CN111381209A - Distance measurement positioning method and device - Google Patents
Distance measurement positioning method and device Download PDFInfo
- Publication number
- CN111381209A CN111381209A CN201811636477.3A CN201811636477A CN111381209A CN 111381209 A CN111381209 A CN 111381209A CN 201811636477 A CN201811636477 A CN 201811636477A CN 111381209 A CN111381209 A CN 111381209A
- Authority
- CN
- China
- Prior art keywords
- value
- positioning
- data
- coordinate
- iteration
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 76
- 238000005259 measurement Methods 0.000 title description 4
- 238000013178 mathematical model Methods 0.000 claims abstract description 40
- 238000004364 calculation method Methods 0.000 claims abstract description 17
- 238000012545 processing Methods 0.000 claims abstract description 10
- 230000009466 transformation Effects 0.000 claims abstract description 9
- 238000004590 computer program Methods 0.000 claims description 19
- 238000007781 pre-processing Methods 0.000 claims description 10
- 238000001914 filtration Methods 0.000 claims description 9
- 239000011159 matrix material Substances 0.000 claims description 8
- 230000001131 transforming effect Effects 0.000 claims 1
- 238000004422 calculation algorithm Methods 0.000 abstract description 11
- 238000005516 engineering process Methods 0.000 description 12
- 230000008569 process Effects 0.000 description 11
- 230000006870 function Effects 0.000 description 8
- 230000005540 biological transmission Effects 0.000 description 7
- 238000004891 communication Methods 0.000 description 7
- 238000010586 diagram Methods 0.000 description 7
- 230000004044 response Effects 0.000 description 4
- 239000007787 solid Substances 0.000 description 4
- 229910000831 Steel Inorganic materials 0.000 description 3
- 230000008878 coupling Effects 0.000 description 3
- 238000010168 coupling process Methods 0.000 description 3
- 238000005859 coupling reaction Methods 0.000 description 3
- 239000010959 steel Substances 0.000 description 3
- 238000001514 detection method Methods 0.000 description 2
- 230000006872 improvement Effects 0.000 description 2
- 238000012935 Averaging Methods 0.000 description 1
- 230000002238 attenuated effect Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 239000011521 glass Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 230000035515 penetration Effects 0.000 description 1
- 230000000737 periodic effect Effects 0.000 description 1
- 230000005855 radiation Effects 0.000 description 1
- 230000008054 signal transmission Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 230000001360 synchronised effect Effects 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
- 239000002023 wood Substances 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
- G01S5/02—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using radio waves
- G01S5/10—Position of receiver fixed by co-ordinating a plurality of position lines defined by path-difference measurements, e.g. omega or decca systems
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
- G01S5/0009—Transmission of position information to remote stations
- G01S5/0045—Transmission from base station to mobile station
- G01S5/0054—Transmission from base station to mobile station of actual mobile position, i.e. position calculation on base station
Landscapes
- Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Radar Systems Or Details Thereof (AREA)
Abstract
The invention is suitable for the technical field of wireless positioning, and provides a distance measuring and positioning method and a distance measuring and positioning device, wherein the distance measuring and positioning method comprises the following steps: obtaining a set of distance data between the tag and each of at least three base stations; establishing a corresponding three-dimensional coordinate mathematical model according to the three-dimensional coordinate data of each base station and the corresponding preprocessed group of distance data so as to generate a corresponding number of three-dimensional coordinate mathematical models according to the number of the base stations; performing linear transformation of a nonlinear equation set on the generated three-dimensional coordinate mathematical models; and iteratively calculating the three-dimensional positioning value and the iteration error value of the label according to the linear equation set and a preset iteration initial value, wherein the preset iteration initial value is the initial coordinate value of the label. Compared with the traditional positioning calculation mode, the method has higher positioning precision by processing the distance data and optimizing the distance algorithm.
Description
Technical Field
The invention belongs to the technical field of wireless positioning, and particularly relates to a distance measuring and positioning method and device, terminal equipment and a computer readable storage medium.
Background
Ultra Wide Band (UWB) is a wireless communication technology for transmitting data at a high speed in a short distance with extremely low power, and UWB has many advantages such as strong anti-interference performance, high transmission rate, extremely wide bandwidth, low power consumption, and low transmission power, and is mainly applied to the fields of indoor communication, home networks, position determination, radar detection, and the like. The system has large capacity and very small transmission power, and the influence of electromagnetic wave radiation on human bodies is very small, so that the application range is wide.
In recent years, sub-nanosecond ultra-narrow pulses are mostly used for close-range accurate indoor positioning. The impulse has high positioning precision, and the positioning and communication are easily integrated by adopting ultra-wideband radio communication, which is difficult to realize by the conventional radio. Ultra-wideband radio has extremely strong penetration capability, can perform accurate positioning indoors and underground, and a GPS positioning system can only work within the visual range of a GPS positioning satellite. Unlike GPS which provides absolute geographic position, the ultra-short pulse locator can give relative position, and the locating precision can reach centimeter level. Most of the traditional ultra-wideband positioning technologies calculate the positioning value of the label by an RSS method, an AOA method and a TOA/TDOA method, but the positioning algorithm and data processing aspects of the methods have certain defects, so that the positioning accuracy is poor.
Disclosure of Invention
In view of this, embodiments of the present invention provide a method and an apparatus for ranging and positioning to solve the technical problem of poor positioning accuracy in the prior art.
A first aspect of an embodiment of the present invention provides a method for ranging and positioning, including:
obtaining a set of distance data between the tag and each of at least three base stations;
establishing a corresponding three-dimensional coordinate mathematical model according to the three-dimensional coordinate data of each base station and the corresponding preprocessed group of distance data so as to generate a corresponding number of three-dimensional coordinate mathematical models according to the number of the base stations;
performing linear transformation of a nonlinear equation set on the generated three-dimensional coordinate mathematical models;
and iteratively calculating the three-dimensional positioning value and the iteration error value of the label according to the linear equation set and a preset iteration initial value, wherein the preset iteration initial value is the initial coordinate value of the label.
A second aspect of the embodiments of the present invention provides a distance measuring and positioning apparatus, including:
an obtaining unit, configured to obtain a set of distance data between the tag and each of at least three base stations;
the calculation unit is used for establishing a corresponding three-dimensional coordinate mathematical model according to the three-dimensional coordinate data of each base station and the corresponding preprocessed group of distance data so as to generate a corresponding number of three-dimensional coordinate mathematical models according to the number of the base stations; performing linear transformation of a nonlinear equation set on the generated three-dimensional coordinate mathematical models; and iteratively calculating the three-dimensional positioning value and the iteration error value of the label according to the linear equation set and a preset iteration initial value, wherein the preset iteration initial value is the initial coordinate value of the label.
A third aspect of the embodiments of the present invention provides a terminal device for ranging and positioning, including: a memory, a processor and a computer program stored in the memory and executable on the processor, the processor implementing the steps of the method of the first and/or second aspect when executing the computer program.
A fourth aspect of embodiments of the present invention provides a computer-readable storage medium, which stores a computer program that, when executed by a processor, implements the steps of the method of the first and/or second aspect.
Compared with the prior art, the embodiment of the invention has the following beneficial effects: the invention accurately processes the distance data of the label and each base station, establishes a mathematical model through the distance data, calculates the three-dimensional positioning data of the label, and optimizes the selection of the iteration result, and has the advantages of higher precision and the like compared with the traditional RSS method, AOA method and TOA/TDOA method.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the embodiments or the prior art descriptions will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise.
Fig. 1 is a flowchart of a method for ranging and positioning according to an embodiment of the present invention;
fig. 2 is a schematic flowchart of another implementation process before step S101 in a method for ranging and positioning according to an embodiment of the present invention;
fig. 3 is a schematic flowchart of another implementation after step S101 in a method for ranging and positioning according to an embodiment of the present invention;
fig. 4 is a schematic diagram of a specific implementation flow of S103 in a method for ranging and positioning according to an embodiment of the present invention;
FIG. 5 is a schematic diagram of a specific flow chart of a Gauss-Newton iterative algorithm provided by an embodiment of the present invention;
fig. 6 is a schematic flowchart of another implementation after step S104 in a method for ranging and positioning according to an embodiment of the present invention;
FIG. 7 is a schematic diagram of a device for ranging and positioning according to an embodiment of the present invention;
fig. 8 is a schematic diagram of a terminal device for ranging and positioning according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It will be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
It is also to be understood that the terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in the specification of the present invention and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
It should be further understood that the term "and/or" as used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.
As used in this specification and the appended claims, the term "if" may be interpreted contextually as "when", "upon" or "in response to a determination" or "in response to a detection". Similarly, the phrase "if it is determined" or "if a [ described condition or event ] is detected" may be interpreted contextually to mean "upon determining" or "in response to determining" or "upon detecting [ described condition or event ]" or "in response to detecting [ described condition or event ]".
With the advancement of science and technology, emerging wireless network technologies, such as WiFi, WiMax, ZigBee, Adhoc, BlueTooth and ultrawide band (uwb), are widely applied in the aspects of mass life such as offices, homes, factories, parks, and the like, and the application of the positioning technology based on the wireless network has a wider development. The ultra-wideband (UWB) positioning technology is a hotspot and a first choice of the future wireless positioning technology due to the advantages of low power consumption, good anti-multipath effect, high security, low system complexity, and especially the capability of providing very accurate positioning accuracy. The most common ultra-wideband positioning technology at present mainly comprises the following steps: time difference location techniques, signal angle of arrival measurement (AOA) techniques, time of arrival location (TOA), time difference of arrival location (TDOA), and the like, enable the location of tags. In order to improve the technical problem of large positioning error in the conventional technology, the invention provides a method for ranging and positioning, and please refer to fig. 1, which is a flowchart for implementing the method for ranging and positioning provided by the embodiment of the invention. A method of ranging and positioning as shown in fig. 1 includes:
s101, acquiring a group of distance data between the tag and each base station of at least three base stations.
UWB location technology calculates a distance value between a base station and a tag by using radio transceiver time measurements. The tag transmits pulses according to a certain frequency and continuously communicates with a plurality of base stations with known positions. The tag needs to communicate with three or more base stations at the same time, and keeps communicating with the base stations for multiple times, so as to obtain multiple distance values between the tag and each base station, namely a set of distance data between the tag and each base station, and further determine the distance data between the tag and each base station. The distances between the nodes are measured using the time of flight of the signal between the tag and the plurality of base stations. The time of flight represents the time of transmission of the signal over the air (i.e. the time of transmission does not include the time from the receipt of the request signal to the transmission of the feedback signal by the base station). First, the tag remains synchronized with multiple base station system times. The label sends a pulse signal requesting for properties to a plurality of base stations, and when the base stations receive the request signal sent by the label, the base stations respectively send feedback signals to the label. And completing multiple communications in a reciprocating manner to obtain a group of distance data between the tag and each base station, wherein the group of distance data comprises multiple distance data. In this embodiment, the positioning of the tag is a periodic positioning, and a set of distance data between the tag and each base station is distance data in one positioning period.
S102, establishing a corresponding three-dimensional coordinate mathematical model according to the three-dimensional coordinate data of each base station and the corresponding preprocessed group of distance data, and generating a corresponding number of three-dimensional coordinate mathematical models according to the number of the base stations.
The three-dimensional coordinate data of the base stations is a unique three-dimensional coordinate value of each base station in a preset map image, so that subsequent calculation is facilitated.
For the distance data, on one hand, the distance data determines the distance data of the tag and the plurality of base stations through signals, and during the transmission process, the signals may affect the signal transmission due to occlusion, for example, a solid wall: the solid wall occlusion can enable the UWB signal to be attenuated by 60-70% and the positioning accuracy error to rise by about 30 cm, and if the two walls or more solid walls are occluded, the UWB signal cannot be positioned; steel plate: the UWB pulse signals are absorbed more seriously by steel, so that the UWB cannot be positioned; telegraph pole or tree: the pole or tree is less than 1 meter from the base station or tag, which may have a large impact on the signal.
On the other hand, the positioning has periodicity, the position of the label is accurately positioned according to a fixed time period, the period is often in a short time, the position of the robot does not change greatly in the short time, and if all distance data in the period are calculated, problems such as data jitter can be caused. The positioning accuracy of the tag may be affected by the two aspects. Therefore, in this embodiment, in order to improve the robustness of positioning, the data is preprocessed before the iterative computation, and the preprocessing is to transmit the distance data to a register, and the register preprocesses the data. Establishing a three-dimensional coordinate mathematical model according to the preprocessed distance data and the three-dimensional coordinate data of the base station, wherein the three-dimensional coordinate mathematical model comprises the following steps:
let us assume the coordinates (x) of the ith base stationi,yi,zi) Distance l to the label coordinates (x, y, z)iThen the mathematical model of the i-th base station's three-dimensional coordinates is:
generating three-dimensional coordinate mathematical models with corresponding quantity according to the number of the base stations as follows:
and S103, performing linear transformation of a nonlinear equation system on the generated three-dimensional coordinate mathematical models.
Since the equation set of a plurality of the three-dimensional coordinate mathematical models is a nonlinear equation set, it is often difficult to obtain an accurate solution when solving such equations. Therefore, after the nonlinear equation system is required to be converted into the linear equation system, the iterative method is utilized to solve the solution gradually approaching the accurate solution.
And S104, iteratively calculating a three-dimensional positioning value and an iteration error value of the label according to the linear equation set and a preset iteration initial value, wherein the preset iteration initial value is an initial coordinate value of the label.
The iterative method is an important method for solving an equation approximation root, continuously uses the process of recursion of a new value by using an old value of a variable, and is a common algorithm for solving the equation or the equation set approximation root. In the iterative computation process, a preset initial iterative value needs to be given for the first iteration, and in the subsequent iteration process, iterative computation is performed through recursion of a new value of an old value, wherein the preset initial iterative value is an initial coordinate value of the tag. In the conventional iterative computation, most of the old values obtained by the last iteration are subjected to iterative computation by recursion new values, and in the embodiment, the selection of the old values depends on the judgment of iteration error values, the old value corresponding to the minimum iteration error value is selected, and the three-dimensional coordinate data of the next iteration is computed, so that the positioning accuracy of each iterative computation is improved. It should be noted that, in this embodiment, the three-dimensional coordinate data of the tag and the three-dimensional positioning value are different from each other, the three-dimensional coordinate data refers to a result obtained by each iteration within one positioning period and is referred to as three-dimensional coordinate data, and the three-dimensional positioning value refers to three-dimensional coordinate data obtained after the iteration calculation is finished (i.e., three-dimensional coordinate data with the smallest iteration error value in the iteration calculation process in this period) and is referred to as a three-dimensional positioning value.
In this embodiment, the distance data of each base station is preprocessed, so that the precision of the distance data is higher, then, a three-dimensional coordinate mathematical model is established through the preprocessed distance data and the three-dimensional coordinate data of each base station, and a three-dimensional positioning value and an iteration error value of the label are calculated through iteration. Through the improvement of distance data and algorithm, compared with the traditional positioning mode, the method has higher positioning accuracy.
Optionally, before obtaining the distance data of each base station, the three-dimensional coordinate values of the base stations need to be determined for subsequent calculation. Therefore, the present embodiment provides another implementation manner before step S101. Referring to fig. 2, fig. 2 is a schematic view of another implementation flow before step S101 in a method for ranging and positioning according to an embodiment of the present invention. As shown in fig. 2, before step S101 in the embodiment shown in fig. 1, the following steps S201 to S202 may be further implemented, including:
s201, establishing a plane coordinate system of a map; the X-axis coordinate and the Y-axis coordinate of the map coordinate system both use one pixel as a length unit, and each length unit represents a fixed X-axis coordinate width value and a fixed Y-axis coordinate length value in a space coordinate system.
Each base station has unique three-dimensional coordinate data in a space coordinate system. Before the distance data of the tag and the plurality of base stations is acquired, the three-dimensional coordinate data of the base stations in the map needs to be determined according to the three-dimensional coordinate data in the space coordinate system, so that the subsequent calculation is facilitated. Specifically, each pixel in the map represents a fixed X-axis coordinate width value and a fixed Y-axis coordinate length value in the spatial coordinate system.
Wherein the map is a complete image consisting of a plurality of pixels, each pixel in the map image representing a length unit,
s202, converting the two-dimensional coordinate data of the XOY plane of each base station in the space coordinate system into three-dimensional coordinate data of the base station in the plane coordinate system according to the X-axis coordinate width value and the Y-axis coordinate length value, and combining the two-dimensional coordinate data and the Z-axis coordinate data of the base station in the space coordinate system into the three-dimensional coordinate data of the base station.
Each pixel of the map image represents a fixed X-axis coordinate width value and Y-axis coordinate length value in a spatial coordinate system, i.e. the width value and the length value in the spatial coordinate system are scaled into the map in equal proportion. And obtaining the three-dimensional coordinate data of the base station according to the combination of the Z-axis data of the base station in the space coordinate system and the X-axis data and the Y-axis data of the base station in the step S201.
In this embodiment, the unique coordinate value of each base station is obtained by establishing a coordinate system of the map before obtaining the data, so as to provide a data basis for subsequent calculation, and further improve the accuracy of tag positioning.
Alternatively, after obtaining the distance data of each base station, the signals of some base stations are weak or blocked because the signals in the UWB positioning technology are often interfered by obstacles such as solid walls, steel plates, glass, wood plates or cardboard, telegraph poles or trees. The distance data needs to be preprocessed, and the robustness of positioning is further improved. Therefore, the present embodiment provides another implementation manner after step S101. Referring to fig. 3, fig. 3 is a schematic view of another implementation flow after step S101 in a method for ranging and positioning according to an embodiment of the present invention. As shown in fig. 3, after step S101 in the embodiment shown in fig. 1, the method further includes: and respectively preprocessing each group of distance data to obtain a plurality of groups of preprocessed distance data. The preprocessing is specifically realized by the following steps S301 to S302:
s301, when the data quantity of a group of distance data is smaller than a preset quantity, deleting the group of distance data; and when the data quantity of one group of distance data is greater than or equal to the preset quantity, reserving the group of distance data.
Some base stations may have less or missing data due to obstructions or self-failures. Therefore, before the mean filtering, the filtering needs to be performed for each set of distance data. If the data quantity of a group of distance data of a certain base station is smaller than a preset quantity (if the signal quality is poor, the group of distance data can be regarded as signal loss), deleting the group of distance data, and otherwise, taking the group of distance data as the distance data for subsequent calculation.
S302, performing mean filtering processing on each group of the reserved distance data to obtain a plurality of groups of the preprocessed distance data.
A plurality of distance data is generated because the tag communicates with each base station a plurality of times in a short period of time, but the location of the tag moves only slightly in the short period of time. If all the distance data in the short time are calculated, problems such as data jitter are easily caused, so in this embodiment, the tag and the plurality of distance data of each base station in the short time are subjected to an average filtering process, that is, the distance data obtained in the short time are averaged, and the average is used as the unique distance data in the short time. The mean filtering is also called linear filtering, and the main method adopted by the mean filtering is a neighborhood averaging method. The basic principle of linear filtering is to replace each pixel value in the original image with the mean value, namely, to-be-processed current pixel (x, y), select a template, which is composed of a plurality of pixels adjacent to the template, calculate the mean value of all pixels in the template, and then give the mean value to the current pixel (x, y), and the gray g (x, y) of the processed image at the point is the total number of pixels including the current pixel in the template.
In this embodiment, after acquiring a plurality of sets of the distance data, preprocessing is performed respectively. And calculating a positioning value of the label through the preprocessed distance data, calculating a three-dimensional positioning value of the label, and improving the robustness of positioning.
Specifically, in the embodiment shown in fig. 1, the step S103 is specifically implemented by the following steps S401 to S404, please refer to fig. 4, and fig. 4 is a flowchart illustrating an implementation procedure of S103 in the method for ranging and positioning according to an embodiment of the present invention, including:
s401, linearly converting the three-dimensional coordinate mathematical models through a Jacobian matrix.
The Jacobian matrix is a matrix formed by arranging first-order partial derivatives in a certain mode, and a nonlinear equation can be converted into a linear equation. In this embodiment, the plurality of three-dimensional coordinate mathematical models are linearly transformed by a jacobian matrix as follows:
s402, calculating a three-dimensional positioning value and an iteration error value of the label by the linear equation set and the iteration initial value through a Gauss-Newton iteration method.
The gauss-newton iteration method is a nonlinear fitting of a least square method, approximately replaces a nonlinear regression model by using a taylor series expansion formula, and obtains a three-dimensional positioning value of the label through multiple iterations, wherein the gauss-newton iteration method has the following formula:
wherein x isk,yk,zkDenotes the result of the kth iteration, xk-1,yk-1,zk-1Denotes the result g (x) of iteration at time k-1k-1,yk-1,zk-1) Denotes the Jacobian matrix, g (x), at the k-1 st iterationk-1,yk-1,zk-1)TDenotes g (x)k-1,yk-1,zk-1) The transposed matrix of (2). The iteration error value represents the satisfaction degree of the iteration result and the three-dimensional coordinate mathematical model, and the ith iteration result (x) is obtained byi,yi,zi) The iterative error value is obtained by substituting into the equation set in step S103. The smaller the iteration error value, the higher the satisfaction degree of the three-dimensional coordinate mathematical model is, and the larger the iteration error value, the lower the satisfaction degree of the three-dimensional coordinate mathematical model is.
And S403, in each iteration calculation, calculating the three-dimensional coordinate data of the label and the iteration error value according to the three-dimensional coordinate data with the minimum iteration error value.
Referring to fig. 5, fig. 5 is a schematic flow chart of the gauss-newton iterative algorithm according to the embodiment of the present invention. In a positioning period, the first iteration calculates first three-dimensional coordinate data and a first iteration error value of the label according to a preset iteration initial value, and records the first three-dimensional coordinate data and the first iteration error value. And calculating second three-dimensional coordinate data and a second iteration error value of the label according to the first three-dimensional coordinate data. And when the third calculation is carried out, comparing the sizes of the first iteration error value and the second iteration error value, selecting the three-dimensional coordinate data with the minimum iteration error value as the three-dimensional coordinate data of the next iteration, and repeating the steps until the iteration times reach the preset times.
S404, when the iterative computation reaches the preset times, selecting the three-dimensional coordinate data with the minimum iterative error value as the three-dimensional positioning value of the label.
Through the calculation logic of step S403, the three-dimensional coordinate data with the minimum iteration error value within the preset iteration number is selected as the three-dimensional positioning value of the tag, and the smaller the iteration error value is, the higher the satisfaction degree of the three-dimensional coordinate mathematical model is, that is, the more accurate the positioning of the tag is.
In this embodiment, the three-dimensional data of the tag is calculated specifically by using the jacobian matrix and the gauss-newton iteration method, and the selection of the final result in the gauss-newton iteration method is improved, and specifically, the three-dimensional coordinate data corresponding to the minimum iteration error value is selected as the three-dimensional positioning value of the tag in the iteration calculation of this period, so that the accuracy of tag positioning is improved.
Optionally, in the embodiment shown in fig. 1, after step S104, one cycle of positioning on the tag is completed, and positioning in a next positioning cycle requires selecting a three-dimensional positioning value in a previous positioning cycle as an iteration initial value in the next positioning cycle, and selecting the iteration initial value also needs to meet a certain requirement, please refer to fig. 6, where fig. 6 is another implementation flow diagram after step S104 in the method for ranging and positioning according to an embodiment of the present invention, and includes:
s601, when the iteration error value is converged, taking the three-dimensional positioning value of the label as an iteration initial value of the next positioning period.
In a positioning period, obtaining three-dimensional coordinate data with the minimum iteration error value within a preset iteration number, judging whether the minimum iteration error value of the period is converged compared with the minimum iteration error value of the previous period, and if the minimum iteration error value of the period is converged, taking the three-dimensional coordinate data corresponding to the minimum iteration error value of the period as an iteration initial value of the next positioning period.
S602, when the iteration error value diverges, recalculating the preprocessed iteration initial value until the iteration error value converges.
And if the minimum iteration error value of the period is divergent, preprocessing the iteration initial value of the period, wherein the preprocessing is to add the initial values X, Y and Z to the same numerical values (except 0 and a negative number) respectively, and bring the preprocessed iteration initial value into the Gauss-Newton iteration formula of the period again. And if the minimum iteration error value is still divergent, adding the same numerical value (except 0 and a negative number) on the basis of the preprocessing until the minimum iteration error value is converged, and taking the corresponding three-dimensional coordinate data during the convergence as an iteration initial value of the next positioning period.
In this embodiment, the iteration initial value of each period is processed and recalculated until the iteration error value converges, so as to ensure the accuracy of each positioning period in positioning the tag.
In the present invention, the data processing includes two aspects of data processing, on one hand, preprocessing the distance data between the tag and the plurality of base stations before iterative computation in one positioning cycle, and on the other hand, processing the initial value iteratively for each positioning cycle during a plurality of positioning cycles. The invention improves the algorithm not only by applying the Gauss-Newton iteration algorithm, but also improves the traditional Gauss-Newton iteration algorithm, thereby further improving the accuracy of the UWB positioning technology.
Referring to fig. 7, the present invention provides a distance measuring and positioning device 7, please refer to fig. 7, fig. 7 is a schematic diagram of a distance measuring and positioning device according to an embodiment of the present invention, and the distance measuring and positioning device shown in fig. 7 includes:
an obtaining unit 71, configured to obtain a set of distance data between the tag and each of at least three base stations;
a calculating unit 72, configured to establish a corresponding three-dimensional coordinate mathematical model according to the three-dimensional coordinate data of each base station and the corresponding preprocessed set of distance data, so as to generate a corresponding number of three-dimensional coordinate mathematical models according to the number of the base stations; performing linear transformation of a nonlinear equation set on the generated three-dimensional coordinate mathematical models; and iteratively calculating the three-dimensional positioning value and the iteration error value of the label according to the linear equation set and a preset iteration initial value, wherein the preset iteration initial value is the initial coordinate value of the label.
Optionally, the apparatus further comprises a creating unit:
establishing a plane coordinate system of a map; the method comprises the following steps that an X-axis coordinate and a Y-axis coordinate of a map coordinate system both use one pixel as a length unit, and each length unit represents a fixed X-axis coordinate width value and a fixed Y-axis coordinate length value in a space coordinate system;
and converting the two-dimensional coordinate data of the XOY plane of each base station in a space coordinate system into three-dimensional coordinate data of the base station in the plane coordinate system according to the X-axis coordinate width value and the Y-axis coordinate length value, and combining the two-dimensional coordinate data and the Z-axis coordinate data of the base station in the space coordinate system into the three-dimensional coordinate data of the base station.
According to the distance measuring and positioning device provided by the invention, the distance data of each base station is preprocessed, so that the precision of the distance data is higher. Secondly, a three-dimensional coordinate mathematical model is established through the preprocessed distance data and the three-dimensional coordinate data of each base station, and a three-dimensional positioning value and an iteration error value of the label are calculated through iteration. Through the improvement of distance data and algorithm, the method has higher positioning accuracy.
It should be understood that, the sequence numbers of the steps in the foregoing embodiments do not imply an execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.
Fig. 8 is a schematic diagram of a terminal device for ranging and positioning according to an embodiment of the present invention. As shown in fig. 8, a ranging positioning terminal device 8 of the embodiment includes: a processor 80, a memory 81 and a computer program 82, such as a ranging and positioning program, stored in said memory 81 and executable on said processor 80. The processor 80 executes the computer program 82 to implement the steps in each of the above-mentioned embodiments of a method for ranging and positioning, such as the steps S101 to S104 shown in fig. 1. Alternatively, the processor 80, when executing the computer program 82, implements the functions of the units in the device embodiments described above, such as the functions of the units 71 to 72 shown in fig. 7.
Illustratively, the computer program 82 may be divided into one or more units, which are stored in the memory 81 and executed by the processor 80 to accomplish the present invention. The one or more units may be a series of computer program instruction segments capable of performing specific functions for describing the execution of the computer program 82 in the terminal device 8 of the kind of ranging positioning. For example, the computer program 82 may be divided into an acquisition unit and a calculation unit, each unit having the following specific functions:
an obtaining unit, configured to obtain a set of distance data between the tag and each of at least three base stations;
the calculation unit is used for establishing a corresponding three-dimensional coordinate mathematical model according to the three-dimensional coordinate data of each base station and the corresponding preprocessed group of distance data so as to generate a corresponding number of three-dimensional coordinate mathematical models according to the number of the base stations; performing linear transformation of a nonlinear equation set on the generated three-dimensional coordinate mathematical models; and iteratively calculating the three-dimensional positioning value and the iteration error value of the label according to the linear equation set and a preset iteration initial value, wherein the preset iteration initial value is the initial coordinate value of the label.
The terminal device 8 for ranging and positioning may be a desktop computer, a notebook, a palm computer, a cloud server, or other computing devices. The terminal device for ranging and positioning may include, but is not limited to, a processor 80 and a memory 81. Those skilled in the art will appreciate that fig. 8 is merely an example of one type of ranging-enabled terminal device 8 and does not constitute a limitation of one type of ranging-enabled terminal device 8 and may include more or fewer components than shown, or some components may be combined, or different components, e.g., the one type of ranging-enabled terminal device may also include input-output devices, network access devices, buses, etc.
The Processor 80 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic device, discrete hardware component, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory 81 may be an internal storage unit of the ranging-positioning terminal device 8, such as a hard disk or a memory of the ranging-positioning terminal device 8. The memory 81 may also be an external storage device of the distance-measuring and positioning terminal device 8, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like, provided on the distance-measuring and positioning terminal device 8. Further, the memory 81 may also comprise both an internal memory unit and an external memory device of the one ranging-positioning terminal device 8. The memory 81 is used for storing the computer program and other programs and data required by the terminal device of one kind of ranging positioning. The memory 81 may also be used to temporarily store data that has been output or is to be output.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-mentioned division of the functional units and modules is illustrated, and in practical applications, the above-mentioned function distribution may be performed by different functional units and modules according to needs, that is, the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-mentioned functions. Each functional unit and module in the embodiments may be integrated in one processing unit, or each unit may exist alone physically, or two or more units are integrated in one unit, and the integrated unit may be implemented in a form of hardware, or in a form of software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working processes of the units and modules in the system may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to the related descriptions of other embodiments for parts that are not described or illustrated in a certain embodiment.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
In the embodiments provided in the present invention, it should be understood that the disclosed terminal device and method may be implemented in other ways. For example, the above-described terminal device embodiments are merely illustrative, and for example, the division of the modules or units is only one logical function division, and there may be other divisions when actually implemented, for example, a plurality of units or components may be combined or may be integrated into another system, or some features may be omitted or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, all or part of the flow of the method according to the embodiments of the present invention may also be implemented by a computer program, which may be stored in a computer-readable storage medium, and when the computer program is executed by a processor, the steps of the method embodiments may be implemented. . Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, and the like. It should be noted that the computer readable medium may contain content that is subject to appropriate increase or decrease as required by legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer readable media does not include electrical carrier signals and telecommunications signals as is required by legislation and patent practice.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present invention, and are intended to be included within the scope of the present invention.
Claims (10)
1. A method for ranging and positioning is used for measuring the distance between a tag and a base station, and is characterized in that the method comprises the following steps:
obtaining a set of distance data between the tag and each of at least three base stations;
establishing a corresponding three-dimensional coordinate mathematical model according to the three-dimensional coordinate data of each base station and the corresponding preprocessed group of distance data so as to generate a corresponding number of three-dimensional coordinate mathematical models according to the number of the base stations;
performing linear transformation of a nonlinear equation set on the generated three-dimensional coordinate mathematical models;
and iteratively calculating the three-dimensional positioning value and the iteration error value of the label according to the linear equation set and a preset iteration initial value, wherein the preset iteration initial value is the initial coordinate value of the label.
2. The method of claim 1, wherein prior to obtaining the set of distance data between the tag and each of the at least three base stations, further comprising:
establishing a plane coordinate system of a map; the method comprises the following steps that an X-axis coordinate and a Y-axis coordinate of a map coordinate system both use one pixel as a length unit, and each length unit represents a fixed X-axis coordinate width value and a fixed Y-axis coordinate length value in a space coordinate system;
and converting the two-dimensional coordinate data of the XOY plane of each base station in a space coordinate system into three-dimensional coordinate data of the base station in the plane coordinate system according to the X-axis coordinate width value and the Y-axis coordinate length value, and combining the two-dimensional coordinate data and the Z-axis coordinate data of the base station in the space coordinate system into the three-dimensional coordinate data of the base station.
3. The method of claim 1, wherein after obtaining a set of distance data between the tag and each of at least three base stations, further comprising: respectively preprocessing each group of distance data to obtain a plurality of groups of preprocessed distance data;
wherein, the preprocessing is respectively carried out on each group of distance data to obtain a plurality of groups of preprocessed distance data, and the method comprises the following steps:
when the number of a group of distance data is smaller than a preset number, deleting the group of distance data; when the number of a group of distance data is greater than or equal to the preset number, reserving the group of distance data;
and respectively carrying out mean value filtering processing on each group of the reserved distance data to obtain a plurality of groups of the preprocessed distance data.
4. The method of claim 1, wherein said linearly transforming the generated plurality of said three-dimensional coordinate mathematical models with a non-linear system of equations comprises:
performing linear transformation on the three-dimensional coordinate mathematical models through a Jacobian matrix;
correspondingly, the iteratively calculating the three-dimensional positioning value and the iteration error value of the tag according to the linear equation set and a preset iteration initial value includes:
and calculating the three-dimensional positioning value and the iteration error value of the label by the linear equation set and the iteration initial value through a Gauss-Newton iteration method.
5. The method of claim 4, wherein iteratively calculating the three-dimensional positioning value and the iteration error value of the tag according to the system of linear equations and a preset iteration initial value, the preset iteration initial value being an initial coordinate value of the tag, comprises:
in each iteration calculation, calculating the three-dimensional coordinate data of the label and an iteration error value according to the three-dimensional coordinate data with the minimum iteration error value;
and when the iterative computation reaches the preset times, selecting the three-dimensional coordinate data with the minimum iterative error value as the three-dimensional positioning value of the label.
6. The method of claim 1, wherein iteratively calculating the three-dimensional positioning value and the iteration error value of the tag according to the system of linear equations and a preset iteration initial value, the preset iteration initial value being an initial coordinate value of the tag, further comprises:
when the iteration error value is converged, taking the three-dimensional positioning value of the label as an iteration initial value of the next positioning period;
and when the iteration error value is diverged, recalculating the preprocessed iteration initial value until the iteration error value is converged.
7. An apparatus for ranging and positioning, which is used for measuring a distance between a tag and a base station, comprising:
an obtaining unit, configured to obtain a set of distance data between the tag and each of at least three base stations;
the calculation unit is used for establishing a corresponding three-dimensional coordinate mathematical model according to the three-dimensional coordinate data of each base station and the corresponding preprocessed group of distance data so as to generate a corresponding number of three-dimensional coordinate mathematical models according to the number of the base stations; performing linear transformation of a nonlinear equation set on the generated three-dimensional coordinate mathematical models; and iteratively calculating the three-dimensional positioning value and the iteration error value of the label according to the linear equation set and a preset iteration initial value, wherein the preset iteration initial value is the initial coordinate value of the label.
8. The apparatus of claim 7, wherein the apparatus further comprises a creating unit:
establishing a plane coordinate system of a map; the method comprises the following steps that an X-axis coordinate and a Y-axis coordinate of a map coordinate system both use one pixel as a length unit, and each length unit represents a fixed X-axis coordinate width value and a fixed Y-axis coordinate length value in a space coordinate system;
and converting the two-dimensional coordinate data of the XOY plane of each base station in a space coordinate system into three-dimensional coordinate data of the base station in the plane coordinate system according to the X-axis coordinate width value and the Y-axis coordinate length value, and combining the two-dimensional coordinate data and the Z-axis coordinate data of the base station in the space coordinate system into the three-dimensional coordinate data of the base station.
9. Terminal device for ranging positioning, comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor implements the steps of the method according to any of claims 1 to 6 when executing the computer program.
10. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 6.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811636477.3A CN111381209A (en) | 2018-12-29 | 2018-12-29 | Distance measurement positioning method and device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811636477.3A CN111381209A (en) | 2018-12-29 | 2018-12-29 | Distance measurement positioning method and device |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN111381209A true CN111381209A (en) | 2020-07-07 |
Family
ID=71214776
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201811636477.3A Pending CN111381209A (en) | 2018-12-29 | 2018-12-29 | Distance measurement positioning method and device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111381209A (en) |
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111918387A (en) * | 2020-08-14 | 2020-11-10 | 合肥工业大学 | Three-base-station three-dimensional positioning method based on UWB technology |
| CN112533288A (en) * | 2020-12-26 | 2021-03-19 | 中北大学 | Self-calibration method for mobile base station position applied to UWB positioning |
| CN113672866A (en) * | 2021-07-27 | 2021-11-19 | 深圳市未来感知科技有限公司 | Measuring point coordinate calibration method, device, equipment and storage medium |
| CN113777557A (en) * | 2021-09-26 | 2021-12-10 | 北方工业大学 | UWB indoor positioning method and system based on redundant distance screening |
| CN114415113A (en) * | 2022-01-14 | 2022-04-29 | 深圳锦沃科技有限公司 | Indoor positioning method and device, computer equipment and storage medium |
| CN114594421A (en) * | 2022-02-15 | 2022-06-07 | 湖北大学 | Moving target point position calculation method based on least square method and Kalman filter |
| CN115157257A (en) * | 2022-07-22 | 2022-10-11 | 山东大学 | Intelligent plant management robot and system based on UWB navigation and visual identification |
| CN115856970A (en) * | 2023-02-13 | 2023-03-28 | 自然资源部第二海洋研究所 | Anchor point positioning method, device, equipment and computer readable storage medium |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102056293A (en) * | 2010-12-10 | 2011-05-11 | 北京星网锐捷网络技术有限公司 | Radio frequency fingerprint positioning method and system as well as access controller (AC) and positioning server |
| CN102186239A (en) * | 2011-04-13 | 2011-09-14 | 福建星网锐捷网络有限公司 | Radio frequency (RF) fingerprint positing method, device and network equipment |
| CN106597364A (en) * | 2016-11-18 | 2017-04-26 | 烟台职业学院 | Target radiation source initial position estimation method for single-antenna single-station passive positioning |
| CN106961725A (en) * | 2017-03-31 | 2017-07-18 | 深圳大学 | Indoor equipotential method and system based on UWB Yu Wifi combined high precisions |
| CN107948296A (en) * | 2017-11-30 | 2018-04-20 | 中电科卫星导航运营服务有限公司 | A kind of indoor locating system and method based on bluetooth |
| CN108717176A (en) * | 2018-04-12 | 2018-10-30 | 哈尔滨工程大学 | Time difference locating technology method based on artificial bee colony algorithm |
-
2018
- 2018-12-29 CN CN201811636477.3A patent/CN111381209A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102056293A (en) * | 2010-12-10 | 2011-05-11 | 北京星网锐捷网络技术有限公司 | Radio frequency fingerprint positioning method and system as well as access controller (AC) and positioning server |
| CN102186239A (en) * | 2011-04-13 | 2011-09-14 | 福建星网锐捷网络有限公司 | Radio frequency (RF) fingerprint positing method, device and network equipment |
| CN106597364A (en) * | 2016-11-18 | 2017-04-26 | 烟台职业学院 | Target radiation source initial position estimation method for single-antenna single-station passive positioning |
| CN106961725A (en) * | 2017-03-31 | 2017-07-18 | 深圳大学 | Indoor equipotential method and system based on UWB Yu Wifi combined high precisions |
| CN107948296A (en) * | 2017-11-30 | 2018-04-20 | 中电科卫星导航运营服务有限公司 | A kind of indoor locating system and method based on bluetooth |
| CN108717176A (en) * | 2018-04-12 | 2018-10-30 | 哈尔滨工程大学 | Time difference locating technology method based on artificial bee colony algorithm |
Non-Patent Citations (1)
| Title |
|---|
| 郭少彬 等: "基于UWB的室内协同定位方法", 《电子信息对抗技术》 * |
Cited By (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111918387B (en) * | 2020-08-14 | 2022-02-11 | 合肥工业大学 | Three-base-station three-dimensional positioning method based on UWB technology |
| CN111918387A (en) * | 2020-08-14 | 2020-11-10 | 合肥工业大学 | Three-base-station three-dimensional positioning method based on UWB technology |
| CN112533288A (en) * | 2020-12-26 | 2021-03-19 | 中北大学 | Self-calibration method for mobile base station position applied to UWB positioning |
| CN112533288B (en) * | 2020-12-26 | 2022-07-08 | 中北大学 | Self-calibration method for mobile base station position applied to UWB positioning |
| CN113672866A (en) * | 2021-07-27 | 2021-11-19 | 深圳市未来感知科技有限公司 | Measuring point coordinate calibration method, device, equipment and storage medium |
| CN113777557B (en) * | 2021-09-26 | 2023-09-15 | 北方工业大学 | UWB indoor positioning method and system based on redundant distance screening |
| CN113777557A (en) * | 2021-09-26 | 2021-12-10 | 北方工业大学 | UWB indoor positioning method and system based on redundant distance screening |
| CN114415113A (en) * | 2022-01-14 | 2022-04-29 | 深圳锦沃科技有限公司 | Indoor positioning method and device, computer equipment and storage medium |
| CN114594421A (en) * | 2022-02-15 | 2022-06-07 | 湖北大学 | Moving target point position calculation method based on least square method and Kalman filter |
| CN114594421B (en) * | 2022-02-15 | 2022-11-18 | 湖北大学 | Moving target point position calculation method based on least square method and Kalman filter |
| CN115157257A (en) * | 2022-07-22 | 2022-10-11 | 山东大学 | Intelligent plant management robot and system based on UWB navigation and visual identification |
| CN115157257B (en) * | 2022-07-22 | 2024-08-27 | 山东大学 | Intelligent plant management robot and system based on UWB navigation and visual recognition |
| CN115856970A (en) * | 2023-02-13 | 2023-03-28 | 自然资源部第二海洋研究所 | Anchor point positioning method, device, equipment and computer readable storage medium |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111381209A (en) | Distance measurement positioning method and device | |
| CN103118333B (en) | Similarity based wireless sensor network mobile node positioning method | |
| CN104853317B (en) | The structure and update method of fingerprint base in a kind of WiFi indoor positionings | |
| KR101556711B1 (en) | Time of arrival based wireless positioning system | |
| CN103338516B (en) | A kind of wireless sensor network two step localization method based on total least square | |
| CN101986757B (en) | Positioning method and device for mobile terminal | |
| Shi | A new weighted centroid localization algorithm based on RSSI | |
| CN104125538A (en) | WIFI (wireless fidelity) network based RSSI (received signal strength indicator) signal strength secondary locating method and device | |
| CN105137390A (en) | Indoor positioning method based on AP with adjustable transmitted power | |
| CN102984745A (en) | Combined estimation method for Wi-Fi AP (wireless fidelity access point) position and path loss model | |
| CN105222789A (en) | A kind of building indoor plane figure method for building up based on laser range sensor | |
| CN103220777A (en) | Mobile device positioning system | |
| CN107484123B (en) | WiFi indoor positioning method based on integrated HWKNN | |
| CN109379711B (en) | positioning method | |
| AU2006321675A1 (en) | System and method for computing the position of a mobile device operating in a wireless network | |
| CN104053129A (en) | Wireless sensor network indoor positioning method and device based on sparse RF fingerprint interpolations | |
| CN105072581A (en) | Indoor positioning method of path attenuation coefficient based database construction | |
| Yan et al. | Research on positioning system based on Zigbee communication | |
| CN103581831A (en) | Indoor locating algorithm based on WiFi and mobile terminal | |
| Yingxi et al. | WSN node localization algorithm design based on RSSI technology | |
| CN108072860A (en) | A kind of 3-D positioning method based on radio communication base station | |
| CN105652235A (en) | Linear regression algorithm-based WLAN indoor positioning multi-user RSS (Received Signal Strength) fusion method | |
| CN110636436A (en) | Three-dimensional UWB indoor positioning method based on improved CHAN algorithm | |
| WO2024088243A1 (en) | Uwb-based positioning method and device, and medium | |
| CN103916956A (en) | Optimization method for wireless transmission environment loss parameters in indoor positioning system |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20200707 |