WO2014085988A1 - 一种定位的方法、设备及系统 - Google Patents
一种定位的方法、设备及系统 Download PDFInfo
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- WO2014085988A1 WO2014085988A1 PCT/CN2012/085861 CN2012085861W WO2014085988A1 WO 2014085988 A1 WO2014085988 A1 WO 2014085988A1 CN 2012085861 W CN2012085861 W CN 2012085861W WO 2014085988 A1 WO2014085988 A1 WO 2014085988A1
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- state information
- measurement data
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- mobile state
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W64/00—Locating users or terminals or network equipment for network management purposes, e.g. mobility management
- H04W64/006—Locating users or terminals or network equipment for network management purposes, e.g. mobility management with additional information processing, e.g. for direction or speed determination
Definitions
- the present invention relates to the field of communications, and in particular, to a method, device, and system for positioning.
- MDT Minimization of Drive Tests
- the location measurement data reported by the UE is generally affected by noise and causes errors in the positioning result. Therefore, the location measurement data of the UE is usually processed to improve the positioning accuracy, for example, performing Kalman filtering on the location measurement data of the UE.
- the perturbation variance Q of the UE motion plays a very important role in the accuracy gain of the positioning result.
- Q is generally set to a constant according to experience. The inventors have found that at least the following problems exist in the prior art:
- the UE positioning accuracy is not high, so that the location information of the UE required in the MDT measurement is inaccurate, and the cost of the operator network optimization is improved.
- Embodiments of the present invention provide a method, device, and system for positioning, which process location measurement data of a UE according to mobile state information of a UE, thereby improving positioning accuracy.
- an embodiment of the present invention provides a method for positioning, including:
- the network management device acquires the mobile state information of the user equipment UE and the location measurement data of the UE, where the mobile state information of the UE is used to indicate that the UE is a high speed mobile, a medium speed mobile or a general mobile;
- the device obtains the corrected position of the UE according to the mobile state information of the UE and the location measurement data of the UE.
- the network management device acquires The mobile state information of the UE includes:
- the network management device sends the indication information to the UE, where the indication information is used to instruct the UE to record the mobile state information of the UE;
- the network management device receives mobile state information of the UE sent by the UE.
- a method of locating including:
- the user equipment UE acquires mobile state information of the UE
- the modified location of the UE is used to indicate that the UE is a high speed mobile, a medium speed mobile, or a general mobile.
- the method further includes: before the user equipment UE acquires the mobile state information of the UE, according to the second aspect, the method further includes:
- the UE receives the indication information sent by the network management device, where the indication information is used to instruct the UE to record the mobility state information of the UE.
- a positioning device including:
- An acquiring unit configured to acquire mobile state information of the user equipment UE and location measurement data of the UE, and transmit the mobile state information of the UE and location measurement data of the UE to a positioning unit, where The mobile state information is used to indicate that the UE is a high speed mobile, a medium speed mobile, or a general mobile;
- a positioning unit configured to receive, by the acquiring unit, mobile state information of the UE and measurement data of the UE, and obtain a correction of the UE according to the mobile state information of the UE and location measurement data of the UE position.
- the acquiring unit includes: a sending module, configured to send, to the UE, indication information, where the indication information is used to instruct the UE to record the UE Mobile status information;
- a receiving module configured to receive mobile state information of the UE.
- the fourth aspect provides a user equipment UE, including: An acquiring unit, configured to acquire mobile state information of the UE;
- a sending unit configured to send the mobile state information of the UE to the network management device, to enable the network management device to obtain, according to the mobile state information of the UE and the location measurement data of the UE acquired by the network management device, The corrected position coordinates of the UE;
- the mobile state information of the UE is used to indicate that the UE is a high speed mobile, a medium speed mobile, or a general mobile.
- the UE further includes: a receiving unit, configured to receive indication information that is sent by the network management device, where the indication information is used to instruct the UE to record the Mobile status information of the UE.
- the fifth aspect provides a positioning system, comprising: the positioning device according to any one of the preceding claims, and the user equipment UE according to any one of the foregoing.
- the method, the device and the system for positioning according to the embodiment of the present invention process the location measurement data of the UE according to the mobile state information of the UE to improve the positioning accuracy, thereby obtaining more accurate location information of the UE in the MDT measurement, and reducing The cost of carrier network optimization.
- FIG. 1 is a schematic flowchart of a positioning method according to an embodiment of the present disclosure
- FIG. 2 is a schematic flowchart of acquiring mobile state information and location measurement data of a UE;
- FIG. 3 is a simulation result of a Kalman filter;
- FIG. 4 is a schematic flowchart of another positioning method according to an embodiment of the present invention.
- FIG. 5 is a schematic structural diagram of a positioning device according to an embodiment of the present disclosure.
- FIG. 6 is a schematic structural diagram of another positioning device according to an embodiment of the present invention
- FIG. 7 is a schematic structural diagram of another device for positioning a device according to an embodiment of the present disclosure
- FIG. 8 is a schematic structural diagram of a user equipment UE according to an embodiment of the present invention
- FIG. 9 is a schematic structural diagram of another user equipment UE according to an embodiment of the present invention
- FIG. 10 is a positioning system according to an embodiment of the present invention; Schematic diagram of the structure.
- an embodiment of the present invention provides a positioning method, as shown in FIG. 1, including:
- the network management device acquires the mobile state information of the user equipment UE and the location measurement data of the UE, where the mobile state information of the UE is used to indicate that the UE is a high speed mobile, a medium speed mobile, or a general mobile.
- the network management device acquires the mobile state information of the UE, where the network management device sends the indication information to the UE, where the indication information is used to instruct the UE to record the mobile state information of the UE.
- the UE may determine the current mobility state information of the UE according to the speed in the current mobile state process.
- the high speed mobile refers to the UE moving speed greater than 80 km/h
- the medium speed mobile refers to the UE moving speed is 30 km/h.
- 80km/h for example, 60km/h
- the general movement means that the moving speed of the UE is less than 30km/h.
- the UE's mobility status information may be measured, recorded, and sent by the UE to the network management device via the logged MDT.
- the network management device may be configured as a separate entity device in the embodiment, and the network management device is an independent physical device.
- the network management device acquiring the location measurement data of the UE may include: directly acquiring from the UE, for example, the UE records original measurement data of the UE, where the original data is used to determine location measurement data of the UE, and the original measurement data of the UE is based on The positioning technology used may vary.
- the original data when using satellite positioning technology, the original data may be the attitude angle of the UE or the distance from the UE to the satellite; when the base station is used for positioning, the original data may be the distance from the UE to the base station at different times; when using the MDT technology,
- the raw data can be MDT measurement data; Which technology is used to obtain the original measurement data of the UE, and there is no limitation here.
- the UE records the original measurement data of the UE, and sends the original measurement data to the base station, so that the base station acquires the location measurement data according to the original measurement data, and reports the location measurement data to the network management device; or directly by the network management device
- the UE records the original measurement data of the UE, and sends the original measurement data to the network management device by using the base station, and the network management device acquires the location measurement data according to the original measurement data.
- the network management device acquiring the mobile state information of the UE and the location measurement data of the UE may include: acquiring, by the network management device, the mobile state information of the UE and the original measurement data of the UE, and acquiring the location measurement data according to the original measurement data, where Correspondingly, the network management device sends the indication information to the UE, where the network management device sends the logged MDT configuration message to the UE via the base station, where the logged MDT configuration message includes an indication that the mobile state information of the UE is requested to be recorded.
- the network management device acquiring the mobile state information of the user equipment UE and the location measurement data of the UE may include: the network management device sending the tracking session activation cancellation to the base station;
- the base station selects the UE according to the tracking session activation message, and sends a logged MDT configuration message to the UE;
- the UE performs logged MDT measurement after converting the RRC connection state to the RRC idle state according to the logged MDT configuration message, and records the mobile state information of the UE and the original measurement data of the UE;
- the network management device receives the mobile state information sent by the UE via the base station and the original measurement data of the UE, and acquires the location measurement data of the UE according to the original measurement data of the UE.
- the method may include:
- the network management system sends a tracking session activation message to the base station.
- the trace session message may include a logged MDT, and a UE's movement Status information and identification of location measurement data requirements.
- the mobile state information of the UE may be used to indicate the mobile state of the UE.
- the mobile state of the UE may include a high speed mobile, a medium speed mobile, or a general mobile, and the mobile state of the UE may be divided according to the actual motion state of the UE.
- the high speed movement means that the moving speed of the UE is greater than 80 km/h
- the medium speed moving means that the moving speed of the UE is between 30 km/h and 80 km/h (for example, 60 km/h).
- the general movement means that the moving speed of the UE is less than 30 km/h.
- the base station performs UE selection according to the tracking session activation message.
- the base station selects the UE according to the identifier of the UE in the tracking session activation message.
- the base station sends the logged MDT configuration information to the selected UE according to the tracking session activation message.
- the logged MDT configuration information may include a logged MDT, and an indication of the UE's mobility status information, raw measurement data requirements.
- the logged MDT configuration information is sent by the base station to the UE in an RRC connected state, where the logged MDT configuration message includes an indication to request to record the mobile state information of the UE.
- the UE is converted from the RRC connected state to the RRC idle state.
- the RRC connection state is converted to the RRC idle state, but the UE does not release the received logged MDT configuration information at the same time, but continues to remain, where
- the logged MDT configuration message includes an indication requesting to record the mobile state information of the UE.
- the UE performs logged MDT measurement according to the logged MDT configuration information, and records the mobile state information of the UE and the original measurement data.
- the UE performs a logged MDT measurement in the RRC idle state.
- the UE may acquire mobility state information by interacting with information between cells serving the UE.
- the cell serving the UE will have the parameter ff (the number of critical reselections at high speed), 1 CR-M (the number of critical reselections during normal movement), L J-CR max (the period of reselection) Transmitted to the UE through system information broadcast, in the idle state UE statistics for a period of time 7 CR R max between the cell reselection number N, by comparing N with the UE V CR-H ff, CR _M to determine the size of the mobile UE status information, for example: if N ⁇ N CR H UE status information of the mobile high-speed movement If N CR ff > ⁇ NCR M ⁇ , the UE mobile state information is a medium speed mobile; if N TV ⁇ M , the UE mobile state information is a general mobile.
- the UE is changed from the RRC idle state to the RRC connected state.
- the RRC connection establishment process is: the UE may first send an RRC connection state establishment request message to the base station side, and switch from the RRC idle state to the RRC connection state after receiving the RRC connection state establishment message sent by the base station side to the UE.
- the UE sends a logged MDT log available indication to the base station.
- the logged MDT log available indication may be sent to the base station in an RRC Connected State Setup Complete message.
- the base station sends a UE information requirement message to the UE.
- the UE sends a logged MDT log containing the mobile state information of the UE and the original measurement data to the base station.
- the base station saves a logged MDT log that is sent by the UE and includes the mobile state information of the UE and the original measurement data.
- the base station sends a logged MDT log containing the UE's mobile state information and the original measurement data to the network management device.
- the network management device receives the logged MDT log including the mobile state information of the UE and the original measurement data, and acquires the location measurement data according to the original measurement data.
- the above example only shows a method for acquiring the mobile state information of the UE and the measurement data by using the logged MDT.
- any other achievable method may be used, which is not limited in this embodiment.
- the network management device obtains a corrected location of the UE according to the mobile state information of the UE and the location measurement data of the UE. Because the UE generally receives noise interference when it acquires the original measurement data, according to the original measurement number. There is a certain error in positioning according to the directly obtained position measurement data, so it is necessary to process the position measurement data according to the moving state of the UE to improve the positioning accuracy.
- the positioning methods for processing the position measurement data by using the mobile state of the UE include feature library matching positioning, positioning according to arrival angle, location based on cell identification, and positioning using Kalman filtering. The following is a detailed description by taking Kalman filter positioning as an example.
- Kalman filtering is a highly efficient recursive filter (autoregressive filter) that predicts the coordinate position and velocity of an object from a limited set of observations of the object's position and noise, ie, as long as it is known
- the optimal estimated value at a moment and the measured value at the current time can calculate the optimal estimated value at the current time, so that it is not necessary to record the observed historical information in a large amount.
- X(k) F-X(k- ⁇ ) + - U(k) + W(k)
- W can be expressed as the motion variance 2 of the motion, and W can be expressed as the coordinate measurement accuracy variance ⁇ ?. According to the optimal estimation at the last moment.
- the value and the measured value of the current time to calculate the optimal estimate of the current time can be achieved by the following steps:
- P(k ⁇ k- ⁇ ) F-P(k- ⁇ k- ⁇ )-F'+Q .
- the corrected position coordinate of the UE is the optimal estimated value of the UE position at each moment
- the optimal estimation value at the current moment can be obtained, which may include:
- the predicted position coordinate of the UE is a vector component in the x direction
- the predicted position coordinate of the UE is a vector component in the y direction
- ⁇ is a vector component of the speed of the UE in the X direction
- the speed of the UE is in the y direction.
- the vector component, t is the system equation update time interval
- a is the acceleration of the UE at time I
- a x is the vector component of the acceleration a in the X direction
- a y is the vector component of the acceleration a in the y direction.
- the acceleration a can be regarded as the amount of noise disturbance to the system, and it is assumed that the acceleration a remains unchanged between the moments, that is, the acceleration a of the UE is constant during the time;
- the vector component of the measurement position coordinate of the UE in the x direction at time k the vector component of the measurement position coordinate of the UE at the time k in the y direction, ⁇ , the direct measurement error at time k, the measurement position coordinate (ie, the position) Measurement data) Obtained from the raw measurement data of the UE.
- the acceleration and a-vehicle accelerations measured by the MDT range from 0 to 6 m/. ⁇ . Can be based on
- the mobile state information setting of the UE For example, the standard deviation ⁇ of the acceleration a depends on the topography. It can be configured as follows: When the mobile state of the UE is high speed (about 80 kmph or more), ⁇ . Configured as 4 ⁇ 5m/; When the mobile state of the UE is medium speed (about 30km/h ⁇ 80km/h, for example, about 60km/h), ⁇ . Configured to 2 ⁇ 3m/ When the mobile state of the UE is normal movement (about 30kmph or less), ⁇ . Configured to 0 ⁇ 1 m/.
- At least the system equation, the measurement system equation, and the motion variance variance Q of the UE at time -1 are obtained to obtain the corrected position coordinates of the UE.
- each of the actual variables in the Kalman filtering step 1) - step 5 is: Where ⁇ " is the standard deviation of the direct measurement error ⁇ . In actual engineering, it can be configured as a fixed empirical value according to the curvature of the UE motion trajectory.
- Substituting the above variables into the above Kalman filter step 1) - step 5) can obtain the UE's positional coordinates. Dynamically configuring the perturbation variance Q of the motion based on the UE's movement state information can improve the positioning accuracy.
- the simulation result of the Kalman filtering of the UE under different mobile state information wherein the horizontal axis is ⁇ .
- the vertical axis is an error between the corrected position coordinate and the measured position coordinate, wherein the measured position coordinate is obtained by the measurement data of the UE.
- FIG. 3A the simulation result of the Kalman filter obtained when the moving speed of the UE is 100 km/h, at this time, the UE is moving at a high speed, ⁇ .
- the error is the smallest;
- the error is the smallest; as shown in Fig. 3C, the simulation result of the Kalman filter obtained when the moving speed of the UE is 10km/h, at this time, the UE is a general movement, ⁇ .
- the error is minimal when configured as 0-lm/.
- the acceleration standard deviation determined based on the movement state information of the UE.
- the error of the Kalman filter can be minimized, thereby improving the positioning accuracy of the UE.
- the embodiment of the present invention provides a method for positioning, and processing location measurement data of the UE according to the mobile state information of the UE to improve positioning accuracy, which can improve accuracy of location information of the UE required in the MDT measurement, and reduce operator network optimization. the cost of.
- the state information dynamically configures the Kalman filter parameters to improve the positioning accuracy, and overcomes the prior art.
- the motion disturbance variance Q is set to a constant according to experience, and the Kalman is not
- the filtered positioning result has the highest precision gain, and even a negative gain defect.
- FIG. 4 is a schematic diagram of another positioning method according to an embodiment of the present invention. As shown in the figure, the following steps may be included:
- the user equipment UE acquires mobile state information of the UE.
- the UE sends the mobile state information of the UE to the network management device, so that the network management device obtains the location information according to the mobile state information of the UE and the location measurement data of the UE acquired by the network management device.
- the mobile state information of the UE is used to indicate that the UE is a high speed mobile, a medium speed mobile, or a general mobile.
- the method may further include: receiving the indication information sent by the network management device, where the indication information is used to instruct the UE to record the mobile state information of the UE.
- the method for positioning according to the embodiment of the present invention by sending the mobile state information of the UE to the network management device, causes the network management device to process the location measurement data of the UE according to the mobile state information of the UE to improve the positioning accuracy, and the MDT can be improved.
- the positioning accuracy of the location information of the UE required in the measurement reduces the cost of the operator network optimization.
- the Kalman filter parameters are dynamically configured according to the mobile state information of the UE, and the positioning accuracy is improved.
- the prior art overcomes the Kalman filter of the measurement data, and empirically sets the motion variance Q of the motion to be constant. The accuracy gain of the Kalman-filtered positioning result cannot be maximized, and even a negative gain defect may occur.
- the embodiments of the present invention further provide an apparatus embodiment for implementing the steps and methods in the foregoing method embodiments.
- the embodiments of the present invention are applicable to a base station or a UE in various communication systems.
- FIG. 5 is a structural diagram of a positioning device according to an embodiment of the present invention.
- the positioning device includes: an obtaining unit 501, a processing unit 502, where the acquiring unit 501 is configured to acquire mobile state information and a location of the user equipment UE. Transmitting the location measurement data of the UE, and transmitting the mobile state information of the UE and the location measurement data of the UE to the positioning unit 502, where the mobile state information of the UE is used to indicate the
- the UE is a high speed mobile, a medium speed mobile or a general mobile.
- the obtaining unit 501 when the acquiring unit 501 acquires the mobile state information of the UE, may include: the positioning device sends the indication information to the UE, where the indication information is used to instruct the UE to record the mobile state information of the UE; The mobile state information of the UE and the measurement data of the UE.
- the locating device can be set on the base station or can be an independent physical device. In this embodiment, the locating device is an independent physical device.
- the obtaining, by the acquiring unit 501, the location measurement data of the UE may include: directly acquiring from the UE, for example, the UE records original measurement data of the UE, where the original data is used to determine location measurement data of the UE.
- the UE records the original measurement data of the UE, and sends the original measurement data to the base station, so that the base station acquires the location measurement data according to the original measurement data, and reports the location measurement data to the network management device; or directly by the network management device
- the UE records the original measurement data of the UE, and sends the original measurement data to the network management device by using the base station, and the network management device acquires the location measurement data according to the original measurement data.
- the obtaining unit 501 may include:
- the sending module 5011 is configured to send the indication information to the UE, where the indication information is used to instruct the UE to record the mobile state information of the UE.
- the sending module 5011 may be specifically configured to send to the UE via the base station.
- the logged MDT configuration message where the logged MDT configuration message includes an indication to request to record the mobile state information of the UE.
- the receiving module 5012 is configured to receive the mobile state information of the UE that is sent by the UE.
- a positioning unit 502 configured to receive, by the acquiring unit 501, mobile state information of the UE and location measurement data of the UE, and obtain the UE according to the mobile state information of the UE and location measurement data of the UE. Corrected position. Because the UE generally receives noise interference when acquiring the original measurement data, there is a certain error in positioning according to the position measurement data directly acquired by the original measurement data. Therefore, the position measurement data needs to be processed according to the moving state of the UE to improve the positioning accuracy.
- the positioning method for processing the position measurement data by using the moving state of the UE has a feature library matching positioning, according to the angle of arrival Bit, based on cell identification and Kalman filter positioning, the following is a detailed description of Kalman filter positioning.
- Kalman filtering is a highly efficient recursive filter (autoregressive filter) that predicts the coordinate position and velocity of an object from a limited set of observations of the object's position and noise, ie, as long as it is known
- the optimal estimated value at a moment and the measured value at the current time can calculate the optimal estimated value at the current time, so that it is not necessary to record the observed historical information in a large amount.
- X(k) F-X(k- ⁇ ) + - U(k) + W(k)
- z(k) nx(k)+v(k) is the time system state, which is the control quantity of the system at the moment, 2 ( ⁇ ) is the measured value of the time; F, B, H are the system parameters; W(k, W is system noise and measurement noise.
- W can be expressed as the motion variance 2 of the motion, W can be expressed as the coordinate measurement accuracy variance ⁇ ?
- the estimated value and the measured value of the current time are used to calculate the optimal estimate of the current time by the following steps:
- P(k ⁇ k- ⁇ ) F-P(k- ⁇ k- ⁇ )-F'+Q .
- X(k ⁇ k) X(k ⁇ k-l) + Kg(k)-[Z(k)-1i-X(k ⁇ k-l)].
- the positioning unit 502 performs Kalman filtering on the location measurement data of the UE according to the mobile state information of the UE, and obtains the corrected position coordinates of the UE.
- the corrected position coordinate of the UE is the optimal position of the UE at each moment.
- the estimated value can be obtained from the optimal estimated value at the previous moment.
- the positioning unit 502 may include:
- Determining module 5021 determining system equations and measurement system equations from time to time k k l to time k;
- the predicted position coordinate of the UE is a vector component in the x direction
- the predicted position coordinate of the UE is a vector component in the y direction
- ⁇ is a vector component of the speed of the UE in the X direction
- the speed of the UE is in the y direction.
- the vector component, t is the system equation update time interval
- a is the acceleration of the UE at time I
- a x is the vector component of the acceleration a in the X direction
- a y is the vector component of the acceleration a in the y direction.
- the acceleration a can be regarded as the amount of noise disturbance to the system, and it is assumed that the acceleration a remains unchanged between the moments, that is, the acceleration a of the UE is constant during the time;
- the vector component of the measurement position coordinate of the UE at the time k in the X direction is k
- the measurement position coordinate ie, the position measurement data
- the first acquisition module 5022 And acquiring a disturbance variance Q of the motion according to the system equation of the UE at the moment to the moment and the movement state information of the UE;
- the perturbation variance Q of the motion of the UE can be calculated according to the system equation of the UE at time -1 from the time provided by the determining module 5021, as follows,
- the mobile state information setting of the UE For example, the standard deviation ⁇ of the acceleration a depends on the topography. It can be configured as follows: When the mobile state of the UE is high speed (about 80 kmph or more), ⁇ . Configured as 4 ⁇ 5m/; When the mobile state of the UE is medium speed (about 30km/h ⁇ 80km/h, for example, about 60km/h), ⁇ . Configured as 2 ⁇ 3m/ y 2 ; When the mobile state of the UE is general movement (about 30km/h or less), ⁇ . Configured as 0 ⁇ lm/.
- the second obtaining module 5023 is configured to obtain the corrected position coordinates of the UE according to at least the system equation of the UE at the time of -1 to the time, the measurement system equation, and the disturbance variance Q of the motion.
- the first obtaining module 5022 may determine that each of the actual variables in the Kalman filtering step 1) - step 5) are: Where ⁇ " is the standard deviation of the direct measurement error ⁇ . In actual engineering, it can be configured as a fixed empirical value according to the curvature of the UE motion trajectory.
- Substituting the above variables into the above Kalman filter step 1) - step 5) can obtain the UE's positional coordinates. Dynamically configuring the perturbation variance Q of the motion based on the UE's movement state information can improve the positioning accuracy.
- the simulation result of the Kalman filtering of the UE in different moving states wherein the horizontal axis is ⁇ .
- the vertical axis is an error between the corrected position coordinate and the measured position coordinate, wherein the measured position coordinate is obtained by the measurement data of the UE.
- FIG. 3A the simulation result of the Kalman filter obtained when the moving speed of the UE is 100 km/h, at this time, the UE is moving at a high speed, ⁇ .
- the error is the smallest;
- the error is the smallest; as shown in Fig. 3C, the simulation result of the Kalman filter obtained when the moving speed of the UE is 10km/h, at this time, the UE is a general movement, ⁇ .
- the error is minimal when configured as 0-lm/.
- the acceleration standard deviation ⁇ is determined according to the moving state of the UE.
- the error of the Kalman filter can be minimized, thereby improving the positioning accuracy of the UE.
- the positioning device processes the measurement data of the UE according to the mobile state information of the UE to improve the positioning accuracy, so that the location information of the required UE in the MDT measurement is more accurate, and the cost of the operator network planning is reduced.
- the network tube configures the motion variance Q of the motion according to the mobile state information of the UE and performs Kalman filtering on the measurement data of the UE, thereby maximizing the UE positioning accuracy gain based on the Kalman filtering technique.
- the disturbance Q of the motion is set to a constant according to experience, and the accuracy gain of the Kalman-filtered positioning result is not maximized, and even a negative gain occurs.
- the foregoing sending module may be a transmitter or a transceiver
- the above receiving module may be a receiver or a transceiver
- the sending module and the receiving module may be integrated to form a transceiver unit, which is implemented as a transceiver corresponding to hardware
- the obtaining unit and the positioning unit may be embedded in the hardware of the positioning device in hardware or may be stored in the memory of the positioning device in a software form, so that the processor calls to perform the operations corresponding to the above modules.
- the processor can be a central processing unit (CPU), a microprocessor, a microcontroller, or the like.
- FIG. 7 is a schematic structural diagram of a positioning apparatus according to an embodiment of the present invention. As shown in FIG.
- the positioning apparatus includes: a transmitter 701, a receiver 702, a memory 703, and a transmitter 701 and a receiver 702, respectively.
- the locating device may also include a common component such as an input/output device, and the embodiment of the present invention is not limited thereto.
- a set of program codes is stored in the memory 703, and the processor 704 is used to call the memory.
- the program code in 703, configured to: obtain the mobile state information of the user equipment UE, and the location measurement data of the UE, where the mobile state information of the UE is used to indicate that the UE is a high speed mobile, medium speed Moving or moving in general; obtaining a corrected position of the UE according to the mobile state information of the UE and the location measurement data of the UE.
- the transmitter 701 is configured to send the indication information to the UE, where the indication information is used to indicate that the UE records the mobile state information of the UE.
- the transmitter 701 may be specifically configured to send a logged to the UE via the base station.
- the MDT configuration message, where the logged MDT configuration message includes an indication to request to record the mobile state information of the UE.
- the receiver 702 is configured to receive mobile state information of the UE that is sent by the UE.
- obtaining the mobile state information of the UE may include: locating the device to the The UE sends the indication information, where the indication information is used to indicate that the UE records the mobile state information of the UE.
- the acquiring unit 501 receives the mobile state information of the UE and the measurement data of the UE.
- the locating device can be set on the base station or can be an independent physical device. In this embodiment, the locating device is an independent physical device.
- obtaining location measurement data of the UE may include: directly acquiring from the UE, for example, the UE records original measurement data of the UE, where the original data is used to determine location measurement data of the UE. Recording, by the UE, original measurement data of the UE, and acquiring location measurement data according to the original measurement data, and transmitting the location measurement data to the network management device via the base station; or the location measurement data of the UE is indirectly obtained by using other network entities, for example, The UE records the original measurement data of the UE, and sends the original measurement data to the base station, so that the base station acquires the location measurement data according to the original measurement data, and reports the location measurement data to the network management device; or directly by the network management device For example, the UE records the original measurement data of the UE, and sends the original measurement data to the network management device by using the base station, and the network management device acquires the location measurement data according to the original measurement data.
- the positioning method for processing the position measurement data by using the UE's mobile state has feature library matching positioning, positioning according to the arrival angle, cell identification based positioning, and Kalman filter positioning.
- the Kalman filter positioning is taken as an example for detailed description.
- Kalman filtering is a highly efficient recursive filter (autoregressive filter) that predicts the coordinate position and velocity of an object from a limited set of observations of the object's position and noise, ie, as long as it is known
- the optimal estimated value at a moment and the measured value at the current time can calculate the optimal estimated value at the current time, so that it is not necessary to record the observed historical information in a large amount.
- z(k) n- x(k)+v(k) is the time system state, which is the control quantity of the system at the moment, 2 ( ⁇ ) is the measured value of the time; F, B, H are the system parameters; Is system noise and measurement noise, examples
- W can be expressed as the motion variance 2 of the motion, and W can be expressed as the coordinate measurement accuracy variance.
- P(k ⁇ k- ⁇ ) F-P(k- ⁇ k- ⁇ )-F'+Q .
- X(k ⁇ k) X(k ⁇ k-l) + Kg(k)-[Z(k)-1i-X(k ⁇ k-l)].
- the corrected position coordinate of the UE is the optimal estimated value of the UE position at each moment
- the optimal estimation value at the current moment can be obtained, which may include:
- the predicted position coordinate of the UE is a vector component in the x direction
- the predicted position coordinate of the UE is a vector component in the y direction
- ⁇ is a vector component of the speed of the UE in the X direction
- the speed of the UE is in the y direction.
- the vector component, t is the system equation update time interval
- a is the acceleration of the UE at time I
- a x is the vector component of the acceleration a in the X direction
- a y is the vector component of the acceleration a in the y direction.
- the acceleration a can be regarded as the amount of noise disturbance to the system, and it is assumed that the acceleration a remains unchanged between the moments, that is, the acceleration a of the UE is constant during the time;
- the vector component of the measurement position coordinate of the UE in the x direction at time k the vector component of the measurement position coordinate of the UE at the time k in the y direction, ⁇ , the direct measurement error at time k, the measurement position coordinate (ie, the position) Measurement data) Obtained from the raw measurement data of the UE.
- the acceleration and a-vehicle accelerations measured by the MDT range from 0 to 6 m/. ⁇ . Can be based on
- the mobile state information setting of the UE For example, the standard deviation ⁇ of the acceleration a depends on the topography. It can be configured as follows: When the mobile state of the UE is high speed (about 80 kmph or more), ⁇ . Configured as 4 ⁇ 5m/; When the mobile state of the UE is medium speed (about 30km/h ⁇ 80km/h, for example, about 60km/h), ⁇ . Configured to 2 ⁇ 3m/; When the UE's movement state is normal movement (about 30kmph or less), ⁇ . Configured to 0 ⁇ 1 m/.
- At least the system equation, the measurement system equation, and the motion variance variance Q of the UE at time -1 are obtained to obtain the corrected position coordinates of the UE.
- each of the actual variables in the Kalman filtering step 1) - step 5) is:
- ⁇ is the standard deviation of the direct measurement error ⁇ . In actual engineering, it can be configured as a fixed empirical value according to the curvature of the UE motion trajectory.
- Step 1) - step 5) of the above Kalman filter can obtain the positional coordinates of the UE.
- Dynamically configuring the perturbation variance Q of the motion according to the mobile state information of the UE can improve the positioning accuracy.
- the simulation result of the Kalman filtering of the UE in different moving states wherein the horizontal axis is ⁇ .
- the vertical axis is an error between the corrected position coordinate and the measured position coordinate, wherein the measured position coordinate is obtained by the measurement data of the UE.
- FIG. 3A the simulation result of the Kalman filter obtained when the moving speed of the UE is 100 km/h, at this time, the UE is moving at a high speed, ⁇ .
- the error is the smallest;
- the error is the smallest; as shown in Fig. 3C, the simulation result of the Kalman filter obtained when the moving speed of the UE is 10km/h, at this time, the UE is a general movement, ⁇ .
- the error is minimal when configured as 0-lm/.
- the acceleration standard deviation ⁇ is determined according to the moving state of the UE.
- the error of the Kalman filter can be minimized, thereby improving the positioning accuracy of the UE.
- the positioning device shown in FIG. 5 to FIG. 7 can implement any of the methods provided by the foregoing method embodiments.
- the positioning device provided by the present invention processes the measurement data of the UE according to the mobile state information of the UE to improve the positioning accuracy, so that the location information of the UE required in the MDT measurement is more accurate, thereby reducing the cost of the operator network optimization.
- the network management device configures the motion variance Q of the motion according to the mobile state information of the UE and performs Kalman filtering on the measurement data of the UE, thereby maximizing the UE positioning accuracy gain based on the direct measurement data and the Kalman filtering technique.
- the disturbance variance Q of the motion is set to a constant according to experience, and the accuracy gain of the Kalman-filtered positioning result is not maximized, and even a negative gain defect occurs.
- FIG. 8 is a schematic structural diagram of a user equipment UE according to an embodiment of the present invention.
- the UE is used to implement the positioning method shown in FIG. 4, where the user equipment UE includes:
- the obtaining unit 801 is configured to acquire mobility state information of the UE.
- the sending unit 802 is configured to send the mobile state information of the UE to the network management device, so that the network management device obtains, according to the mobile state information of the UE and the location measurement data of the UE acquired by the network management device. Corrected position coordinates of the UE;
- the mobile state information of the UE is used to indicate that the UE is a high speed mobile, a medium speed mobile, or a general mobile. Further, the UE may further include: a receiving unit 803, configured to receive the indication information that is sent by the network management device, where the indication information is used to instruct the UE to record the mobile state information of the UE.
- the user equipment UE which is provided by the embodiment of the present invention, sends the mobile state information of the UE and the measurement data of the UE to the network management device, so that the network management device processes the measurement data of the UE according to the mobile state information of the UE to improve the positioning.
- the accuracy makes the position information of the required UE in the MDT measurement more accurate, thereby reducing the cost of the operator network optimization.
- the network management device configures the motion variance Q of the motion according to the mobile state information of the UE and performs Kalman filtering on the measurement data of the UE, thereby maximizing the UE positioning accuracy gain based on the direct measurement data and the Kalman filtering technique.
- the disturbance Q of the motion is set to a constant according to experience, and the accuracy gain of the Kalman-filtered positioning result is not maximized, and even a negative gain occurs.
- the above sending unit may be a transmitter
- the above receiving unit may be a receiver
- the transmitter and the receiver may be integrated to form a transceiver
- the above obtaining unit may be embedded in hardware or independent of the user.
- the processor of the device UE may also be stored in the memory of the user equipment UE in the form of software, so that the processor calls to perform operations corresponding to the above modules, and the processor may be a central processing unit (CPU), a microprocessor, MCU, etc.
- FIG. 9 is a schematic structural diagram of a user equipment UE according to an embodiment of the present invention.
- the user equipment UE includes: a transmitter 901, a receiver 902, a memory 903, and a transmitter 901 and a receiver, respectively.
- the processor 904 is coupled to the memory 903.
- the user equipment UE may also include general-purpose components such as input and output devices, and the embodiments of the present invention are not limited thereto.
- a set of program codes is stored in the memory 903, and the processor 904 is used to call the memory.
- the program code in 903, configured to: perform acquiring the mobile state information of the UE;
- the transmitter 901 is configured to send the mobile state information of the UE to the network management device, so that the network management device obtains, according to the mobile state information of the UE and the location measurement data of the UE acquired by the network management device, Corrected position coordinates of the UE;
- the mobile state information of the UE is used to indicate that the UE is a high speed mobile, a medium speed mobile, or a general mobile.
- the receiver 902 is configured to receive the indication information sent by the network management device, where the indication information is used to instruct the UE to record the mobile state information of the UE.
- the user equipment UE which is provided by the embodiment of the present invention, sends the mobile state information of the UE and the measurement data of the UE to the network management device, so that the network management device processes the measurement data of the UE according to the mobile state information of the UE to improve the positioning.
- the accuracy makes the position information of the required UE in the MDT measurement more accurate, thereby reducing the cost of the operator network optimization.
- the network management device configures the motion variance Q of the motion according to the mobile state information of the UE and performs Kalman filtering on the measurement data of the UE, thereby maximizing the UE positioning accuracy gain based on the direct measurement data and the Kalman filtering technique.
- the disturbance Q of the motion is set to a constant according to experience, and the accuracy gain of the Kalman-filtered positioning result is not maximized, and even a negative gain defect occurs.
- An embodiment of the present invention provides a positioning system.
- the method includes: a positioning device and a user equipment UE, where
- a positioning device configured to acquire mobile state information of the user equipment UE and location measurement data of the UE, where the mobile state information of the UE is used to indicate that the UE is a high speed mobile, a medium speed mobile, or a general mobile;
- the network management device obtains the corrected location of the UE according to the mobile state information of the UE and the location measurement data of the UE.
- the user equipment UE is configured to send the mobile state information of the UE to the network management device.
- the positioning system may further include: a base station, configured to receive indication information that is sent by the network management device, where the indication information is used to instruct the UE to record mobility state information of the UE, and forward the UE The mobile state information of the UE transmitted.
- a base station configured to receive indication information that is sent by the network management device, where the indication information is used to instruct the UE to record mobility state information of the UE, and forward the UE The mobile state information of the UE transmitted.
- the process of acquiring the mobile state information of the user equipment UE and the location measurement data of the UE may be referred to the foregoing embodiment, and details are not described herein again.
- the positioning method for processing the position measurement data by using the moving state of the UE has a feature library matching positioning, according to the angle of arrival Bit, location based on cell identity and location using Kalman filtering. Kalman filtering is usually applied to the UE positioning result to reduce the influence of noise and improve the positioning accuracy.
- the positioning system processes the measurement data of the UE according to the mobile state information of the UE to improve the positioning accuracy, so that the location information of the UE required in the MDT measurement is more accurate, thereby reducing the cost of the operator network optimization.
- the network management device configures the motion variance Q of the motion according to the mobile state information of the UE and performs Kalman filtering on the measurement data of the UE, thereby maximizing the UE positioning accuracy gain based on the direct measurement data and the Kalman filtering technique.
- the disturbance variance Q of the motion is set to be constant, and the accuracy gain of the Kalman-filtered positioning result is not maximized, and even a negative gain occurs.
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Abstract
本发明实施例公开了一种定位的方法、设备及系统,涉及通信领域,根据用户设备UE的移动状态信息和所述UE的位置测量数据确定所述UE的修正位置,可以提高UE的定位精度。本发明实施例提供的方法包括:网络管理设备获取UE的移动状态信息以及所述UE的位置测量数据,其中,所述UE的移动状态信息用以指示所述UE为高速移动、中速移动或一般移动;所述网络管理设备根据所述UE的移动状态信息和所述UE的位置测量数据,得到所述UE的修正位置。本发明实施例可以提高获取的UE定位精度,进一步提高最小化路测的精度。
Description
一种定位的方法、 设备及系统 技术领域
本发明涉及通信领域, 尤其涉及一种定位的方法、 设备及系统。
背景技术
最小化路测 ( Minimization of Drive Tests , 简称 MDT )是 UE根据网 络配置信息向基站上报测量信息, 基站根据 UE 上报的位置测量数据对 UE进行定位的技术。
UE 上报的位置测量数据一般会受到噪声影响而使定位结果产生误 差, 所以通常需要对 UE 的位置测量数据进行处理, 以提高定位精度, 比如对 UE的位置测量数据进行卡尔曼滤波。 在卡尔曼滤波过程中, UE 运动的扰动方差 Q对于定位结果的精度增益具有非常重要的作用, 现有 技术中 Q—般根据经验各设定为一个常数。 发明人发现现有技术中至少存在如下问题:
现有 MDT测量中对 UE测量数据进行处理时, UE定位精度不高使 得 MDT测量中所需 UE的位置信息不准确,提高了运营商网络优化的成 本。
发明内容
本发明的实施例提供一种定位的方法、 设备及系统, 根据 UE的移动 状态信息对 UE的位置测量数据进行处理, 从而提高定位精度。
为达到上述目的, 本发明实施例釆用的技术方案为,
第一方面, 本发明实施例提供一种定位的方法, 包括:
网络管理设备获取用户设备 UE的移动状态信息以及所述 UE的位置 测量数据, 其中, 所述 UE的移动状态信息用以指示所述 UE为高速移动、 中速移动或一般移动; 所述网络管理设备根据所述 UE的移动状态信息和 所述 UE的位置测量数据, 得到所述 UE的修正位置。
在第一种可能的实现方式中, 根据第一方面, 所述网络管理设备获取
所述 UE的移动状态信息, 包括:
所述网络管理设备向所述 UE发送指示信息, 所述指示信息用于指示 所述 UE记录所述 UE的移动状态信息;
所述网络管理设备接收所述 UE发送的所述 UE的移动状态信息。 第二方面, 提供一种定位的方法, 包括:
用户设备 UE获取所述 UE的移动状态信息;
所述 UE向网络管理设备发送所述 UE的移动状态信息, 以使得所述 网络管理设备根据所述 UE的移动状态信息和所述网络管理设备获取的所 述 UE的位置测量数据得到所述 UE的修正位置; 其中, 所述 UE的移动 状态信息用以指示所述 UE为高速移动、 中速移动或一般移动。
在第一种的能的实现方式中, 根据第二方面, 所述用户设备 UE获取 所述 UE的移动状态信息之前, 该方法还包括:
所述 UE接收所述网络管理设备发送的指示信息, 所述指示信息用于 指示所述 UE记录所述 UE的移动状态信息。
第三方面, 提供一种定位设备, 包括:
获取单元, 用于获取用户设备 UE的移动状态信息以及所述 UE的位 置测量数据, 以及将所述 UE的移动状态信息和所述 UE的位置测量数据 传输给定位单元, 其中, 所述 UE的移动状态信息用以指示所述 UE为高 速移动、 中速移动或一般移动;
定位单元, 用于从所述获取单元接收所述 UE的移动状态信息和所述 UE的测量数据, 以及根据所述 UE的移动状态信息和所述 UE的位置测 量数据, 得到所述 UE的修正位置。
在第一种可能的实现方式中, 根据第三方面, 所述获取单元, 包括: 发送模块, 用于向所述 UE发送指示信息, 所述指示信息用于指示所 述 UE记录所述 UE的移动状态信息;
接收模块, 用于接收所述 UE的移动状态信息。
第四方面、 提供一种用户设备 UE, 包括:
获取单元, 用于获取所述 UE的移动状态信息;
发送单元, 用于向网络管理设备发送所述 UE的移动状态信息, 以使 得所述网络管理设备根据所述 UE的移动状态信息和所述网络管理设备获 取的所述 UE的位置测量数据得到所述 UE的修正位置坐标;
其中, 所述 UE的移动状态信息用以指示所述 UE为高速移动、 中速 移动或一般移动。
在第一种可能的实现方式中, 根据第四方面, 所述 UE还包括: 接收单元, 用于接收所述网络管理设备发送的指示信息, 所述指示信 息用于指示所述 UE记录所述 UE的移动状态信息。
第五方面, 提供一种定位系统, 包括: 上述任一项所述的定位设备以 及上述任一项所述的用户设备 UE。
本发明实施例提供的用于定位的方法、 设备及系统, 根据 UE的移动 状态信息对 UE 的位置测量数据进行处理以提高定位精度, 从而在 MDT 测量中能够获取 UE更加精确的位置信息,降低了运营商网络优化的成本。 附图说明
为了更清楚地说明本发明实施例或现有技术中的技术方案,下面将对 实施例或现有技术描述中所需要使用的附图作简单地介绍, 显而易见地, 下面描述中的附图仅仅是本发明的一些实施例,对于本领域普通技术人员 来讲, 在不付出创造性劳动的前提下, 还可以根据这些附图获得其他的附 图。
图 1为本发明实施例提供的一种定位方法流程示意图;
图 2为获取 UE的移动状态信息以及位置测量数据的流程示意图; 图 3为卡尔曼滤波仿真结果图;
图 4为本发明实施例提供的另一种定位方法流程示意图;
图 5为本发明实施例提供的一种定位设备的结构示意图;
图 6为本发明实施例提供的另一种定位设备的结构图示意图; 图 7为本发明实施例提供的另一种定位设备的装置结构示意图;
图 8为本发明实施例提供的一种用户设备 UE的结构示意图; 图 9为本发明实施例提供的另一种用户设备 UE的结构示意图; 图 10为本发明实施例提供的一种定位系统的结构示意图。
具体实施方式 下面将结合本发明实施例中的附图, 对本发明实施例中的技术方案 进行清楚、 完整地描述, 显然, 所描述的实施例仅仅是本发明一部分实 施例, 而不是全部的实施例。 基于本发明中的实施例, 本领域普通技术 人员在没有做出创造性劳动前提下所获得的所有其他实施例, 都属于本 发明保护的范围。
一方面, 本发明实施例提供了一种定位方法, 参见图 1 , 包括:
101 : 网络管理设备获取用户设备 UE 的移动状态信息以及所述 UE 的位置测量数据, 其中, 所述 UE的移动状态信息用以指示所述 UE为高 速移动、 中速移动或一般移动。
示例性的, 网络管理设备获取 UE的移动状态信息, 可以包括: 网络 管理设备向所述 UE发送指示信息, 所述指示信息用于指示所述 UE记录 所述 UE的移动状态信息; 网络管理设备接收所述 UE的移动状态信息以 及所述 UE的测量数据。 所述 UE可以根据当前移动状态过程中的速度, 确定当前所述 UE的移动状态信息, 例如, 高速移动指 UE的移动速度大 于 80km/h, 中速移动指 UE 的移动速度为 30km/h~80km/h 之间 (例如 60km/h ) , 一般移动指 UE的移动速度小于 30km/h。 对于上述高速移动、 中速移动和一般移动可以根据实际工程经验进行设定,这里不作限制。 UE 的移动状态信息可以由该 UE通过 logged MDT测量、 记录并发送给网络 管理设备。 网络管理设备可以设置在基站上, 也可以为独立的实体设备, 本实施例以网络管理设备为独立的实体设备进行说明。 示例性的, 网络管理设备获取 UE的位置测量数据可以包括: 直接从 UE 获取, 例如, UE 记录该 UE 的原始测量数据, 该原始数据用于确定 UE的位置测量数据, UE的原始测量数据根据所釆用的定位技术的不同而 可能不同。 例如釆用卫星定位技术时, 该原始数据可以是 UE的姿态角或 UE到卫星的距离; 釆用基站定位时, 该原始数据可以是不同时刻 UE到 基站的距离; 釆用 MDT技术时, 该原始数据可以是 MDT测量数据; 釆
取何种技术获取 UE的原始测量数据, 在这里不作限制。 在 UE记录该 UE 的原始测量数据并可以根据该原始测量数据获取位置测量数据, 并经由基 站将该位置测量数据发送给网络管理设备; 或者 UE的位置测量数据通过 其他网络实体间接获取, 例如, UE记录该 UE 的原始测量数据, 并将该 原始测量数据发送给基站,使得基站根据该原始测量数据获取位置测量数 据, 并将该位置测量数据上报给网络管理设备; 或者由该网络管理设备直 接获取, 例如, UE记录该 UE 的原始测量数据, 并将该原始测量数据经 基站发送给网络管理设备, 网络管理设备根据该原始测量数据获取位置测 量数据。
具体的, 网络管理设备获取 UE的移动状态信息以及 UE的位置测量 数据可以包括: 网络管理设备经由基站获取 UE 的移动状态信息以及 UE 的原始测量数据, 并根据该原始测量数据获取位置测量数据, 相应的, 网络管理设备向 UE发送指示信息, 可以包括: 网络管理设备经由基 站向 UE发送 logged MDT配置消息, 其中, logged MDT配置消息包括请 求记录 UE的移动状态信息的指示。
示例性的, 网络管理设备获取用户设备 UE的移动状态信息以及所述 UE的位置测量数据, 可以包括: 网络管理设备向基站发送跟踪会话激活消 , ;
基站根据跟踪会话激活消息选择 UE,并向 UE发送 logged MDT配置 消息;
UE根据 logged MDT配置消息从 RRC连接态转化为 RRC空闲态后 进行 logged MDT测量, 并记录 UE的移动状态信息以及 UE的原始测量 数据;
网络管理设备接收 UE经由基站发送的移动状态信息以及 UE的原始 测量数据, 并根据 UE的原始测量数据获取 UE的位置测量数据。
下面以一个具体示例对网络管理设备获取 UE的移动状态信 , 的移动 状态信息以及 UE的位置测量数据的过程进行说明, 参见图 2 , 可以包括:
201 : 网络管理系统向基站发送跟踪会话激活消息。 示例性的, 该跟踪会话消息可以包含 logged MDT , 以及 UE的移动
状态信息以及位置测量数据需求的标识。
示例性的, UE的移动状态信息可以用来指示 UE的移动状态, 例如, UE的移动状态可以包括高速移动、 中速移动或者一般移动, 可以根据 UE 实际的运动状态来划分 UE的移动状态, 例如, 根据步行或车载进行划分 时, 可以认为, 高速移动指 UE的移动速度大于 80km/h, 中速移动指 UE 的移动速度为 30km/h~80km/h之间 (例如 60km/h ) , —般移动指 UE的移 动速度小于 30km/h。
202: 基站根据跟踪会话激活消息进行 UE选择。
示例性的, 基站根据跟踪会话激活消息中的 UE的标识选择 UE。
203 :基站根据跟踪会话激活消息向选择的 UE发送 logged MDT配置 信息。
示例性的 , logged MDT配置信息可以包含 logged MDT , 以及 UE的 移动状态信息、 原始测量数据需求的标识。
示例性的, logged MDT配置信息由基站在 RRC连接态下发给 UE, 其中, 所述 logged MDT配置消息包括请求记录所述 UE的移动状态信息 的指示。
204: UE由 RRC连接态转化为 RRC空闲态。
示例性的,当 UE接收到基站发送的 logged MDT配置信息时,由 RRC 连接态转化为 RRC空闲态, 但是 UE不会将接收到的 logged MDT配置信 息同时释放, 而是继续保留, 其中, 所述 logged MDT配置消息包括请求 记录所述 UE的移动状态信息的指示。
205: UE根据 logged MDT配置信息进行 logged MDT测量并记录 UE 的移动状态信息以及原始测量数据。
示例性的, UE在 RRC空闲态进行 logged MDT测量。
示例性的, UE可以通过与服务于该 UE的小区之间的信息交互获取 移动状态信息。 例如: 服务于该 UE 的小区将参数 ff (高速移动时的 临界重选次数) 、 1 CR—M (一般移动时的临界重选次数) 、 L J- CR max (重选次 数的时间段) 通过系统信息广播发送给 UE, 在空闲态 UE统计在一段时
间 7 CRR max内小区重选次数 N, UE通过比较 N跟 V CR—H ff、 CR _M的大小来确 定 UE的移动状态信息, 例如: 如果 N≥ NCR H UE移动状态信息为高速移动; 如果 NCR ff > ≥ NCR M ^ 则 UE移动状态信息为中速移动; 如果 N TV^ M , 则 UE移动状态信息为一般移动。 206: UE由 RRC空闲态转为 RRC连接态。
示例性的, RRC连接建立过程为: UE首先可以向基站侧发送 RRC 连接态建立请求消息; 在接收到基站侧向 UE发送的 RRC连接态建立消 息后由 RRC空闲态转为 RRC连接态。
207: UE向基站发送 logged MDT 日志可用指示。
示例性的, logged MDT 日志可用指示可以包含在 RRC连接态建立完 成消息中发送给基站。
208: 基站向 UE发送 UE信息需求消息。
209: UE 向基站发送包含 UE 的移动状态信息以及原始测量数据的 logged MDT 日志。
210: 基站保存 UE发送的包含 UE的移动状态信息以及原始测量数 据的 logged MDT 日志。
211 : 基站向网络管理设备发送包含 UE 的移动状态信息以及原始测 量数据的 logged MDT 日志。
212: 网络管理设备接收包含 UE 的移动状态信息以及原始测量数据 的 logged MDT 日志, 并根据原始测量数据获取位置测量数据。
上述示例仅表示一种利用 logged MDT获取 UE的移动状态信息以及 测量数据的一种方法, 当然也可以选用其他任何可以实现的方法, 本实施 例对此不进行限定。
102: 所述网络管理设备根据所述 UE的移动状态信息和所述 UE的 位置测量数据, 得到所述 UE的修正位置。 因为 UE获取原始测量数据时一般会受到噪声干扰, 根据原始测量数
据直接获取的位置测量数据进行定位存在一定误差, 因此需要根据 UE的 移动状态对位置测量数据进行处理以提高定位精度。 利用 UE的移动状态 对位置测量数据进行处理的定位方法有特征库匹配定位、根据到达角度定 位、 基于小区标识定位和利用卡尔曼滤波定位, 下面以卡尔曼滤波定位为 例进行具体详细的说明。 卡尔曼滤波是一种高效率的递归滤波器( 自回归滤波器), 它能够从 一组有限的、 对物体位置的、 包含噪声的观察序列预测出物体的坐标位置 及速度, 即只要获知上一时刻的最优估计值以及当前时刻的测量值就可以 计算出当前时刻的最优估计值, 因此不需要大量记录观测的历史信息。
卡尔曼滤波假设系统方程为:
X(k) = F-X(k-\) + - U(k) + W(k)
系统测量方程为:
z(k) = n-x(k)+v(k) 是 时刻系统状态, 是 时刻对系统的控制量, 2(^)是 时刻 的测量值; F, B, H是系统参数; W(k , W是系统噪声和测量噪声, 例 如, 对 UE的定位结果进行卡尔曼滤波时, W可以表示为运动的扰动方 差 2, W可以表示为坐标测量精度方差^?。 根据上一时刻的最优估计值以及当前时刻的测量值计算当前时刻的 最优估计值可以通过下述步骤实现:
1 ) 建立上一时刻最优估计值与当前时刻的预测值之间的方程: X(k\k-\) = F-X(k-\\k-\) + -U(k).
其中, ^-il^- 1)为上一时刻最优估计值, ^l 1)为当前时刻的预测 值:
2) 更新 的系统协方差 ρ ΐπ):
P(k\k-\) = F-P(k-\\k-\)-F'+Q .
3) 计算卡尔曼增益 (KalmanGain) :
Kg(k)= 聊- 'H'
n-P(k\k-\)-w+R .
5) 更新当前时刻最优化估计值 ^l 的协方差75^^), 其中 I为单位 阵:
P(k\k) = [l-Kg(k)-1i]-P(k\k-l) 在对 UE的定位结果进行卡尔曼滤波过程中, Q和 R的配置对于经卡 尔曼滤波后的定位结果的精度增益具有非常重要的作用, 根据 UE的移动 状态信息动态配置扰动方差 Q可以提高定位精度。
示例性的, 根据 UE的移动状态信息对 UE的位置测量数据进行卡尔 曼滤波, 得到 UE的修正位置坐标 (在此处, UE的修正位置坐标即为每 个时刻 UE位置的最优估计值, 根据上一时刻的最优估计值可以得到当前 时刻的最优估计值) , 可以包括:
( 1 ) 确定 UE 时刻至 时刻的系统方程及测量系统方程; 示例性的, 可以建立如下系统方程:
vy(k)
, 其中, 为 UE的预测位置坐标在 x方向上矢量分量、 为 UE的预测 位置坐标在 y方向上矢量分量, ^为 UE的速度在 X方向上的矢量分量、 为 UE的速度在 y方向上的矢量分量, t为系统方程更新时间间隔, a为 I 时刻 UE的加速度, ax为加速度 a在 X方向上的矢量分量、 ay为加速度 a 在 y方向上的矢量分量。 示例性的, 在这里加速度 a可以看作对系统的噪 声扰动量, 并且假设在 和 时刻之间, 该加速度 a保持不变, 即在 时 间内 UE的加速度 a恒定;
示例性的, 可以建立如下测量系统方程:
其中, 为 k时刻 UE的测量位置坐标在 x方向上的矢量分量、 为 k 时刻 UE的测量位置坐标在 y方向上的矢量分量, φ、为 k时刻的直接测量 误差, 测量位置坐标 (即位置测量数据) 通过 UE的原始测量数据获得。
( 2 ) 根据 UE在 时刻至 时刻的系统方程及 UE的移动状态信息 获取运动的扰动方差 Q; 例如, 根据步骤 ( 1 ) 中提供的 UE在 时刻至 时刻的系统方程可 以计算出 UE的运动的扰动方差 Q, 如下,
MDT测量的车载和步行的加速度 a变化范围在 0~6m/ 之间。 σ。可以根据
UE的移动状态信息设置。 例如, 根据地形地貌的不同, 加速度 a的标准差 σ。的可以进行如下配置: 当 UE的移动状态为高速移动(约 80kmph以上)时, σ。配置为 4~5m/ ; 当 UE的移动状态为中速移动(约 30km/h~80km/h之间, 例如 60km/h 左右) 时, σ。配置为 2~3m/ 当 UE的移动状态为一般移动(约 30kmph以下)时, σ。配置为 0~1 m/ 。
( 3 ) 至少 居所述 UE 在 -1时刻至 时刻的系统方程、 测量系统方 程及运动的扰动方差 Q得到所述 UE的修正位置坐标。
示例性的, 根据步骤 ( 1 ) 、 (2 ) 可以确定上述卡尔曼滤波步骤 1 ) - 步骤 5 ) 中的各个实际变量分别为:
其中, σ "为直接测量误差 η的标准差, 在实际工程中可以根据 UE运 动轨迹的曲率将其配置为一个固定的经验值。
将以上变量代入上述卡尔曼滤波的步骤 1 ) -步骤 5 ) 中可以得到 UE 的爹正位置坐标。 根据 UE的移动状态信息动态配置运动的扰动方差 Q可以提高定位精 度。
参见图 3 , 为 UE在不同移动状态信息下的卡尔曼滤波的仿真结果, 其中横轴为 σ。, 纵轴为修正位置坐标与测量位置坐标之间的误差, 其中, 测量位置坐标通过 UE的测量数据获得。 如图 3Α所示, 为 UE的移动速 度为 100km/h时获得的卡尔曼滤波的仿真结果, 此时 UE为高速移动, σ。 配置为 5m/ 左右时误差最小;如图 3B所示,为 UE的移动速度为 60km/h 时获得的卡尔曼滤波的仿真结果,此时 UE为中速移动, σ。配置为 2-3m/ 时误差最小; 如图 3C所示, 为 UE的移动速度为 10km/h时获得的卡尔曼 滤波的仿真结果, 此时 UE为一般移动, σ。配置为 0-lm/ 时误差最小。 由图 3可知, 根据 UE的移动状态信息确定的加速度标准差 。来动态 配置运动的扰动方差 Q , 可以使卡尔曼滤波的误差最小, 从而提高 UE的 定位精度。
本发明实施例提供用于定位的方法, 根据 UE的移动状态信息对 UE 的位置测量数据进行处理以提高定位精度,可以提高 MDT测量中所需 UE 的位置信息的精度, 降低了运营商网络优化的成本。 例如根据 UE的移动
状态信息来动态配置卡尔曼滤波参数, 提高了定位精度, 克服了现有技术 在在对测量数据进行卡尔曼滤波时 ,根据经验将运动的扰动方差 Q设定为 常数, 而不能使经卡尔曼滤波后的定位结果的精度增益最大, 甚至还会出 现负增益的缺陷。
参见图 4 , 为本发明实施例提供的另一种定位方法的示意图, 如图所 示, 可以包括以下步骤:
401 : 用户设备 UE获取所述 UE的移动状态信息;
402: 所述 UE向网络管理设备发送所述 UE的移动状态信息, 以使 得所述网络管理设备根据所述 UE的移动状态信息和所述网络管理设备获 取的所述 UE的位置测量数据得到所述 UE的修正位置;
其中, 所述 UE的移动状态信息用以指示所述 UE为高速移动、 中速 移动或一般移动。
示例性的, 在步骤 401之前, 该方法还可以包括: 接收所述网络管理 设备发送的指示信息, 所述指示信息用于指示所述 UE记录所述 UE的移 动状态信息。
本发明实施例提供的用于定位的方法, 通过向网络管理设备发送 UE 的移动状态信息, 使得网络管理设备根据 UE的移动状态信息对 UE的位 置测量数据进行处理以提高定位精度, 可以提高 MDT测量中所需 UE的 位置信息的定位精度从而降低了运营商网络优化的成本。 例如根据 UE的 移动状态信息来动态配置卡尔曼滤波参数, 提高了定位精度, 克服了现有 技术在在对测量数据进行卡尔曼滤波时,根据经验将运动的扰动方差 Q设 定为常数, 而不能使经卡尔曼滤波后的定位结果的精度增益最大, 甚至还 会出现负增益的缺陷。 本发明实施例进一步给出了实现上述方法实施例中各步骤及方法的 装置实施例, 本发明实施例可应用于各种通信系统中的基站或者 UE。
参见图 5 , 为本发明实施例提供的一种定位设备的结构图, 该定位设 备包括: 获取单元 501 , 处理单元 502 , 其中, 获取单元 501 , 用于获取用户设备 UE的移动状态信息以及所述 UE 的位置测量数据, 以及将所述 UE的移动状态信息和所述 UE的位置测量 数据传输给定位单元 502 , 其中, 所述 UE的移动状态信息用以指示所述
UE为高速移动、 中速移动或一般移动。
示例性的, 获取单元 501获取 UE的移动状态信息, 可以包括: 定位 设备向所述 UE发送指示信息, 所述指示信息用于指示所述 UE记录所述 UE的移动状态信息; 获取单元 501接收所述 UE的移动状态信息以及所 述 UE的测量数据。 定位设备可以设置在基站上, 也可以为独立的实体设 备, 本实施例以定位设备为独立的实体设备进行说明。
示例性的, 获取单元 501获取 UE的位置测量数据可以包括: 直接从 UE 获取, 例如, UE 记录该 UE 的原始测量数据, 该原始数据用于确定 UE的位置测量数据。在 UE记录该 UE的原始测量数据并可以根据该原始 测量数据获取位置测量数据, 并经由基站将该位置测量数据发送给网络管 理设备; 或者 UE的位置测量数据通过其他网络实体间接获取, 例如, UE 记录该 UE的原始测量数据, 并将该原始测量数据发送给基站, 使得基站 根据该原始测量数据获取位置测量数据, 并将该位置测量数据上报给网络 管理设备; 或者由该网络管理设备直接获取, 例如, UE记录该 UE 的原 始测量数据, 并将该原始测量数据经基站发送给网络管理设备, 网络管理 设备根据该原始测量数据获取位置测量数据。
进一步的, 参见图 6 , 所述获取单元 501可以包括:
发送模块 5011 , 用于向所述 UE发送指示信息, 所述指示信息用于指 示所述 UE记录所述 UE的移动状态信息; 示例性的,发送模块 5011可以具体用于,经由基站向 UE发送 logged MDT配置消息, 其中, logged MDT配置消息包括请求记录 UE的移动状 态信息的指示。
接收模块 5012 , 用于接收所述 UE发送的所述 UE的移动状态信息。 定位单元 502 , 用于从所述获取单元 501接收所述 UE的移动状态信 息和所述 UE的位置测量数据, 以及根据所述 UE的移动状态信息和所述 UE的位置测量数据得到所述 UE的修正位置。 因为 UE获取原始测量数据时一般会受到噪声干扰, 根据原始测量数 据直接获取的位置测量数据进行定位存在一定误差, 因此需要根据 UE的 移动状态对位置测量数据进行处理以提高定位精度。 利用 UE的移动状态 对位置测量数据进行处理的定位方法有特征库匹配定位、根据到达角度定
位、 基于小区标识定位和利用卡尔曼滤波定位, 下面以卡尔曼滤波定位为 例进行具体详细的说明。 卡尔曼滤波是一种高效率的递归滤波器( 自回归滤波器), 它能够从 一组有限的、 对物体位置的、 包含噪声的观察序列预测出物体的坐标位置 及速度, 即只要获知上一时刻的最优估计值以及当前时刻的测量值就可以 计算出当前时刻的最优估计值, 因此不需要大量记录观测的历史信息。
卡尔曼滤波假设系统方程为:
X(k) = F-X(k-\) + - U(k) + W(k)
系统测量方程为:
z(k) = n-x(k)+v(k) 是 时刻系统状态, 是 时刻对系统的控制量, 2(^)是 时刻 的测量值; F, B, H是系统参数; W(k , W是系统噪声和测量噪声, 例 如, 对 UE的定位结果进行卡尔曼滤波时, W可以表示为运动的扰动方 差 2, W可以表示为坐标测量精度方差^?。 则根据上一时刻的最优估计值以及当前时刻的测量值计算当前时刻 的最优估计值可以通过下述步骤实现:
1 ) 建立上一时刻最优估计值与当前时刻的预测值之间的方程: X(k\k-\) = F-X(k-\\k-\) + -U(k).
其中, ^-il^- 1)为上一时刻最优估计值, ^l 1)为当前时刻的预测 值:
2) 更新 的系统协方差 ρ ΐπ):
P(k\k-\) = F-P(k-\\k-\)-F'+Q .
3 ) 计算卡尔曼增益 (KalmanGain) :
Kg(k)= 聊- 'H'
n-P(k\k-\)-w+R .
4) 计算当前时刻的最优化估计值^^
X(k\k) = X(k\k-l) + Kg(k)-[Z(k)-1i-X(k\k-l)].
5) 更新当前时刻最优化估计值 ^l 的协方差75^^), 其中 I为单位 阵:
P(k\k) = [l-Kg(k)-1i]-P(k\k-\) 在对 UE的定位结果进行卡尔曼滤波过程中, Q和 R的配置对于经卡 尔曼滤波后的定位结果的精度增益具有非常重要的作用, 根据 UE的移动 状态信息动态配置扰动方差 Q可以提高定位精度。
示例性的, 定位单元 502根据 UE的移动状态信息对 UE的位置测量 数据进行卡尔曼滤波, 得到 UE 的修正位置坐标 (在此处, UE的修正位 置坐标即为每个时刻 UE位置的最优估计值, 根据上一时刻的最优估计值 可以得到当前时刻的最优估计值) 。
进一步地, 参见图 6, 定位单元 502可以包括:
确定模块 5021: 用于确定 UE k-l时刻至 k时刻的系统方程及测量系 统方程;
示例性的, 可以建立如下系统方程:
vy(k)
, 其中, 为 UE的预测位置坐标在 x方向上矢量分量、 为 UE的预测 位置坐标在 y方向上矢量分量, ^为 UE的速度在 X方向上的矢量分量、 为 UE的速度在 y方向上的矢量分量, t为系统方程更新时间间隔, a为 I 时刻 UE的加速度, ax为加速度 a在 X方向上的矢量分量、 ay为加速度 a 在 y方向上的矢量分量。 示例性的, 在这里加速度 a可以看作对系统的噪 声扰动量, 并且假设在 和 时刻之间, 该加速度 a保持不变, 即在 时 间内 UE的加速度 a恒定;
示例性的, 可以建立如下测量系统方程:
其中, 为 k时刻 UE的测量位置坐标在 X方向上的矢量分量、 为 k
时刻 UE的测量位置坐标在 y方向上的矢量分量 , n(J()为 k时刻的直接测量 误差, 测量位置坐标 (即位置测量数据) 通过 UE的原始测量数据获得。 第一获取模块 5022 : 用于根据 UE在 时刻至 时刻的系统方程及 UE的移动状态信息获取运动的扰动方差 Q ;
例如, 根据根据确定模块 5021提供的 UE在 -1时刻至 时刻的系统 方程可以计算出 UE的运动的扰动方差 Q , 如下,
UE的移动状态信息设置。 例如, 根据地形地貌的不同, 加速度 a的标准差 σ。的可以进行如下配置: 当 UE的移动状态为高速移动(约 80kmph以上)时, σ。配置为 4~5m/ ; 当 UE的移动状态为中速移动(约 30km/h~80km/h之间, 例如 60km/h 左右) 时, σ。配置为 2~3m/ y2 ; 当 UE的移动状态为一般移动(约 30km/h以下)时, σ。配置为 0~ l m/ 。 第二获取模块 5023:用于至少根据所述 UE在 -1时刻至 时刻的系统 方程、 测量系统方程及运动的扰动方差 Q得到所述 UE的修正位置坐标。
示例性的, 根据确定模块 5021、 第一获取模块 5022可以确定上述卡 尔曼滤波步骤 1 ) -步骤 5 ) 中的各个实际变量分别为:
其中, σ "为直接测量误差 η的标准差, 在实际工程中可以根据 UE运 动轨迹的曲率将其配置为一个固定的经验值。
将以上变量代入上述卡尔曼滤波的步骤 1 ) -步骤 5 ) 中可以得到 UE 的爹正位置坐标。 根据 UE的移动状态信息动态配置运动的扰动方差 Q可以提高定位精 度。
参见图 3 , 为 UE在不同移动状态下的卡尔曼滤波的仿真结果, 其中 横轴为 σ。, 纵轴为修正位置坐标与测量位置坐标之间的误差, 其中, 测量 位置坐标通过 UE的测量数据获得。 如图 3Α所示, 为 UE的移动速度为 100km/h时获得的卡尔曼滤波的仿真结果, 此时 UE为高速移动, σ。配置 为 5m/ 左右时误差最小; 如图 3B所示, 为 UE的移动速度为 60km/h时 获得的卡尔曼滤波的仿真结果,此时 UE为中速移动, σ。配置为 2-3m/ 时 误差最小; 如图 3C所示, 为 UE的移动速度为 10km/h时获得的卡尔曼滤 波的仿真结果, 此时 UE为一般移动, σ。配置为 0-lm/ 时误差最小。 由图 3可知, 根据 UE的移动状态确定的加速度标准差 σ。来动态配置 运动的扰动方差 Q , 可以使卡尔曼滤波的误差最小, 从而提高 UE的定位 精度。
本发明实施例提供的定位设备, 根据 UE的移动状态信息对 UE的测 量数据进行处理以提高定位精度, 使得 MDT测量中所需 UE的位置信息 更加精确, 降低了运营商网络规划的成本。 例如在卡尔曼滤波中, 网络管
理设备根据 UE的移动状态信息配置运动的扰动方差 Q并对 UE的测量数 据进行卡尔曼滤波, 进而使得基于卡尔曼滤波技术的 UE定位精度增益最 大化。 克服了现有技术中根据卡尔曼滤波时, 根据经验将运动的扰动方差 Q设定为常数, 而不能使经卡尔曼滤波后的定位结果的精度增益最大, 甚 至还会出现负增益的缺陷。 在硬件实现上, 以上发送模块可以为发射机或收发机, 以上接收模 块可以为接收机或收发机, 且该发送模块和接收模块可以集成在一起构 成收发单元, 对应于硬件实现为收发机; 以上获取单元和定位单元可以 以硬件形式内嵌于或独立于定位设备的处理器中, 也可以以软件形式存 储于定位设备的存储器中, 以便于处理器调用执行以上各个模块对应的 操作, 该处理器可以为中央处理单元 (CPU )、 微处理器、 单片机等。 参考图 7 , 为本发明实施例提供的一种定位设备的结构示意图, 如图 7所示, 该定位设备包括: 发射机 701、 接收机 702、 存储器 703 以及分 别与发射机 701、 接收机 702和存储器 703连接的处理器 704。 当然, 定 位设备还可以包括输入输出装置等通用部件, 本发明实施例在此不再任 何限制。
其中, 存储器 703 中存储一组程序代码, 处理器 704用于调用存储器
703中的程序代码, 用于执行以下操作: 获取用户设备 UE的移动状态信息以及所述 UE的位置测量数据, 其 中, 所述 UE的移动状态信息用以指示所述 UE为高速移动、 中速移动或 一般移动; 根据所述 UE的移动状态信息和所述 UE的位置测量数据得到 所述 UE的修正位置。
发射机 701用于向所述 UE发送指示信息, 所述指示信息用于指示所 述 UE记录所述 UE的移动状态信息; 示例性的, 发射机 701 可以具体用于, 经由基站向 UE发送 logged MDT配置消息, 其中, logged MDT配置消息包括请求记录 UE的移动状 态信息的指示。
接收机 702 , 用于接收所述 UE发送的所述 UE的移动状态信息。 示例性的, 获取 UE 的移动状态信息, 可以包括: 定位设备向所述
UE发送指示信息,所述指示信息用于指示所述 UE记录所述 UE的移动状 态信息; 获取单元 501接收所述 UE的移动状态信息以及所述 UE的测量 数据。 定位设备可以设置在基站上, 也可以为独立的实体设备, 本实施例 以定位设备为独立的实体设备进行说明。
示例性的, 获取 UE的位置测量数据可以包括: 直接从 UE获取, 例 如, UE记录该 UE的原始测量数据, 该原始数据用于确定 UE的位置测量 数据。 在 UE记录该 UE的原始测量数据并可以根据该原始测量数据获取 位置测量数据, 并经由基站将该位置测量数据发送给网络管理设备; 或者 UE的位置测量数据通过其他网络实体间接获取, 例如, UE记录该 UE的 原始测量数据, 并将该原始测量数据发送给基站, 使得基站根据该原始测 量数据获取位置测量数据, 并将该位置测量数据上报给网络管理设备; 或 者由该网络管理设备直接获取, 例如, UE记录该 UE 的原始测量数据, 并将该原始测量数据经基站发送给网络管理设备, 网络管理设备根据该原 始测量数据获取位置测量数据。
因为 UE获取原始测量数据时一般会受到噪声干扰, 根据原始测量数 据直接获取的位置测量数据进行定位存在一定误差, 因此需要根据 UE的 移动状态对位置测量数据进行处理以提高定位精度。 利用 UE的移动状态 对位置测量数据进行处理的定位方法有特征库匹配定位、根据到达角度定 位、 基于小区标识定位和利用卡尔曼滤波定位, 下面以卡尔曼滤波定位为 例进行具体详细的说明。 卡尔曼滤波是一种高效率的递归滤波器( 自回归滤波器), 它能够从 一组有限的、 对物体位置的、 包含噪声的观察序列预测出物体的坐标位置 及速度, 即只要获知上一时刻的最优估计值以及当前时刻的测量值就可以 计算出当前时刻的最优估计值, 因此不需要大量记录观测的历史信息。
卡尔曼滤波假设系统方程为:
X(k) = F - X(k - \) + - U(k) + W(k)
系统测量方程为:
z(k) = n- x(k)+v(k) 是 时刻系统状态, 是 时刻对系统的控制量, 2(^)是 时刻 的测量值; F , B , H是系统参数; , W是系统噪声和测量噪声, 例
如, 对 UE的定位结果进行卡尔曼滤波时, W可以表示为运动的扰动方 差 2, W可以表示为坐标测量精度方差^?。 则根据上一时刻的最优估计值以及当前时刻的测量值计算当前时刻 的最优估计值可以通过下述步骤实现:
1 ) 建立上一时刻最优估计值与当前时刻的预测值之间的方程: X(k\k-\) = F-X(k-\\k-\) + -U(k).
其中, ^-il^- 1)为上一时刻最优估计值, ^l 1)为当前时刻的预测 值:
2) 更新 的系统协方差 ρ ΐπ):
P(k\k-\) = F-P(k-\\k-\)-F'+Q .
3) 计算卡尔曼增益 (KalmanGain) :
Kg(k)= 聊- 'H'
n-P(k\k-\)-w+R .
4) 计算当前时刻的最优化估计值^^
X(k\k) = X(k\k-l) + Kg(k)-[Z(k)-1i-X(k\k-l)].
5 ) 更新当前时刻最优化估计值 ^l 的协方差75^^), 其中 I为单位 阵:
P(k\k) = [l-Kg(k)-1i]-P(k\k-l) 在对 UE的定位结果进行卡尔曼滤波过程中, Q和 R的配置对于经卡 尔曼滤波后的定位结果的精度增益具有非常重要的作用, 根据 UE的移动 状态信息动态配置扰动方差 Q可以提高定位精度。
示例性的, 根据 UE的移动状态信息对 UE的位置测量数据进行卡尔 曼滤波, 得到 UE的修正位置坐标 (在此处, UE的修正位置坐标即为每 个时刻 UE位置的最优估计值, 根据上一时刻的最优估计值可以得到当前 时刻的最优估计值) , 可以包括:
( 1 ) 确定 UE 时刻至 时刻的系统方程及测量系统方程; 示例性的, 可以建立如下系统方程:
其中, 为 UE的预测位置坐标在 x方向上矢量分量、 为 UE的预测 位置坐标在 y方向上矢量分量, ^为 UE的速度在 X方向上的矢量分量、 为 UE的速度在 y方向上的矢量分量, t为系统方程更新时间间隔, a为 I 时刻 UE的加速度, ax为加速度 a在 X方向上的矢量分量、 ay为加速度 a 在 y方向上的矢量分量。 示例性的, 在这里加速度 a可以看作对系统的噪 声扰动量, 并且假设在 和 时刻之间, 该加速度 a保持不变, 即在 时 间内 UE的加速度 a恒定;
示例性的, 可以建立如下测量系统方程:
其中, 为 k时刻 UE的测量位置坐标在 x方向上的矢量分量、 为 k 时刻 UE的测量位置坐标在 y方向上的矢量分量, φ、为 k时刻的直接测量 误差, 测量位置坐标 (即位置测量数据) 通过 UE的原始测量数据获得。
( 2 ) 根据 UE在 时刻至 时刻的系统方程及 UE的移动状态信息 获取运动的扰动方差 Q; 例如, 根据步骤 ( 1 ) 中提供的 UE在 时刻至 时刻的系统方程可 以计算出 UE的运动的扰动方差 Q, 如下,
MDT测量的车载和步行的加速度 a变化范围在 0~6m/ 之间。 σ。可以根据
UE的移动状态信息设置。 例如, 根据地形地貌的不同, 加速度 a的标准差 σ。的可以进行如下配置: 当 UE的移动状态为高速移动(约 80kmph以上)时, σ。配置为 4~5m/ ; 当 UE的移动状态为中速移动(约 30km/h~80km/h之间, 例如 60km/h 左右) 时, σ。配置为 2~3m/ ; 当 UE的移动状态为一般移动(约 30kmph以下)时, σ。配置为 0~1 m/ 。
(3) 至少 居所述 UE 在 -1时刻至 时刻的系统方程、 测量系统方 程及运动的扰动方差 Q得到所述 UE的修正位置坐标。
示例性的, 根据步骤 ( 1) 、 (2) 可以确定上述卡尔曼滤波步骤 1 ) - 步骤 5) 中的各个实际变量分别为:
— 1 0 t 0—
sAk), s ~y(k) 0 1 0 t
X(k) = Z(k) = F =
0 0 1 0 1 0 0 0
H =
vy(k) 0 0 0 1 0 1 0 0
R
将以上变量代入上述卡尔曼滤波的步骤 1) -步骤 5) 中可以得到 UE 的爹正位置坐标。
根据 UE的移动状态信息动态配置运动的扰动方差 Q可以提高定位精 度。
参见图 3 , 为 UE在不同移动状态下的卡尔曼滤波的仿真结果, 其中 横轴为 σ。, 纵轴为修正位置坐标与测量位置坐标之间的误差, 其中, 测量 位置坐标通过 UE的测量数据获得。 如图 3Α所示, 为 UE的移动速度为 100km/h时获得的卡尔曼滤波的仿真结果, 此时 UE为高速移动, σ。配置 为 5m/ 左右时误差最小; 如图 3B所示, 为 UE的移动速度为 60km/h时 获得的卡尔曼滤波的仿真结果,此时 UE为中速移动, σ。配置为 2-3m/ 时 误差最小; 如图 3C所示, 为 UE的移动速度为 10km/h时获得的卡尔曼滤 波的仿真结果, 此时 UE为一般移动, σ。配置为 0-lm/ 时误差最小。 由图 3可知, 根据 UE的移动状态确定的加速度标准差 σ。来动态配置 运动的扰动方差 Q , 可以使卡尔曼滤波的误差最小, 从而提高 UE的定位 精度。
需要说明的是,图 5-图 7所示的定位设备可以实现以上方法实施例所 提供的任一种方法。 本发明提供的定位设备, 根据 UE的移动状态信息对 UE的测量数据 进行处理以提高定位精度, 使得 MDT测量中所需 UE的位置信息更加精 确, 从而降低了运营商网络优化的成本。 例如在卡尔曼滤波中, 网络管理 设备根据 UE的移动状态信息配置运动的扰动方差 Q并对 UE的测量数据 进行卡尔曼滤波, 进而使得基于直接测量数据和卡尔曼滤波技术的 UE定 位精度增益最大化。 克服了现有技术中根据卡尔曼滤波时, 根据经验将运 动的扰动方差 Q设定为常数,而不能使经卡尔曼滤波后的定位结果的精度 增益最大, 甚至还会出现负增益的缺陷。
参见图 8 , 为本发明实施例提供的一种用户设备 UE的结构示意图, 该 UE用于实现图 4所示的定位方法, 该用户设备 UE包括:
获取单元 801 , 用于获取所述 UE的移动状态信息;
发送单元 802 , 用于向网络管理设备发送所述 UE的移动状态信息, 以使得所述网络管理设备根据所述 UE的移动状态信息和所述网络管理设 备获取的所述 UE的位置测量数据得到所述 UE的修正位置坐标;
其中, 所述 UE的移动状态信息用以指示所述 UE为高速移动、 中速 移动或一般移动。
进一步地, 该 UE还可以包括: 接收单元 803 , 用于接收所述网络管理设备发送的指示信息, 所述指 示信息用于指示所述 UE记录所述 UE的移动状态信息。 本发明实施例提供的用户设备 UE, 通过向网络管理设备发送 UE的 移动状态信息以及所述 UE的测量数据, 以使得网络管理设备根据 UE的 移动状态信息对 UE的测量数据进行处理以提高定位精度, 使得 MDT测 量中所需 UE的位置信息更加精确, 从而降低了运营商网络优化的成本。 例如在卡尔曼滤波中, 网络管理设备根据 UE的移动状态信息配置运动的 扰动方差 Q并对 UE的测量数据进行卡尔曼滤波, 进而使得基于直接测量 数据和卡尔曼滤波技术的 UE定位精度增益最大化。 克服了现有技术中根 据卡尔曼滤波时, 根据经验将运动的扰动方差 Q设定为常数, 而不能使经 卡尔曼滤波后的定位结果的精度增益最大, 甚至还会出现负增益的缺陷。
在硬件实现上, 以上发送单元可以为发送器, 以上接收单元可以为接 收器, 且该发送器和接收器可以集成在一起构成收发器; 以上获取单元可 以以硬件形式内嵌于或独立于用户设备 UE 的处理器中, 也可以以软件 形式存储于用户设备 UE 的存储器中, 以便于处理器调用执行以上各个 模块对应的操作, 该处理器可以为中央处理单元 (CPU )、 微处理器、 单 片机等。
参考图 9 , 为本发明实施例提供的一种用户设备 UE的结构示意图, 如图所示, 该用户设备 UE 包括: 发送器 901、 接收器 902、 存储器 903 以及分别与发送器 901、 接收器 902和存储器 903连接的处理器 904。 当 然, 用户设备 UE还可以包括输入输出装置等通用部件, 本发明实施例在 此不再任何限制。 其中, 存储器 903 中存储一组程序代码, 处理器 904用于调用存储器
903中的程序代码, 用于执行以下操作: 获取所述 UE的移动状态信息;
发送器 901 , 用于向网络管理设备发送所述 UE的移动状态信息, 以 使得所述网络管理设备根据所述 UE的移动状态信息和所述网络管理设备 获取的所述 UE的位置测量数据得到所述 UE的修正位置坐标;
其中, 所述 UE的移动状态信息用以指示所述 UE为高速移动、 中速 移动或一般移动。
接收器 902 , 用于接收所述网络管理设备发送的指示信息, 所述指示 信息用于指示所述 UE记录所述 UE的移动状态信息。 本发明实施例提供的用户设备 UE, 通过向网络管理设备发送 UE的 移动状态信息以及所述 UE的测量数据, 以使得网络管理设备根据 UE的 移动状态信息对 UE的测量数据进行处理以提高定位精度, 使得 MDT测 量中所需 UE的位置信息更加精确, 从而降低了运营商网络优化的成本。 例如在卡尔曼滤波中, 网络管理设备根据 UE的移动状态信息配置运动的 扰动方差 Q并对 UE的测量数据进行卡尔曼滤波, 进而使得基于直接测量 数据和卡尔曼滤波技术的 UE定位精度增益最大化。 克服了现有技术中根 据卡尔曼滤波时, 根据经验将运动的扰动方差 Q设定为常数, 而不能使经 卡尔曼滤波后的定位结果的精度增益最大, 甚至还会出现负增益的缺陷。
本发明实施例提供一种定位的系统, 参见图 10 , 包括: 定位设备和 用户设备 UE, 其中,
定位设备, 用于获取用户设备 UE的移动状态信息以及所述 UE的位 置测量数据, 其中, 所述 UE的移动状态信息用以指示所述 UE为高速移 动、 中速移动或一般移动; 所述网络管理设备根据所述 UE的移动状态信 息和所述 UE的位置测量数据, 得到所述 UE的修正位置。
用户设备 UE , 用于向网络管理设备发送 UE的移动状态信息。
进一步的, 所述定位系统还可以包括: 基站, 用于接收所述网络管理设备发送的指示信息, 所述指示信息用 于指示所述 UE记录所述 UE的移动状态信息, 以及转发所述 UE发送的 所述 UE的移动状态信息。
示例性的, 获取用户设备 UE的移动状态信息以及所述 UE的位置测 量数据的过程可以参见上述实施例, 此处不再赘述。
因为 UE获取原始测量数据时一般会受到噪声干扰, 根据原始测量数 据直接获取的位置测量数据进行定位存在一定误差, 因此需要根据 UE的 移动状态对位置测量数据进行处理以提高定位精度。 利用 UE的移动状态 对位置测量数据进行处理的定位方法有特征库匹配定位、根据到达角度定
位、 基于小区标识定位和利用卡尔曼滤波定位。 通常对 UE定位结果应用 卡尔曼滤波, 以减小噪声的影响, 提高定位精度。
根据 UE的移动状态信息配置运动的扰动方差 Q并对 UE的测量数据 进行卡尔曼滤波的具体过程同方法实施例, 此处不再赘述。
本发明实施例提供的定位系统, 根据 UE的移动状态信息对 UE的测 量数据进行处理以提高定位精度, 使得 MDT测量中所需 UE的位置信息 更加精确, 从而降低了运营商网络优化的成本。 例如在卡尔曼滤波中, 网 络管理设备根据 UE的移动状态信息配置运动的扰动方差 Q并对 UE的测 量数据进行卡尔曼滤波, 进而使得基于直接测量数据和卡尔曼滤波技术的 UE 定位精度增益最大化。 克服了现有技术中根据卡尔曼滤波时, 根据经 验将运动的扰动方差 Q设定为常数,而不能使经卡尔曼滤波后的定位结果 的精度增益最大, 甚至还会出现负增益的缺陷。
本领域普通技术人员可以理解: 实现上述方法实施例的全部或部分 步骤可以通过程序指令相关的硬件来完成, 前述的程序可以存储于一计 算机可读取存储介质中, 该程序在执行时, 执行包括上述方法实施例的 步骤; 而前述的存储介质包括: ROM、 RAM, 磁碟或者光盘等各种可以 存储程序代码的介质。
以上所述, 仅为本发明的具体实施方式, 但本发明的保护范围并不 局限于此, 任何熟悉本技术领域的技术人员在本发明揭露的技术范围内, 可轻易想到变化或替换, 都应涵盖在本发明的保护范围之内。 因此, 本 发明的保护范围应以所述权利要求的保护范围为准。
Claims
1、 一种定位的方法, 其特征在于, 包括:
网络管理设备获取用户设备 UE的移动状态信息以及所述 UE的位置 测量数据,其中,所述 UE的移动状态信息用以指示所述 UE为高速移动、 中速移动或一般移动;所述网络管理设备根据所述 UE的移动状态信息和 所述 UE的位置测量数据, 得到所述 UE的修正位置。
2、 根据权利要求 1所述的定位的方法, 其特征在于, 所述网络管理 设备获取所述 UE的移动状态信息, 包括:
所述网络管理设备向所述 UE发送指示信息, 所述指示信息用于指 示所述 UE记录所述 UE的移动状态信息;
所述网络管理设备接收所述 UE发送的所述 UE的移动状态信息。
3、 一种定位的方法, 其特征在于, 包括:
用户设备 UE获取所述 UE的移动状态信息;
所述 UE向网络管理设备发送所述 UE的移动状态信息,以使得所述 网络管理设备根据所述 UE 的移动状态信息和所述网络管理设备获取的 所述 UE的位置测量数据得到所述 UE的修正位置;
其中, 所述 UE的移动状态信息用以指示所述 UE为高速移动、 中速 移动或一般移动。
4、 根据权利要求 3所述的定位的方法, 其特征在于, 所述用户设备 UE获取所述 UE的移动状态信息之前, 所述方法还包括:
所述 UE接收所述网络管理设备发送的指示信息, 所述指示信息用 于指示所述 UE记录所述 UE的移动状态信息。
5、 一种定位设备, 其特征在于, 包括:
获取单元,用于获取用户设备 UE的移动状态信息以及所述 UE的位 置测量数据, 以及将所述 UE的移动状态信息和所述 UE的位置测量数据 传输给定位单元, 其中, 所述 UE的移动状态信息用以指示所述 UE为高 速移动、 中速移动或一般移动;
定位单元, 用于从所述获取单元接收所述 UE 的移动状态信息和所 述 UE的测量数据, 以及根据所述 UE的移动状态信息和所述 UE的位置 测量数据得到所述 UE的修正位置。
6、 根据权利要求 5所述的定位设备, 其特征在于, 所述获取单元, 包括:
发送模块, 用于向所述 UE 发送指示信息, 所述指示信息用于指示 所述 UE记录所述 UE的移动状态信息;
接收模块, 用于接收所述 UE发送的所述 UE的移动状态信息。
7、 一种用户设备 UE, 其特征在于, 包括:
获取单元, 用于获取所述 UE的移动状态信息;
发送单元, 用于向网络管理设备发送所述 UE 的移动状态信息, 以 使得所述网络管理设备根据所述 UE 的移动状态信息和所述网络管理设 备获取的所述 UE的位置测量数据得到所述 UE的修正位置坐标;
其中, 所述 UE的移动状态信息用以指示所述 UE为高速移动、 中速 移动或一般移动。
8、 根据权利要求 7所述的用户设备 UE, 其特征在于, 所述 UE还 包括:
接收单元, 用于接收所述网络管理设备发送的指示信息, 所述指示 信息用于指示所述 UE记录所述 UE的移动状态信息。
9、 一种定位系统, 其特征在于, 包括: 权利要求 5或 6所述的定位 设备以及权利要求 7或 8所述的用户设备 UE。
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