminal equipment. Compared with a single measurement quantity solution, the positioning accuracy can be improved.

In addition, the first parameter may also include only one of the above parameters, for example, the first parameter may only include the pseudorange between the terminal devices, or only include the angle between the first terminal device and the base station. Through the first parameter, the position of the first terminal device can also be determined.

The position of the first terminal device may be an absolute position or a relative position. The absolute position may refer to the latitude and longitude coordinates of the first terminal device, and the relative position may refer to the position of the first terminal device relative to other terminal devices.

The location information of the first terminal device may include three-dimensional location information or two-dimensional location information of the first terminal device, which is not limited in this embodiment of the present application.

For convenience of description, the embodiment of the present application may collectively refer to a terminal device, a satellite, and a base station as a node. The pseudo-range between the first terminal device and the node may be obtained by using a traditional method of measuring pseudo-range.

The satellites in this embodiment of the present application may be global positioning system (global positioning system, GPS) satellites, or Beidou satellites, etc., which are not limited.

The base station in the embodiment of the present application may be a base station in a 5G system, a base station in an LTE system, or a base station in other systems.

The angle between the first terminal device and the base station may refer to the angle between the base station and the first terminal device measured by the antenna array of the base station. The angle between the first terminal device and the base station may include an azimuth angle and/or an elevation angle between the first terminal device and the base station.

The embodiment of the present application does not specifically limit the manner of determining the location of the first terminal device. It is assumed that the first parameter includes the pseudo-range between the first terminal device and the satellite, and the pseudo-range between the first terminal device and the base station.

As an example, the method of determining the position may refer to calculating the position of the first terminal device respectively according to the pseudo-range between the first terminal device and the satellite, and the pseudo-range between the first terminal device and the base station, that is, That is, the position X1 of the first terminal device can be calculated according to the pseudo-range between the first terminal device and the satellite, and then the position X2 of the first terminal device can be calculated according to the pseudo-range between the first terminal device and the base station, and finally the position X2 of the first terminal device can be calculated. According to the position X1 and the position X2, the position of the first terminal device is finally determined.

According to the position X1 and the position X2, determining the position of the first terminal device may refer to taking the average value of the position X1 and the position X2 as the position of the first terminal device. Alternatively, different weights may be set for the position X1 and the position X2 to calculate the position of the first terminal device.

The embodiment of the present application does not limit the manner of calculating the position X1 of the first terminal device according to the pseudo-range between the first terminal device and the satellite. For example, the traditional least square cost function may be used to determine the position X1 of the first terminal device; or the position X1 of the first terminal device may be determined according to a hyperbolic positioning algorithm.

Similarly, according to the pseudo-range between the first terminal device and the base station, the method of calculating the position X2 of the first terminal device may also adopt any one of the above-mentioned methods.

As yet another example, the method of determining the position may also be to integrate the pseudo-range between the first terminal device and the satellite, and the pseudo-range between the first terminal device and the base station into a cost function, and perform Iterate to determine the location of the first terminal device.

For convenience of description, the pseudo-range between the first terminal device and the satellite is simply referred to as the pseudo-range of the satellite, and the pseudo-range between the first terminal device and the base station is simply referred to as the pseudo-range of the base station.

The above is an example of the pseudorange of the satellite and the pseudorange of the base station. The first parameter in the embodiment of the present application may also include other parameters, such as the angle between the first terminal device and the base station, and/or the first The pseudorange between an end device and other end devices.

Of course, the first parameter may also include other measurement quantities. For example, in a case where angle measurement can be performed between terminal devices, positioning may also be performed according to the angle between terminal devices. Any parameter that enables location determination can be included in the first parameter.

In this embodiment of the present application, weights may also be set for different parameters. That is to say, each parameter in the first parameter has its own weight information, and the weights of different parameters may be the same or different, and the specific weight information may be determined according to actual conditions. In this embodiment of the present application, the position of the first terminal device may be determined according to the first parameter and weight information of each parameter in the first parameter.

In this way of determining the position, different weights can be set for different parameters according to specific situations. For example, when the measurement parameter is relatively accurate, a higher weight can be set for the parameter, and a lower weight can be set for the parameter when the measurement parameter error is large, so that when determining the first terminal based on multiple parameters When determining the location of the device, the accuracy of the location of the first terminal device can be guaranteed.

In addition to the influence of clock skew, the distance deviation is mainly caused by noise, and the noise may include signal noise and/or clock noise. Since noise cannot be eliminated and is unavoidable, we can minimize the impact of noise when determining the location of terminal equipment. As an implementation manner, different weights can be set for different parameters based on noise, so as to improve positioning accuracy.

It is assumed that the pseudorange between the first terminal device and the satellite has a first weight, the pseudorange between the first terminal device and the base station has a second weight, and the pseudorange between the first terminal device and the second terminal device has a third weight. Weight, the angle between the first terminal device and the base station has a fourth weight.

Since the clock of the satellite is relatively stable, the influence of the clock noise of the satellite may not be considered, and the first weight may be determined according to the variance of the signal noise when determining the weight. For the base station and the second terminal device, there may be an influence of clock noise, therefore, the second weight and the third weight may be jointly determined according to the variance of signal noise and the variance of clock noise. The angle measured by the base station and the first terminal device will also be affected by signal noise, therefore, the fourth weight may be determined according to the covariance of signal noise.

As an implementation, the first weight can be the reciprocal of the variance of the signal noise, the second weight and the third weight can be the reciprocal of the sum of the variance of the signal noise and the variance of the clock noise, and the fourth weight can be the covariance of the signal noise the inverse matrix of .

In an embodiment, the pseudo-range between the first terminal device and the second terminal device may be used to determine a distance estimate, and the distance estimate may be a pseudo-range obtained by the first terminal device and the second terminal device, and the mean value of the pseudo-range between the second terminal device and the first terminal device; then, according to the first parameter, determining the position of a terminal device may refer to determining the position of the first terminal device according to the estimated distance value.

The embodiment of the present application utilizes the characteristic that two-way distance measurement can be performed between terminal devices. When performing positioning, the mean value of two-way distance measurement (that is, the estimated distance value) is used as the first parameter for calculation. Since the estimated distance value can eliminate the Therefore, the distance estimation value can more truly reflect the distance between two terminal devices, so the positioning accuracy can also be improved by using the distance estimation value for positioning.

In an implementation manner, the embodiment of the present application does not limit the algorithm used to determine the location of the first terminal device. For example, a maximum likelihood function may be constructed based on the maximum likelihood theory, and the position of the first terminal device may be determined through the maximum likelihood function. The maximum likelihood function will be described in detail below.

The maximum likelihood function may also include a clock bias parameter, and the present application can also determine the clock bias of the terminal device while determining the position of the terminal device. Specifically, the clock offset of the first terminal device may be calculated according to the first parameter and the maximum likelihood function.

Calculating the maximum likelihood function and determining the position of the terminal device may be performed by any node among the terminal device, the base station and the satellite.

The likelihood function may be a centralized likelihood function, which means that the location information of all terminal devices is obtained by iterating the likelihood function by the same computing node.

Alternatively, the likelihood function may be a distributed likelihood function, which means that each terminal device only calculates its own location information. The positions of the multiple terminal devices may be obtained by each terminal device among the multiple terminal devices respectively iterating the likelihood function.

Determining the position of the first terminal device by the first terminal device according to the first parameter and the maximum likelihood function may refer to that the first terminal device may iterate the likelihood function according to the first parameter to obtain the position of the first terminal device. The m iteration parameter, m is an integer greater than or equal to 1; then the first terminal device can be determined according to the mth iteration parameter of other terminal devices among the multiple terminal devices and the mth iteration parameter of the first terminal device The (m+1)th iteration parameter; repeat the above steps until all the iteration parameters are no longer changed, or the maximum number of iterations is reached; according to the last iteration parameter, determine the position of the first terminal device.

The maximum likelihood function provided by the embodiment of the present application will be described in detail below with reference to specific examples.

和

We may assume that there are N _c terminal devices, N _b base stations, and N _s satellites in the system, where the positions of the base stations and satellites are known. The N _c terminal devices can calculate pseudo-ranges with N _b base stations, and/or pseudo-ranges with N _s satellites. The set of terminals, base stations and satellites is defined as follows:

with

The terminal device may be a vehicle, and the N _c terminal devices may refer to N _c vehicles in the Internet of Vehicles system.

The position of node k (including terminal equipment, base station and satellite) is denoted as p _k =[x _k , y _k , z _k ] ^T , and the parameter vector containing the positions of all terminal equipment is denoted as

和

We can define the measured and estimated forms of the parameter a as

with

In the embodiment of the present application, it may be assumed that the satellite and the base station are synchronized, that is, there is no clock deviation between the satellite and the base station. Due to the limitation of hardware equipment, there is a clock deviation δ _k between the terminal equipment k and the base station and the satellite.

Define the distance d _kj , pitch angle θ _kj , and azimuth angle φ _kj of node k observing node j as:

d _kj ＝||p _k -p _j ||

Among them, p _k represents the position of the node, and p _j represents the position of node j.

Node k may receive a signal from node j, node k may be, for example, a first terminal device, and node j may be any one of a satellite, a base station, and other terminal devices.

Node k can receive a signal from node j, which can be written as follows:

r _kj (t)＝α _kj S _j (t-τ _kj )+n _kj (t) (2)

Among them, s _j (t) is a known signal, and its Fourier transform is s _j (f), α _kj and τ _kj are the signal amplitude and time delay of the transmission link from node j to node k, respectively, n _kj (t ) is Gaussian white noise with power spectral density N ₀ /2. That is to say, the signal received by node k will include noise signal n _kj (t) in addition to the s _j (t) signal sent by node j.

建模如下：Assuming that node j is a satellite, for node k to receive a signal from satellite j, we use the following pseudorange model, the pseudorange measurement

Modeled as follows:

表示节点k与节点j之间的伪距，d_kj表示节点k与节点j之间的实际距离，b_k表示节点k的时钟偏差引入的距离偏差，ω_kj是由于信号噪声n_kj(t)引入的一个等效零均值高斯误差，换句话说，ω_kj是由于信号噪声n_kj(t)引入的距离误差。in,

represents the pseudorange between node k and node j, d _kj represents the actual distance between node k and node j, b _k represents the distance deviation introduced by the clock bias of node k, ω _kj is due to signal noise n _kj (t) An equivalent zero-mean Gaussian error introduced, in other words, ω _kj is the distance error due to signal noise n _kj (t).

Wherein, b _k =c*δ _k , c is the speed of light, and δ _k represents the clock bias of node k (or terminal device k).

满足：Variance of ω _kj

Satisfy:

的倒数确定为节点k与节点j之间伪距的权重。In this embodiment of the present application, the variance of ω _kj may be used to determine the weight of the pseudo-range between node k and node j. For example, the variance can be

The reciprocal of is determined as the weight of the pseudo-range between node k and node j.

It can be seen from the above formula that the variance is inversely proportional to the signal-to-noise ratio and the equivalent bandwidth, and the variance can be reduced by increasing the signal-to-noise ratio and the equivalent bandwidth.

Assuming that node j is a base station or other terminal equipment, for node k to receive the signal from node j, we also consider the influence of clock noise caused by clock drift of terminal equipment and base station. Therefore, the following pseudorange model can be established:

会随着时间的累积而增长。该时钟噪声的方差

可以在时钟的出厂参数中获得。Among them, b _j represents the distance deviation introduced by the clock offset of node j, and υ _kj represents the distance error introduced by clock noise. If the clock noise is not calibrated, its variance

will grow over time. The variance of the clock noise

It can be obtained in the factory parameters of the clock.

For the case where node j is a base station, we can assume that the base station is synchronous with the satellite, there is no clock offset, and b _j =0 at this time. At this point, the pseudorange model can be expressed as:

For different pseudorange measurements, we introduce the parameter λ _kj , which represents the reciprocal of the variance after the superposition of the two noises:

For the case where node j is a satellite:

For the case where node j is a base station or other terminal equipment:

In addition to the above-mentioned pseudo-range measurement, the embodiment of the present application also considers the property that the base station can measure angles, and the base station j can measure the pitch angle θ _jk and the azimuth angle φ _jk between the terminal device k, and its modeling can be as follows:

表示节点j与节点k之间的俯仰角的测量值，

表示节点j与节点k之间的方位角的测量值，θ_jk表示节点j与节点k之间的实际俯仰角，φ_jk表示节点j与节点k之间的实际方位角，μ_jk表示由于信号噪声引入的二维角度上的等效零均值的高斯噪声，其协方差矩阵可以用c_jk来表示。in,

represents the measured value of the pitch angle between node j and node k,

represents the measured value of the azimuth between node j and node k, θ _jk represents the actual pitch angle between node j and node k, φ _jk represents the actual azimuth between node j and node k, μ _jk represents the The equivalent zero-mean Gaussian noise on the two-dimensional angle introduced by the noise, its covariance matrix can be expressed by c _jk .

The specific form of c _jk is related to the spatial structure of the base station antenna array. The spatial structure of the base station antenna array may be, for example, a rectangular array or a circular array. For different spatial structures, the expressions of c _jk are different. Hereinafter, the antenna array of the base station is an example of a rectangular array for description. As shown in FIG. 4 , it is assumed that the antenna array of the base station is an M×N rectangular array.

Δ为图中阵元间隔，或者，Δ可以理解为行间距或列间距，λ为信号波长，则μ_jk的协方差矩阵C_jk可以表示为：When measuring the angle with the antenna array shown in Figure 4, the

Δ is the array element spacing in the figure, or, Δ can be understood as the row spacing or column spacing, and λ is the signal wavelength, then the covariance matrix C _jk of μ _jk can be expressed as:

in:

a＝cos ² θ _jk (mcos ² φ _jk +nsin ² φ _jk +2lcosφ _jk sinφ _jk )

b＝cosθ _jk sinθ _jk ((nm)cosφ _jk sinφ _jk +l(cos ² φ _jk -sin ² φ _kj ))

d＝sin ² θ _jk (msin ² φ _jk +ncos ² φ _jk -2lcosφ _jk sinφ _jk )

After establishing the pseudo-range model and angle model, we can obtain the location information of the terminal device through a suitable algorithm.

For example, the position of the end device can be calculated by conventional algorithms. For another example, the position of the terminal device may also be calculated based on the maximum likelihood function provided by the embodiment of the present application.

Based on the maximum likelihood theory, we can construct the following total likelihood function, where z is the vector composed of all measurements. p represents a vector composed of positions of all terminal devices, and b represents a vector composed of clock offsets of all terminal devices.

Among them, p _k represents the position of node k, node k can be a terminal device, p _j represents the position of node j, node j can be any one of terminal device, base station and satellite, ||p _k -p _j || Indicates the actual distance between node k and node j.

The above formula expresses the maximum likelihood of the pseudorange of the base station or satellite.

The above formula represents the maximum likelihood of pseudoranges between terminal devices.

The above formula expresses the maximum likelihood of the angle between the base station and the terminal equipment.

In this embodiment of the present application, when determining the position of the terminal device, multiple measurement items are considered, and the multiple measurement items can be integrated into a cost function, and the cost function is iterated multiple times until the cost function converges or After reaching the maximum number of iterations, the last iteration parameter can then be determined as the position of the end device.

Secondly, the likelihood function provided by the embodiment of the present application also considers the influence of the clock bias, and the distance deviation caused by the clock bias is also introduced into the likelihood function for calculation. While calculating the position of the terminal device, it can also obtain the The clock skew of the device. The clock deviation may play an important role in the subsequent communication process of the terminal device. For example, the terminal device may inform the opposite terminal device of its own clock deviation, which is beneficial to subsequent communication.

Of course, the likelihood function in the embodiment of the present application is not limited to the above-mentioned form, for example, the position estimation may be performed directly through the measured pseudorange without considering the distance deviation caused by the clock deviation.

Furthermore, this embodiment of the present application also considers the feature that two-way ranging can be performed between terminal devices, that is, the first parameter may include the pseudorange between the first terminal device and the second terminal device, and the second The pseudo-range obtained by the terminal device and the first terminal device. Therefore, the two-way pseudoranges measured between the first terminal device and the second terminal device are considered and integrated into the likelihood function to further improve the positioning accuracy.

The pseudo-range obtained by the first terminal device k and the second terminal device j may mean that the second terminal device j may send a first signal to the first terminal device, and the first signal may include a signal sent by the second terminal device j. At the sending time t1 of the first signal, after the first terminal device k receives the first signal, it can determine the pseudo-range to the second terminal device j according to its receiving time t2 as

The pseudo-range between the second terminal device j and the first terminal device k may mean that the first terminal device k may send a second signal to the second terminal device j, and the second signal may include the first terminal device k The sending time t3 of the second signal is sent. After the second terminal device j receives the second signal, it can determine the pseudo-range to the first terminal device k according to its own receiving time t4 as

At this time, after considering the characteristics of two-way ranging between terminal devices, the maximum likelihood of the pseudo-range between terminal devices in the maximum likelihood function can be transformed into:

表示节点k获得的与节点j之间的伪距的最大似然，

表示节点j获得的与节点k之间的伪距的最大似然。

Indicates the maximum likelihood of the pseudorange obtained by node k and node j,

Indicates the maximum likelihood of the pseudorange obtained by node j from node k.

节点j表示卫星。Further, in the embodiment of the present application, different weights can be set for different parameters. For the pseudo-range of the satellite, we can only consider the influence of signal noise, so the weight can be set for the pseudo-range of the satellite based on the signal noise. For example, the signal The reciprocal λ _kj of the variance of the noise is set as the weight of the satellite pseudorange,

Node j represents a satellite.

节点j表示基站。For the pseudo-range of the base station, we can consider the influence of signal noise and clock noise at the same time. The pseudo-range of the base station can be determined according to the variance of the signal noise and the variance of the clock noise. For example, the weight of the pseudo-range of the base station can be the signal noise. The inverse of the sum of the variance of the variance and the clock noise,

Node j represents a base station.

节点j表示其他终端设备。For the pseudo-range between terminal devices, similar to the pseudo-range of the base station, we can consider the influence of signal noise and clock noise at the same time, and set the weight for the pseudo-range between terminal devices. The weight can be, for example,

Node j represents other end devices.

For the angle measurement of the base station, the embodiment of the present application may consider the influence of the equivalent zero-mean Gaussian noise on the two-dimensional angle introduced by the signal noise, and the covariance matrix of the signal noise may be used to determine the weight of the angle measurement. For example, the inverse of the covariance matrix is determined as the weight for the angle measure.

We can add the above weight information to the maximum likelihood function to determine the position of the terminal device.

The maximum likelihood function can be transformed into:

In the above likelihood function, different weights λ _kj can be set for different parameters.

Since the variance of the noise is inversely proportional to the SNR, and _λkj is inversely proportional to the variance of the noise, therefore, _λkj is directly proportional to the SNR, that is, the larger the SNR, the greater the weight _λkj . If the signal-to-noise ratio of a measurement is relatively large, it means that the noise in the signal is relatively small, and a larger weight can be assigned to the measurement; if the signal-to-noise ratio of a measurement is relatively small, it means that the noise in the signal is relatively small. If the value is large, a smaller weight can be given to the measurement. This method of setting weights is more reasonable, and the influence of signal noise and clock noise is considered in the algorithm. The position of the terminal device determined by the maximum likelihood function is also relatively close to the actual position, and the positioning accuracy is high.

For the above-mentioned maximum likelihood function, the embodiment of the present application does not specifically limit the method adopted for solving it. For example, it may be a gradient descent method, an EM algorithm, a coordinate ascent or descent algorithm, and the like. The following takes the gradient descent algorithm as an example to describe the solution process of the likelihood function.

For the above likelihood function, our purpose is to find the appropriate P and b to maximize the value of the above likelihood function. Because the likelihood function is in exponential form, we only need to get the maximum value of the exponential term to obtain the maximum value of the likelihood function. That is to say, the value of the following cost function H(p, b) should be minimized.

是测量得到的伪距值和角度值。我们的目的是让解算的伪距和角度值，与测量的伪距和角度值之间的偏差最小。H(p,b) takes the form of a weighted sum of squares. Among them, there are two parts, one part is the information from the anchor point, such as the pseudorange and angle information from the base station, and the pseudorange information from the satellite. The other part is pseudorange information from other terminal devices. in,

are the measured pseudorange and angle values. Our goal is to minimize the deviation between the calculated pseudorange and angle values and the measured pseudorange and angle values.

For the above likelihood function, since it includes all the measurement information, that is, the measurement information between all nodes among N _c terminal devices, N _b base stations and N _s satellites, we can set The likelihood function is called a centralized localization algorithm.

When using the gradient descent algorithm to solve, we can give the gradient (ie, the first derivative) of each polynomial in H(p, b) with respect to P and b. For each polynomial in H(p, b), it only represents the measurement between node j and node k, so it is only related to the unknown parameters p _j , p _k , b _j , b _k of the terminal equipment.

For the pseudo-range measurement, we take the pseudo-range measurement between terminal devices as an example. The first-order derivative of the pseudo-range between base stations or satellites for the position parameter p _k and clock bias parameter b _k of the terminal device can also be obtained by the following It can be obtained by analogy with the formula, only need to regard p _j and b _j in the polynomial as the known parameters of the corresponding satellite or base station.

For the measurement item of the pseudo-range between terminal devices, we can derive it, and we can get:

For the angle measurement between the base station and the end device, first define:

Then the gradient corresponding to the angle measurement item is:

After obtaining the first-order derivatives of each polynomial, the likelihood function can be iterated for the first time to obtain the minimum value of the first iterative. Further, the second iteration is performed according to the iteration parameters of the first iteration to obtain the iteration parameters of the second iteration. Loop in turn until the iteration parameters no longer change, or reach the maximum number of iterations.

和

并根据该初始状态进行迭代。对于第m次的迭代参数

和

可以根据整体代价函数和当前的迭代参数

和

根据上述给出的梯度表达式计算位置和时钟参数的梯度，依据梯度下降更新下一轮的参数

和

m为大于等于1的整数。直至该似然函数收敛或者达到最大迭代次数；根据最后一次迭代对应的迭代参数，确定终端设备的位置和时钟偏差。When solving this likelihood function, the pseudorange and angle measurements between the end device and all nodes can be input. The initial state of all end devices can then be given

with

And iterate based on that initial state. For the mth iteration parameter

with

According to the overall cost function and the current iteration parameters

with

Calculate the gradient of the position and clock parameters according to the gradient expression given above, and update the parameters of the next round according to the gradient descent

with

m is an integer greater than or equal to 1. Until the likelihood function converges or reaches the maximum number of iterations; according to the iteration parameters corresponding to the last iteration, the position and clock bias of the terminal device are determined.

In addition to the above-mentioned manners for determining weights, other manners for determining weights are also possible. As an implementation, fixed weight information can be set for each measurement quantity. For example, the weights of satellite pseudo-range, base station pseudo-range, base station angle, and pseudo-range between terminal devices can be 0.3, 0.3, 0.2, 0.2.

The above calculation process is described under the assumption that all measurement items exist. Of course, there may be only some of the measurement items. For the case of only some of the measurement items, the above-mentioned likelihood function and its calculation process are also applicable, and it is only necessary to set the missing measurement items to 0.

For the case where there is no measurement item of the base station or satellite system, that is to say, there is no base station or satellite-assisted positioning, and the first parameter value only includes the pseudo-range of the terminal device, if the gradient descent algorithm given above is directly used for For positioning, if the given initial value is not good enough, it is easy to fail to converge or converge to the wrong position, that is, the calculated position of the terminal device is very different from the actual position.

Since there is no satellite and base station assistance, the first vehicle can be used as the clock reference at this time, and the distance deviation b ₁ introduced by its clock deviation can be set to 0, and then the estimated distance between the terminal equipment and other vehicles can be obtained according to the two-way measurement Clock offset relative to the first vehicle.

Since formula (5) is a linear model about distance d _kj and deviations b _k and b _j , the estimation of all distances d _kj and distance deviation b _k can be obtained directly by least squares.

The embodiment of this application also provides another simple way to obtain distance estimation, that is, directly average the two-way ranging to obtain the distance estimation value:

Using the distance estimation value for positioning can eliminate the influence of the clock bias between the first terminal device and the second terminal device on the distance estimation.

的k行j列可以表示为：After obtaining the distance estimates between all nodes, the shape of the terminal equipment network can be obtained directly through the classic multi-dimensional calibration algorithm, or the "shape estimation" of the terminal equipment network can be obtained through other algorithms such as semi-positive definite programming algorithm. The following is an example of a multi-dimensional calibration algorithm, the square distance matrix

The k rows and j columns can be expressed as:

中没有测量的距离值，可以采用经典的最短路径算法进行代替。然后对平方距离矩阵

可以采用多维标定算法即可获得终端设备网络的“形状”。For the squared distance matrix

There is no measured distance value in , which can be replaced by the classic shortest path algorithm. Then for the squared distance matrix

The "shape" of the terminal device network can be obtained by using a multi-dimensional calibration algorithm.

The implementation of the multidimensional calibration algorithm can be as follows:

去质心化，得到G矩阵。

其中L＝I-1/N_c11^T，I为N_c维单位阵，1为N_c维全为1的列向量。对G矩阵进行特征值分解得到特征值和其对应的特征向量。取出最大的三个特征值和其对应的特征向量分别相乘得到三个加权的向量，按特征值从大到小顺序排列三个向量得到一个三列的矩阵，即为三维位置参数矩阵。如果只需要二维位置矩阵，则只取该三列矩阵的前两列即可。First for the squared distance matrix

Decentralize to get the G matrix.

Where L=I-1/N _c 11 ^T , I is an N _c -dimensional unit matrix, and 1 is a column vector of all 1s in N _c dimensions. Decompose the eigenvalues of the G matrix to obtain the eigenvalues and their corresponding eigenvectors. The three largest eigenvalues are multiplied by their corresponding eigenvectors to obtain three weighted vectors, and the three vectors are arranged in descending order of the eigenvalues to obtain a three-column matrix, which is the three-dimensional position parameter matrix. If only a two-dimensional position matrix is required, only the first two columns of the three-column matrix can be used.

The above centralized positioning algorithm needs to gather all the measurements in the network, and all these measurements need to be calculated at a central point, that is, the positions and clock deviations of all terminal devices are calculated through a central point . The central point may be any node among terminal equipment, base station and satellite. Since the algorithm directly calculates the p and b of N _c vehicles, the large calculation space leads to high complexity, and it also has high requirements for the calculation ability of the central point.

In addition, in the mobile network, in order to maintain real-time performance, it is often impossible to collect all the data to the central node for calculation, and the computing power of most nodes cannot calculate the parameters of all nodes in real time.

Based on this, the embodiment of the present application provides a distributed positioning algorithm, which can decompose the calculation process, and each terminal device k only needs to calculate its own position p _k and clock bias b _k , so that all terminal devices can also be obtained position and clock offset. This calculation method can reduce the calculation complexity of the calculation nodes, increase the calculation rate, and ensure the real-time requirements in the mobile network.

For the distributed positioning algorithm, we can extract the items related to the terminal device k from the centralized cost function H(p, b), and construct the local cost function H _k (p _k , b _k ), as follows:

Each terminal device can iterate the likelihood function according to the derivation method described above, and each terminal device iterates its own likelihood function to obtain its corresponding position and clock offset.

The specific iterative process is as follows:

The first terminal device may iterate the distributed likelihood function according to the first parameter to obtain an m-th iteration parameter of the first terminal device, where m is an integer greater than or equal to 1.

The first terminal device can receive the mth iteration parameters of other terminal devices broadcast by other terminal devices, and use the gradient descent algorithm to obtain the (m+1)th iteration of the node according to the mth iteration parameters of other terminal devices parameter.

Repeat the above steps until all iteration parameters do not change, or the maximum number of iterations is reached.

The first terminal device determines the location and clock offset of the first terminal device according to the last iteration parameter. For example, the first terminal device may determine p in the last iteration parameter as the location information of the first terminal device, and determine b in the last iteration parameter as the clock offset distance of the first terminal device.

Likewise, the second terminal device may use the above steps to obtain the location and clock offset of the second terminal device. By analogy, each terminal device can obtain the location and clock offset of its own node. In this way, the position and clock offset of the entire terminal equipment system can be obtained.

For the local positioning algorithm, when there is no anchor point, that is, when there is no base station system and satellite system to assist positioning, the gradient descent algorithm described above can be directly used for calculation. However, if the given initial value is not good enough, it is easy to cause non-convergence or convergence to the wrong position.

Based on this, the embodiment of the present application provides a calculation method, which can avoid the situation of not converging or converging to a wrong position. The calculation method is described below.

Each terminal device can obtain the distance value between itself and its neighbors through formula (6), and each terminal device can broadcast all the distance values it obtains to other terminal devices. In this way, each terminal device can obtain all measurement information in its 1-hop network, that is, each terminal device can obtain measurement information of other terminal devices that can communicate with itself. The terminal device can obtain the "shape" of each terminal device's 1-hop network according to the distance measurement values (or pseudoranges) of all nodes within the 1-hop range, and according to the multi-dimensional calibration algorithm or semi-positive definite programming algorithm. Further, these local structures can be fused to obtain the "shape" of the entire network. The specific calculation process is as follows:

The input is the pseudorange between the end-device and other end-devices, and the output is the "shape" of the entire end-device network.

并将其广播给邻居。Each terminal device can build its own local 1-hop network "shape" of the 0th round of iteration using the multi-dimensional calibration algorithm described above

and broadcast it to neighbors.

Starting from any terminal device, define it as the initial network. Here, define terminal device k as the initial network as an example.

终端设备k可以从不在

中的终端设备中挑选出终端设备j，使得

知

拥有的共有节点最多m为大于等于1的整数。For the mth iteration parameter

End device k can never be in

Select the terminal device j from the terminal devices in , such that

Know

The maximum number of shared nodes owned by m is an integer greater than or equal to 1.

和

融合成一个包含

和

所有节点的新网络“形状”，将融合后的网络更新为

Through the spatial relationship of common nodes will

with

fused into one containing

with

The new network "shape" of all nodes, updating the fused network to

包含所有终端设备。当

包含所有终端设备时，则将其定为网络的整体“形状”。until

Contains all end devices. when

When all end devices are included, this defines the overall "shape" of the network.

Compared with the 3GPP positioning algorithm that only contains pseudo-range measurement parameters and only uses a single type of information (such as base stations or satellites), the embodiment of the present application not only adds the angle measurement of the base station and the pseudo-range measurement of mutual cooperation between terminal devices , and all these measurements are integrated into a cost function in the algorithm, and positioning can be performed through the fused cost function, which can improve the positioning accuracy.

The maximum likelihood function provided by the embodiment of the present application is inclusive. For unknown measurement items or measurement items that have not been performed, it is only necessary to set the missing part of the measurement to 0, and the likelihood function can still be used for positioning. For example, in the case of only the angle measurement and pseudorange measurement of the base station, it is only necessary to set the polynomial of the pseudorange of the satellite and the polynomial of the pseudorange between the terminal equipment to 0, and only carry out the polynomial of the angle and pseudorange of the base station Iterate to obtain the location information of the terminal device.

The maximum likelihood function provided by the embodiment of the present application can realize the estimation of the clock offset of the terminal device while realizing the positioning of the terminal device.

In addition, the embodiment of the present application uses the gradient descent algorithm to solve the maximum likelihood function. Since the gradient descent algorithm is used, only the gradient needs to be calculated in the iterative process. And the gradient part has a closed expression, and the complexity is low. Especially for a network with high real-time requirements such as the Internet of Vehicles, low complexity can meet its real-time requirements. The distributed positioning algorithm provided by the embodiment of the present application can further reduce computational complexity and improve real-time performance.

The method for determining the position provided by the embodiment of the present application has been described in detail above, and the device of the embodiment of the present application will be described in detail below in conjunction with Fig. 5-Fig. See the previous method embodiments.

Fig. 5 is a schematic block diagram of a communication device 500 provided by an embodiment of the present application. The communication device 500 shown in FIG. 5 may be the sending end device in the method embodiment. The communication device may comprise a processing unit 510 .

The processing unit 510 is configured to determine the position of the first terminal device according to a first parameter, where the first parameter includes at least two parameters among the following parameters: a pseudo-range between the first terminal device and a satellite, the The pseudo-range between the first terminal device and the network device, the angle between the first terminal device and the network device, the pseudo-range between the first terminal device and the second terminal device, or the first terminal device A parameter includes a pseudorange between the first terminal device and the second terminal device.

In one embodiment, each of the first parameters has its own weight information, and the processing unit 510 is configured to: according to the first parameter and the weight of each of the first parameters information to determine the location of the first terminal device.

In an embodiment, the pseudorange between the first terminal device and the satellite has a first weight, the pseudorange between the first terminal device and the network device has a second weight, and the first A pseudorange between a terminal device and the second terminal device has a third weight, an angle between the first terminal device and the network device has a fourth weight, and the first weight is based on signal noise The second weight and the third weight are determined according to the variance of signal noise and the variance of clock noise, and the fourth weight is determined according to the covariance of signal noise.

In an implementation manner, the angle between the first terminal device and the network device includes an azimuth angle and/or an elevation angle.

In an embodiment, the pseudo-range between the first terminal device and the second terminal device is used to determine a distance estimate value, and the distance estimate value is obtained by the first terminal device and the second terminal device The pseudorange between the terminal devices, and the mean value of the pseudorange obtained by the second terminal device and the first terminal device; the processing unit 510 is configured to: determine the The location of the first terminal device.

In an implementation manner, the processing unit 510 is configured to: determine the position of the first terminal device according to the first parameter and a maximum likelihood function.

In an embodiment, the communication device is configured to obtain the positions of multiple terminal devices, the multiple terminal devices include the first terminal device, and the processing unit 510 is configured to: according to the first parameter, adopt The gradient descent algorithm performs multiple iterations on the maximum likelihood function to obtain a minimum value of the maximum likelihood function; and determine the positions of the multiple terminal devices according to an iteration parameter at the minimum value of the maximum likelihood function.

In an implementation manner, the positions of the multiple terminal devices are obtained by iterating the maximum likelihood function on the same computing node.

In an embodiment, the positions of the plurality of terminal devices are obtained by each terminal device in the plurality of terminal devices respectively iterating the maximum likelihood function, and the processing unit 510 is configured to: according to the The first parameter is iterated on the maximum likelihood function to obtain the mth iteration parameter of the first terminal device, m is an integer greater than or equal to 1; according to the other terminal devices among the multiple terminal devices The mth iteration parameter and the mth iteration parameter of the first terminal device determine the (m+1)th iteration parameter of the first terminal device; repeat the above steps until all iteration parameters no longer change ; Determine the position of the first terminal device according to the last iteration parameter.

In an embodiment, the maximum likelihood function further includes a clock bias parameter of the first terminal device, and the processing unit 510 is configured to: determine according to the first parameter and the maximum likelihood function The clock deviation of the first terminal device.

In an implementation manner, the first parameter includes a pseudo-range between the first terminal device and the second terminal device, and the processing unit 510 is configured to: according to the first terminal device and the second terminal device A square distance matrix is determined for the pseudo-range between the two terminal devices; according to the square distance matrix, the position of the first terminal device is determined through a multi-dimensional calibration algorithm or a positive semi-definite programming algorithm.

In an embodiment, the position of the first terminal device includes two-dimensional position information and/or three-dimensional position information of the first terminal device.

It should be understood that the communication device 500 may perform corresponding operations performed by the communication device in the foregoing method, and details are not described here for brevity. The communication device 500 may be, for example, the terminal device, network device or satellite described above.

FIG. 6 is a schematic structural diagram of a communication device 600 provided in an embodiment of the present application. The communication device 600 shown in FIG. 6 includes a processor 610, and the processor 610 can invoke and run a computer program from a memory, so as to implement the method in the embodiment of the present application.

In an implementation manner, as shown in FIG. 6 , the communication device 600 may further include a memory 620 . Wherein, the processor 610 can invoke and run a computer program from the memory 620, so as to implement the method in the embodiment of the present application.

Wherein, the memory 620 may be an independent device independent of the processor 610 , or may be integrated in the processor 610 .

In one embodiment, as shown in FIG. 6, the communication device 600 may further include a transceiver 630, and the processor 610 may control the transceiver 630 to communicate with other devices, specifically, to send information or data to other devices, or Receive messages or data from other devices.

Wherein, the transceiver 630 may include a transmitter and a receiver. The transceiver 630 may further include antennas, and the number of antennas may be one or more.

In an embodiment, the communication device 600 may specifically be the terminal device of the embodiment of the present application, and the communication device 600 may implement the corresponding processes implemented by the communication device in each method of the embodiment of the present application. Let me repeat.

FIG. 7 is a schematic structural diagram of a chip according to an embodiment of the present application. The chip 700 shown in FIG. 7 includes a processor 710, and the processor 710 can call and run a computer program from a memory, so as to implement the method in the embodiment of the present application.

In an implementation manner, as shown in FIG. 7 , the chip 700 may further include a memory 720 . Wherein, the processor 710 can invoke and run a computer program from the memory 720, so as to implement the method in the embodiment of the present application.

Wherein, the memory 720 may be an independent device independent of the processor 710 , or may be integrated in the processor 710 .

In an implementation manner, the chip 700 may further include an input interface 730 . Wherein, the processor 710 can control the input interface 730 to communicate with other devices or chips, specifically, can obtain information or data sent by other devices or chips.

In an implementation manner, the chip 700 may further include an output interface 740 . Wherein, the processor 710 can control the output interface 740 to communicate with other devices or chips, specifically, can output information or data to other devices or chips.

In an implementation manner, the chip can be applied to the terminal device in the embodiment of the present application, and the chip can implement the corresponding processes implemented by the terminal device in each method of the embodiment of the present application. For the sake of brevity, details are not repeated here.

It should be understood that the chips mentioned in the embodiments of the present application may also be called system-on-chip, system-on-chip, system-on-a-chip, or system-on-a-chip.

It should be understood that the processor in the embodiment of the present application may be an integrated circuit chip, which has a signal processing capability. In the implementation process, each step of the above-mentioned method embodiments may be completed by an integrated logic circuit of hardware in a processor or instructions in the form of software. The above-mentioned processor may be a general-purpose processor, a digital signal processor (Digital Signal Processor, DSP), an application-specific integrated circuit (Application Specific Integrated Circuit, ASIC), an off-the-shelf programmable gate array (Field Programmable Gate Array, FPGA) or other programmable Logic devices, discrete gate or transistor logic devices, discrete hardware components. Various methods, steps, and logic block diagrams disclosed in the embodiments of the present application may be implemented or executed. A general-purpose processor may be a microprocessor, or the processor may be any conventional processor, or the like. The steps of the method disclosed in connection with the embodiments of the present application may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software module can be located in a mature storage medium in the field such as random access memory, flash memory, read-only memory, programmable read-only memory or electrically erasable programmable memory, register. The storage medium is located in the memory, and the processor reads the information in the memory, and completes the steps of the above method in combination with its hardware.

It can be understood that the memory in the embodiments of the present application may be a volatile memory or a nonvolatile memory, or may include both volatile and nonvolatile memories. Wherein, the non-volatile memory may be a read-only memory (Read-Only Memory, ROM), a programmable read-only memory (Programmable ROM, PROM), an erasable programmable read-only memory (Erasable PROM, EPROM), an electronically programmable Erase Programmable Read-Only Memory (Electrically EPROM, EEPROM) or Flash. The volatile memory can be Random Access Memory (RAM), which acts as an external cache. By way of illustration and not limitation, many forms of RAM are available such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (Synchronous DRAM, SDRAM), double data rate synchronous dynamic random access memory (Double DataRate SDRAM, DDR SDRAM), enhanced synchronous dynamic random access memory (Enhanced SDRAM, ESDRAM), synchronous connection dynamic random access memory (Synchlink DRAM, SLDRAM) And direct memory bus random access memory (Direct Rambus RAM, DR RAM). It should be noted that the memory of the systems and methods described herein is intended to include, but not be limited to, these and any other suitable types of memory.

It should be understood that the above-mentioned memory is illustrative but not restrictive. For example, the memory in the embodiment of the present application may also be a static random access memory (Static RAM, SRAM), a dynamic random access memory (Dynamic RAM, DRAM), Synchronous dynamic random access memory (Synchronous DRAM, SDRAM), double data rate synchronous dynamic random access memory (Double Data Rate SDRAM, DDR SDRAM), enhanced synchronous dynamic random access memory (Enhanced SDRAM, ESDRAM), synchronous connection Dynamic random access memory (Synch Link DRAM, SLDRAM) and direct memory bus random access memory (Direct Rambus RAM, DR RAM), etc. That is, the memory in the embodiments of the present application is intended to include, but not be limited to, these and any other suitable types of memory.

Fig. 8 is a schematic block diagram of a communication system 800 according to an embodiment of the present application. As shown in FIG. 8 , the communication system 800 includes a network device 810 and a terminal device 820 .

In an embodiment, the network device 810 can be used to implement the corresponding functions implemented by the network device in the above method, and the composition of the network device 810 can be shown as the communication device 500 in FIG. 5 , for the sake of brevity, here No longer.

In an embodiment, the terminal device 820 can be used to realize the corresponding functions realized by the terminal device in the above method, and the composition of the terminal device 820 can be shown as the communication device 500 in FIG. 5 , for the sake of brevity, here No longer.

The embodiment of the present application also provides a computer-readable storage medium for storing computer programs. Optionally, the computer-readable storage medium can be applied to the network device in the embodiments of the present application, and the computer program enables the computer to execute the corresponding processes implemented by the network device in the methods of the embodiments of the present application. For brevity, here No longer. In one embodiment, the computer-readable storage medium can be applied to the terminal device in the embodiment of the present application, and the computer program enables the computer to execute the corresponding processes implemented by the terminal device in the various methods of the embodiment of the present application. For the sake of brevity, I won't repeat them here.

The embodiment of the present application also provides a computer program product, including computer program instructions. Optionally, the computer program product may be applied to the network device in the embodiment of the present application, and the computer program instructions cause the computer to execute the corresponding process implemented by the network device in each method of the embodiment of the present application. For the sake of brevity, the Let me repeat. In one embodiment, the computer program product can be applied to the terminal device in the embodiment of the present application, and the computer program instructions cause the computer to execute the corresponding processes implemented by the terminal device in the various methods of the embodiment of the present application. For the sake of brevity, the This will not be repeated here.

The embodiment of the present application also provides a computer program. Optionally, the computer program can be applied to the network device in the embodiment of the present application. When the computer program is run on the computer, the computer executes the corresponding process implemented by the network device in each method of the embodiment of the present application. For the sake of brevity , which will not be repeated here. In one embodiment, the computer program can be applied to the terminal device in the embodiment of the present application. When the computer program is run on the computer, the computer executes the corresponding process implemented by the terminal device in each method of the embodiment of the present application, For the sake of brevity, details are not repeated here.

It should be understood that the terms "system" and "network" are often used interchangeably herein. The term "and/or" in this article is just an association relationship describing associated objects, which means that there can be three relationships, for example, A and/or B can mean: A exists alone, A and B exist simultaneously, and there exists alone B these three situations. In addition, the character "/" in this article generally indicates that the contextual objects are an "or" relationship.

It should also be understood that in the embodiment of the present invention, "B corresponding (corresponding) to A" means that B is associated with A, and B can be determined according to A. However, it should also be understood that determining B according to A does not mean determining B only according to A, and B may also be determined according to A and/or other information.

Those skilled in the art can appreciate that the units and algorithm steps of the examples described in conjunction with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed by hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art may use different methods to implement the described functions for each specific application, but such implementation should not be regarded as exceeding the scope of the present application.

Those skilled in the art can clearly understand that for the convenience and brevity of the description, the specific working process of the above-described system, device and unit can refer to the corresponding process in the foregoing method embodiment, which will not be repeated here.

In the several embodiments provided in this application, it should be understood that the disclosed systems, devices and methods may be implemented in other ways. For example, the device embodiments described above are only illustrative. For example, the division of the units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or can be Integrate into another system, or some features may be ignored, or not implemented. In another point, the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces, and the indirect coupling or communication connection of devices or units may be in electrical, mechanical or other forms.

The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place, or may be distributed to multiple network units. Part or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, each unit may exist separately physically, or two or more units may be integrated into one unit.

If the functions described above are realized in the form of software function units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or the part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including Several instructions are used to make a computer device (which may be a personal computer, a server, or a network device, etc.) execute all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory, ROM), random access memory (Random Access Memory, RAM), magnetic disk or optical disk and other various media that can store program codes. .

The above is only a specific implementation of the application, but the scope of protection of the application is not limited thereto. Anyone familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the application. Should be covered within the protection scope of this application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims (12)

1. A method for determining a position, characterized in that the method is used to obtain the positions of multiple terminal devices, the multiple terminal devices include a first terminal device, and the positions of the multiple terminal devices are the multiple Each terminal device in the terminal devices respectively iterates the maximum likelihood function, and the method includes: Perform multiple iterations on the maximum likelihood function according to the first parameter to obtain the mth iteration parameter of the first terminal device, where m is an integer greater than or equal to 1; Determine the (m+1)th iteration parameter of the first terminal device according to the mth iteration parameter of other terminal devices among the plurality of terminal devices and the mth iteration parameter of the first terminal device; Repeat the above steps until all iteration parameters no longer change; determining the position of the first terminal device according to the last iteration parameter, Wherein, the first parameter includes: the pseudo-range between the first terminal device and the satellite, the pseudo-range between the first terminal device and the network device, and the distance between the first terminal device and the network device. The angle between and the pseudo-range between the first terminal device and the second terminal device; each parameter in the first parameter has its own weight information; Wherein, the pseudo-range between the first terminal device and the satellite has a first weight, the pseudo-range between the first terminal device and the network device has a second weight, and the first terminal device and the satellite have a second weight. The pseudorange between the second terminal devices has a third weight, the angle between the first terminal device and the network device has a fourth weight, and the first weight is determined according to the variance of signal noise, The second weight and the third weight are determined according to the variance of signal noise and the variance of clock noise, and the fourth weight is determined according to the covariance of signal noise, Wherein, the maximum likelihood function integrates each parameter in the first parameters and respective weight information of each parameter. 2. The method according to claim 1, wherein the angle between the first terminal device and the network device comprises an azimuth angle and/or an elevation angle. 3. The method according to claim 1 or 2, wherein the maximum likelihood function also includes a clock bias parameter of the first terminal device, the method further comprising: Determine the clock offset of the first terminal device according to the first parameter and the maximum likelihood function. 4. The method according to claim 1 or 2, wherein the position of the first terminal device comprises two-dimensional position information and/or three-dimensional position information of the first terminal device. 5. A communication device, characterized in that, the communication device is used to acquire the positions of multiple terminal devices, the multiple terminal devices include a first terminal device, and the positions of the multiple terminal devices are the multiple Each terminal device in the terminal device respectively iterates the maximum likelihood function, and the communication device includes: A processing unit for performing the following steps: Perform multiple iterations on the maximum likelihood function according to the first parameter to obtain the mth iteration parameter of the first terminal device, where m is an integer greater than or equal to 1; Determine the (m+1)th iteration parameter of the first terminal device according to the mth iteration parameter of other terminal devices among the plurality of terminal devices and the mth iteration parameter of the first terminal device; Repeat the above steps until all iteration parameters no longer change; determining the position of the first terminal device according to the last iteration parameter, Wherein, the first parameter includes: the pseudo-range between the first terminal device and the satellite, the pseudo-range between the first terminal device and the network device, and the distance between the first terminal device and the network device. The angle between and the pseudo-range between the first terminal device and the second terminal device; each parameter in the first parameter has its own weight information; Wherein, the pseudo-range between the first terminal device and the satellite has a first weight, the pseudo-range between the first terminal device and the network device has a second weight, and the first terminal device and the satellite have a second weight. The pseudorange between the second terminal devices has a third weight, the angle between the first terminal device and the network device has a fourth weight, and the first weight is determined according to the variance of signal noise, The second weight and the third weight are determined according to the variance of signal noise and the variance of clock noise, and the fourth weight is determined according to the covariance of signal noise, Wherein, the maximum likelihood function integrates each parameter in the first parameters and respective weight information of each parameter. 6. The communication device according to claim 5, wherein the angle between the first terminal device and the network device comprises an azimuth angle and/or an elevation angle. 7. The communication device according to claim 5 or 6, wherein the maximum likelihood function further includes a clock bias parameter of the first terminal device, and the processing unit is configured to: Determine the clock offset of the first terminal device according to the first parameter and the maximum likelihood function. 8. The communication device according to claim 5 or 6, wherein the position of the first terminal device comprises two-dimensional position information and/or three-dimensional position information of the first terminal device. 9. A communication device, characterized in that the communication device includes a processor and a memory, the memory is used to store a computer program, and the processor is used to invoke and run the computer program stored in the memory to execute The method according to any one of claims 1 to 4. 10. A chip, characterized in that the chip includes a processor, the processor is used to call and run a computer program from a memory, so that a device equipped with the chip executes any one of claims 1 to 4 the method described. 11. A computer-readable storage medium, characterized by being used for storing a computer program, the computer program causing a computer to execute the method according to any one of claims 1 to 4. 12. A communication system, comprising the communication device according to any one of claims 5-8.

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