A positioning method, storage medium and system based on attributes of positioning candidate areas

Abstract

The present invention discloses a positioning method, storage medium, and system based on the attributes of a candidate positioning area. The method uses environmental information about the positioning base station and target device, as well as positioning measurement reports reported by the base station, to initially obtain approximate target location information by combining the environmental information and measurement reports. After obtaining the rough target location information, the method iteratively selects more accurate measurement report information based on the principle of ray propagation, thereby calculating more accurate target location information. The present invention can select more accurate base station measurement reports in combination with environmental model information to obtain more accurate location information. Using more accurate environmental model information, the method filters error data from a positive feedback perspective and utilizes environmental information to obtain higher positioning accuracy.

Description

Technical Field

[0001] The present invention relates to the field of terminal positioning technology, and in particular to a positioning method, storage medium and system based on attributes of a positioning candidate area. Background Art

[0002] When using measurement data in a positioning algorithm to calculate the target user's location information, environmental factors and the quality of the measurement data will affect positioning accuracy. Incorporating environmental characteristics and selecting unobstructed, high-precision data from the positioning measurement data will significantly improve positioning accuracy. However, before positioning begins, we do not know the target's location, so we cannot incorporate environmental characteristics and determine the quality of the measurement value. Summary of the Invention

[0003] In order to overcome the above technical deficiencies, the present invention provides a positioning method, a storage medium and a system based on the attributes of a positioning candidate area, which can improve the calculation accuracy of target positioning.

[0004] In order to solve the above problems, the present invention is implemented according to the following technical solutions:

[0005] In a first aspect, the present invention provides a positioning method based on attributes of a positioning candidate area, comprising the following steps:

[0006] Obtain the spatial model of the candidate positioning area covered by the base station, roughly divide the candidate positioning area according to the working parameters of the base stations in the candidate positioning area, obtain the roughly divided area closest to each base station, and obtain the measurement report of each base station;

[0007] Calculate the location information of the target device based on the measurement report of each base station;

[0008] Divide the coarse divided area into fine divided areas, and determine the fine divided area to which the target device belongs based on the positioning information of the target device;

[0009] Based on the location information of the target device and the subdivided area to which it belongs, the base station data is filtered and the location information of the target device is updated;

[0010] Calculate the positioning error change of the positioning information, determine whether the positioning error change meets the convergence condition, and if so, output the positioning information of the target device; if not, return to the step of dividing the coarse divided area into fine divided areas, and determine the fine divided area to which the target device belongs based on the positioning information of the target device to perform iterative calculation until the positioning error change meets the convergence condition.

[0011] As an improvement to the above solution, the step of calculating the positioning information of the target device according to the measurement report of each base station includes the following steps:

[0012] According to the area attributes of each coarsely divided area, obtaining the line-of-sight transmission base stations and non-line-of-sight transmission base stations of each coarsely divided area;

[0013] Determine the coarse-divided area where the target device may be located, obtain the line-of-sight propagation base station set in the coarse-divided area where the target device may be located, and calculate the positioning information of the target device based on the measurement report of the line-of-sight propagation base station set.

[0014] As an improvement to the above solution, when the target device may be in more than one coarsely divided area, the set of visible transmission line-of-sight base stations is the union of the visible transmission base stations in the coarsely divided areas in which the target device may be located.

[0015] As an improvement to the above solution, based on the positioning information of the target device and the subdivided area to which it belongs, filtering the base station data and updating the positioning information of the target device include the following steps:

[0016] According to the regional attributes of each subdivided area, obtaining the line-of-sight transmission base stations and non-line-of-sight transmission base stations of each subdivided area;

[0017] The subdivided area where the target device is located is determined according to the positioning information, a line-of-sight propagation base station set of the subdivided area where the target device is located is obtained, and the positioning information of the target device is updated according to the measurement report of the line-of-sight propagation base station set.

[0018] As an improvement to the above solution, based on the positioning information of the target device and the subdivided area to which it belongs, filtering the base station data and updating the positioning information of the target device include the following steps:

[0019] According to the positioning information of the target device, the measurement error of each base station is calculated to obtain an error set;

[0020] The base station data with an error value less than the error threshold is selected from the error set to calculate and update the positioning information of the target device.

[0021] As an improvement to the above solution, the step of determining whether the change in positioning error satisfies the convergence condition includes:

[0022] If the change in positioning error is less than the threshold, the convergence condition is met;

[0023] If the change in positioning error is greater than or equal to the threshold, the convergence condition is not met.

[0024] As an improvement to the above solution, the steps of coarsely dividing the candidate positioning area and dividing the coarsely divided area into finely divided areas adopt the principle of 3D ray tracing.

[0025] As an improvement to the above solution, the measurement report includes base station coordinates and measurement delay.

[0026] In a second aspect, the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores at least one instruction, at least one program, code set, or instruction set, and the at least one instruction, at least one program, code set, or instruction set is loaded and executed by a processor to implement the positioning method based on the attributes of the positioning candidate area as described in the first aspect.

[0027] In a third aspect, the present invention provides a device comprising a processor and a memory, wherein the memory stores at least one instruction, at least one program, code set, or instruction set, and the at least one instruction, at least one program, code set, or instruction set is loaded and executed by the processor to implement the positioning method based on the attributes of the positioning candidate area as described in the first aspect.

[0028] Compared with the prior art, the present invention has the following beneficial effects:

[0029] This application divides the positioning area into attributes based on map information, and then combines the environmental attributes to roughly calculate the target position to obtain the initial positioning information of the target. The base station data is then screened based on the initial positioning information, and the positioning information is repeatedly iterated to improve the positioning accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] The specific embodiments of the present invention will be further described in detail below with reference to the accompanying drawings, wherein:

[0031] Figure 1 1 is a flow chart of a positioning method based on attributes of a positioning candidate area in one embodiment;

[0032] Figure 2 A schematic plan view of a building model described in some embodiments;

[0033] Figure 3 is a flowchart of step S200 in some embodiments;

[0034] Figure 4 is a flowchart of step S400 in some embodiments;

[0035] Figure 5 A schematic plan view of a detailed division of a building model in some embodiments;

[0036] Figure 6 is another flowchart of step S400 in some embodiments;

[0037] Figure 7 is a plan view of a spatial area in one embodiment;

[0038] Figure 8 It is a planar schematic diagram of the detailed division of spatial regions in one embodiment. DETAILED DESCRIPTION

[0039] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0040] It should be noted that the serial numbers mentioned in this article, such as S100, S200, etc., are only used to distinguish between steps and do not mean that the steps must be strictly executed in the order of the serial numbers.

[0041] The present invention provides a positioning method based on the attributes of the candidate positioning area, which is applied to the scenario where the RTOA measurement value reported by the 5G base station uses the UTDOA positioning algorithm to perform target positioning. The location information of the target UE can be calculated by using the positioning algorithm through the time delay difference between the target UE and each base station, which is used to obtain the location information of the terminal user and improve the positioning accuracy.

[0042] In one embodiment, Figure 1 As shown, a positioning method based on the attributes of a positioning candidate area includes the following steps:

[0043] S100: Obtain a spatial model of a candidate positioning area covered by a base station, roughly divide the candidate positioning area according to the working parameters of the base stations in the candidate positioning area, obtain the roughly divided area closest to each base station, and obtain a measurement report for each base station;

[0044] Obtain the spatial model of the candidate positioning area covered by the base station by using surveying and mapping methods, or through CAD drawings of the positioning environment, to obtain the environmental information of the positioning target, and attach the surveyed base station coordinates to the map. First, use the principle of the nearest base station to roughly divide the radiation range of each base station, and then use the principle of ray propagation to determine the base stations that can propagate in a straight line and the base stations that cannot propagate in a straight line in each coarse range, and obtain the measurement data reported by the base station.

[0045] Specifically, based on the environmental attributes of the base station, the characteristics of ray straight line propagation can be used to take into account obstacles and other information in the environment. The entire map information can be divided into multiple areas. In each area, the measurement quality of some base stations can be set to be acceptable, while the measurement quality of some base stations is definitely not acceptable. Figure 2 For example, in Figure 2 In the room model, due to the obstruction of some walls and obstacles, the positioning area can be divided into four blocks, ABCD. The measurement reports reported by the base station are obtained for each block. The measurement reports include the base station coordinates and measurement delay. Based on the measurement quality of the base station in each block, a judgment can be made as follows:

[0046] Area A: Base stations with potentially good measurement quality {base stations 1, 2, 3}, and base stations with poor measurement quality {base stations 4, 5, 6}

[0047] Area B: Base stations with potentially good measurement quality {base station 1, 2}, base stations with poor measurement quality {base station 3, 4, 5, 6}

[0048] Area C: Base stations with potentially good measurement quality {base station 1, 3}, base stations with poor measurement quality {base station 2, 4, 5, 6}

[0049] Region D: Base stations with potentially good measurement quality {base stations 4, 5, 6}, base stations with poor measurement quality {base stations 1, 2, 3}

[0050] S200: Calculating the positioning information of the target device based on the measurement report of each base station;

[0051] After obtaining the measurement data reported by the base station, the target is mapped to the previously divided coarse area, and the appropriate base station data is selected to perform the first step of target positioning. Specifically, Figure 3 As shown, the step S200 further includes the following steps:

[0052] S210: Acquire, according to the area attributes of each coarsely divided area, base stations with line-of-sight transmission and base stations without line-of-sight transmission in each coarsely divided area;

[0053] S220: Determine the coarse-divided area where the target device may be located, obtain the line-of-sight base station set in the coarse-divided area where the target device may be located, and calculate the positioning information of the target device based on the measurement report of the line-of-sight base station set.

[0054] For details, please continue to refer to Figure 2 , where the line-of-sight transmission base station in each coarsely divided area is the base station with possibly good measurement quality in each of the above-mentioned areas, and the non-line-of-sight transmission base station in each coarsely divided area is the base station with poor measurement quality. The area where the target may be located is determined based on the value of the measurement signal collected by the base station. For example, when the minimum value of the measurement delay Ta of the base station received by the target is prru1, the area where the target may be located is area A. When the minimum base station is prru4, 5, 6, the area where the target is located is area D. Based on the regional attributes, base stations with possibly reliable measurement values ​​are selected, and base stations with definitely poor measurement values ​​are filtered out. Based on the measurement reports of the filtered line-of-sight transmission base stations, the positioning information of the target device is calculated.

[0055] Specifically, the method for calculating the positioning information of the target device based on the measurement report of the line-of-sight base station set is as follows:

[0056] The location information of each base station and the received measured delay signal are shown in the following formula:

[0057] gnb 01 :[x1,y1,z1,Ta1]

[0058] gnb 02 :[x2,y2,z2,Ta2] ......

[0060] gnb 0i :[x i ,y i ,z i ,Ta i ]

[0061] Among them gnb 0i , 0 represents the base station data selected after the 0th iteration, and i represents the data of the i-th base station.

[0062] Using the minimum Ta value, we can determine the spatial prru belonging information of the positioning target, and thus preliminarily determine which base station measurement data must be unreliable. After excluding the unreliable base station data, the re-acquired base station measurement data is:

[0063] gnb 11 :[x1,y1,z1,Ta1]

[0064] gnb 12 :[x2,y2,z2,Ta2] ......

[0066] gnb 1m :[x m ,y m ,z m ,Ta m ]

[0067] Select the reference base station and construct the UTDOA positioning equation as follows:

[0068]

[0069] When the number of selected equations exceeds 3, the least squares method is used to transform the above nonlinear equations into linear iterations to solve the initial target position information:

[0070] [x,y,z]=[x ue1 ,y ue1 ,z ue1 ]

[0071] In some embodiments, when the target device may be located in more than one coarsely divided area, the set of line-of-sight base stations is a union of the line-of-sight base stations in the coarsely divided areas.

[0072] Specifically, to determine the target's location, the nearest base station cannot completely accurately locate the target's location. For example, when the nearest base station received is prru3, the target may be in area C or area A. Therefore, for a possibly good base station, the union should be selected, and for a relatively poor base station, the intersection should be selected:

[0073] The union of area A: base stations {base stations 1, 2, 3} with potentially good measurement quality and area C: base stations {base stations 1, 3} with potentially good measurement quality is: base stations {base stations 1, 2, 3} with potentially good measurement quality.

[0074] The intersection of area A: base stations with poor measurement quality {base stations 4, 5, 6} and area C: base stations with poor measurement quality {base stations 2, 4, 5, 6} is: base stations with poor measurement quality {base stations 4, 5, 6}.

[0075] Finally, when prru3 is the nearest base station, the good and bad intervals are: base stations with potentially good measurement quality {base stations 1, 2, 3}; base stations with poor measurement quality {base stations 4, 5, 6}. Therefore, when prru3 is the nearest base station, the measurement data of base stations 1, 2, and 3 are used to calculate the positioning information of the target device. When the target is in other locations, the same process is applied.

[0076] S300: Divide the coarse divided area into fine divided areas, and determine the fine divided area to which the target device belongs based on the positioning information of the target device;

[0077] Specifically, the roughly divided areas are refined to obtain smaller refined areas within each coarse area, and based on the positioning information of the target device obtained by the initial calculation, it is determined to which refined area the positioning information belongs.

[0078] S400: Filtering base station data based on the target device's location information and the subdivided area to which it belongs, and updating the target device's location information;

[0079] Specifically, based on the initial positioning information of the target device and the subdivided area described in the positioning information, useful base station data is further filtered, and the positioning information of the target device is calculated based on the filtered base station data.

[0080] In some embodiments, such as Figure 4 As shown, step S400 includes the following steps:

[0081] S410: Acquire, according to the area attributes of each subdivided area, base stations with line-of-sight transmission and base stations without line-of-sight transmission in each subdivided area;

[0082] S420: Determine the subdivided area where the target device is located based on the positioning information, obtain the line-of-sight base station set for the subdivided area where the target device is located, and update the positioning information of the target device based on the measurement report of the line-of-sight base station set.

[0083] Specifically, with relatively accurate target location information, we can further determine the environmental attributes of the area, and the loose set relationship originally calculated by union and intersection can further confirm which base station data is better, such as Figure 5 As shown, based on the original, area A is further subdivided into areas A1, A2, and A3. The possible base stations in area A1 are [prru1, prru3, prru5, prru6], the possible base stations in area A2 are [prru1, prru2, prru3, prru5], and the possible base stations in area A3 are [prru1, prru3, prru6]. This allows for more refined use of environmental factors to assist in solving the target's location positioning problem. By determining the subdivided area where the target device is located and obtaining the measurement report of the line-of-sight transmission base station in the subdivided area, the positioning information of the target device is further updated based on the measurement report of the line-of-sight transmission base station. The calculation of the target's positioning information based on the measurement report of the line-of-sight transmission base station is described above and will not be repeated here.

[0084] In some embodiments, such as Figure 6 As shown, step S400 includes the following steps:

[0085] S430: Calculate the measurement error of each base station based on the positioning information of the target device to obtain an error set;

[0086] S440: Select base station data with an error value less than a threshold value in the error set, and calculate and update the positioning information of the target device.

[0087] Specifically, the base station measurement reporting strategy after filtering by regional environmental information is not the only method. In addition, the accuracy of the measurement value can be reversely calculated by the calculated target position, thereby selecting base station data with higher measurement accuracy to calculate the target position. The calculation method is as follows:

[0088] Substitute the target device’s location information into the calculation formula for Ta:

[0089]

[0090] Calculate the error function: err 11 =|Ta 11 -Ta1|

[0091] Similarly, we can calculate the error feedback of the measurement values ​​of all base stations. The error set is as follows:

[0092] err1=[err 11 ,err 12 ,...,err 1i ]

[0093] By setting the tolerance error threshold err thre , select the base station data with measurement error less than the error threshold in the err1 set, and use the selected base station data to iteratively calculate the second round of positioning information of the target device. The calculation method is described above and will not be repeated here, thereby obtaining the second round of target position information:

[0094] [x,y,z]=[x ue2 ,y ue2 ,z ue2 ]

[0095] S500: Calculate the positioning error change of the positioning information, determine whether the positioning error change meets the convergence condition, and if so, output the positioning information of the target device; if not, return to the step of dividing the coarse divided area into fine divided areas, and determine the fine divided area to which the target device belongs based on the positioning information of the target device to perform iterative calculation until the positioning error change meets the convergence condition.

[0096] Specifically, after calculating the target position information for the second round, it is necessary to evaluate the positioning quality of the second round. The change in positioning error over multiple rounds of iterations is set as follows:

[0097]

[0098] And set the threshold of position change By calculating the position difference when iterating Determine whether the change in positioning error meets the convergence condition. When the change in positioning error is less than the change threshold, it is considered that the positioning algorithm has reached stability, and the target position output will be calculated at this time; when When the value is greater than or equal to the set threshold information, the calculated latest target position information needs to be substituted into step S300 and the iterative calculation is continued until the iterative convergence condition is met.

[0099] In some embodiments, the steps of coarsely dividing the candidate positioning area and dividing the coarsely divided area into finely divided areas utilize 3D ray tracing principles, identifying direct propagation paths and transmission paths as line-of-sight propagation, and other diffraction paths and reflection paths as non-line-of-sight propagation. Ray tracing principles are used to coarsely and finely divide the line-of-sight propagation area covered by the base station. The coarse division facilitates the determination of user areas based on the target user's measurement report, while the fine division facilitates obtaining more accurate line-of-sight and non-line-of-sight base station measurement reports once the target user's approximate location information is known.

[0100] The following further describes the positioning method based on the attributes of the candidate positioning area in conjunction with one of the embodiments:

[0101] like Figure 7 In the environment shown, the obtained 2D map of the environment where the positioning target is located and the location of the base station are used to roughly divide the spatial area into several intervals. In each interval, the distance between the target and the core base station in the interval is guaranteed to be the shortest. Therefore, the current map can be roughly divided into seven areas. Based on the principle of ray tracing, the reachable base stations and the absolutely unreachable base stations in each area are divided. The effect of the division is shown below:

[0102] Area A: Base stations with potentially good measurement quality {base station 1, 2}, base stations with poor measurement quality {base station 3, 4, 5, 6}

[0103] Area B: Base stations with potentially good measurement quality {base stations 1, 2, 3, 4, 6}, and base stations with poor measurement quality {base stations 5, 7}

[0104] Area C: Base stations with potentially good measurement quality {base stations 2, 3, 4, 5, 6}, and base stations with poor measurement quality {base stations 1, 7}

[0105] Region D: Base stations with potentially good measurement quality {base stations 2, 3, 5, 6, 7}, and base stations with poor measurement quality {base stations 1, 4}

[0106] Area E: Base stations with potentially good measurement quality {base stations 2, 3, 4}, base stations with poor measurement quality {base stations 1, 5, 6, 7}

[0107] Area F: Base stations with potentially good measurement quality {base stations 3, 5, 6}, base stations with poor measurement quality {base stations 1, 2, 4, 7}

[0108] Area G: Base stations with potentially good measurement quality {base stations 6, 7}, base stations with poor measurement quality {base stations 1, 2, 3, 4, 5}

[0109] Based on the measured delay signal of the received base station, the target area is determined and the first step of base station data selection is performed. For example, the base station data received in this case is:

[0110] Prru1: Coordinates: [7m, 6m], Measurement value: 202.3Tc

[0111] Prru2: Coordinates: [8.5m, 28.6m], Measurement value: 107.5Tc

[0112] Prru3: Coordinates: [30m, 26m], Measurement value: 42Tc

[0113] Prru4: Coordinates: [23.4m, 15m], Measurement value: 63Tc

[0114] Prru5: Coordinates: [38.8m, 9m], Measurement value: 158Tc

[0115] Prru6: Coordinates: [56m, 29m], Measurement value: 216Tc

[0116] Prru7: Coordinates: [55m, 10.5m], Measurement value: 251Tc

[0117] As shown in the above measurement values, the target is closest to prru3, so the target is located in area C. Referring to the screening conditions for good and bad base stations in area C, it can be seen that:

[0118] Area C: Base stations with potentially good measurement quality {base stations 2, 3, 4, 5, 6}, and base stations with poor measurement quality {base stations 1, 7}

[0119] Therefore, the base station data participating in the first iterative calculation is:

[0120] Prru2: Coordinates: [8.5m, 28.6m], Measurement value: 107.5Tc

[0121] Prru3: Coordinates: [30m, 26m], Measurement value: 42Tc

[0122] Prru4: Coordinates: [23.4m, 15m], Measurement value: 63Tc

[0123] Prru5: Coordinates: [38.8m, 9m], Measurement value: 158Tc

[0124] Prru6: Coordinates: [56m, 29m], Measurement value: 216Tc

[0125] Construct the UTDOA equations, bring the above measurement data into the constructed UTDOA, and use the least squares method to iteratively calculate the target position to obtain the initial solution: [x ue1 ,y ue1 ]=[22m,26m]

[0126] Substitute the calculated target position into the error calculation of the base station measurement value, and calculate the measurement error of each station as follows:

[0127] err 11 =|163.8-202.3|=38.5

[0128] err 12 =|90-107.5|=17.5

[0129] err 13 =|52.4-42|=10.4

[0130] err 14 =|72.7-63|=9.7

[0131] err 15 =|156.6-158|=1.4

[0132] err 16 =|223.7-216|=7.7

[0133] err 17 =|239-216|=23

[0134] According to the error sorting, we can further confirm that the data of prru1, prru2 and prru7 are excluded, and the positioning information calculation of the filtered base station data is repeated to obtain the second round of positioning results: [x ue2 ,y ue2 ]=[22.6m,23.9m]

[0135] Substitute the calculated target position repeatedly into the error calculation of the base station measurement value, and calculate the measurement error of each station as follows:

[0136] err 11 =|155.6-202.3|=46.7

[0137] err 12 =|97-107.5|=10.5

[0138] err 13 =|50.4-42|=8.4

[0139] err 14 =|58.5-63|=4.5

[0140] err 15 =|144-158|=14

[0141] err 16 =|221.4-216|=5.4

[0142] err 17 =|229.8-216|=13.8

[0143] Through error sorting, we can see that prru5 will be excluded from the adopted calculation range, and prru2 will be re-included in the calculation space. After having detailed positioning results, we can also use more detailed environmental factors to determine whether to adopt the measurement data of the base station. According to the principle of ray straight line propagation, the interval can be divided into Figure 8 For example, if we divide areas B and C into more detailed areas, the reliability of the base station data will be clearer. Figure 8 It can be seen that the properties of regions B1, C1, and C2 are as follows:

[0144] Area B1: Base stations with potentially good measurement quality {base stations 1, 2, 3, 4, 6}, base stations with poor measurement quality {base stations 5, 7}

[0145] Area C1: Base stations with potentially good measurement quality {base stations 2, 3, 4, 5, 6}, and base stations with poor measurement quality {base stations 1, 7}

[0146] Area C2: Base stations with potentially good measurement quality {base stations 2, 3, 4, 6}, base stations with poor measurement quality {base stations 1, 5, 7}

[0147] In the second round of positioning results, the target's positioning area is in C2, so the available base station data are prru2, 3, 4, and 6, which is consistent with the results of error calculation and elimination. Therefore, the following data can be selected for the third round of iterative calculation:

[0148] Prru2: Coordinates: [8.5m, 28.6m], Measurement value: 107.5Tc

[0149] Prru3: Coordinates: [30m, 26m], Measurement value: 42Tc

[0150] Prru4: Coordinates: [23.4m, 15m], Measurement value: 63Tc

[0151] Prru6: Coordinates: [56m, 29m], Measurement value: 216Tc

[0152] The above data is used to calculate the positioning information of the target, and the calculated position of the target is: [x ue3 ,y ue3 ]=[23.5m,24.2m].

[0153] Finally, referring to the previous error change calculation method, calculate the error change and judge whether the positioning information meets the convergence condition. If the positioning error change is less than the change threshold, it is considered that the positioning information has reached stability, and the target position output will be calculated at this time; when When the value is greater than or equal to the set threshold, the latest target location information calculated needs to be substituted into the measurement error value calculation, data screening is performed, and iterative calculations are continued until the iterative convergence conditions are met. After the target positioning information is stabilized, the iterative calculation is exited and the positioning result is output. Compared with directly using all measurement data for positioning solution, the positioning accuracy of this method is greatly improved. In addition, the algorithm selects base station data and uses the logic of environmental attributes clearly. The algorithm has low complexity, strong operability, and is suitable for practical application.

[0154] The present invention obtains the environmental information of the positioning target by utilizing surveying and mapping means or CAD drawings of the positioning environment, and attaches the surveyed base station coordinates to the map. First, the radiation range of each base station is roughly divided by the principle of the nearest base station, and then the base stations that can propagate in a straight line and the base stations that cannot propagate in a straight line in each rough range are determined by the principle of ray propagation. After obtaining the measurement data reported by the base station, the target is matched to the previously divided radiation interval, and the appropriate base station data is selected to perform the first step of target positioning. After obtaining the positioning structure, the original coarse positioning result can be brought into the finely divided area according to the principle of ray propagation to obtain accurate and reliable base station data for iterative calculation. In the calculation process, the measurement error is re-evaluated, and the reliable base station is comprehensively selected in combination with the environmental attributes to iteratively calculate the best positioning accuracy.

[0155] In some embodiments, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program. When the computer program is executed by a processor, the processor implements the positioning method based on the attributes of the positioning candidate area provided in the first aspect.

[0156] It will be understood by those skilled in the art that all or some of the steps, systems, and functional modules / units in the methods disclosed above may be implemented as software, firmware, hardware, and appropriate combinations thereof. In a hardware implementation, the division between the functional modules / units mentioned in the above description does not necessarily correspond to the division of physical components; for example, a physical component may have multiple functions, or a function or step may be performed by several physical components in cooperation. Some or all physical components may be implemented as software executed by a processor, such as a central processing unit, a digital signal processor, or a microprocessor, or may be implemented as hardware, or may be implemented as an integrated circuit, such as an application-specific integrated circuit. Such software may be distributed on a computer-readable storage medium, which may include a computer-readable storage medium (or a non-transitory medium) and a communication medium (or a temporary medium).

[0157] As is well known to those skilled in the art, the term computer-readable storage media includes volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules or other data). Computer-readable storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to store the desired information and can be accessed by a computer. Furthermore, as is well known to those skilled in the art, communication media typically contains computer-readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism, and may include any information delivery media.

[0158] Exemplarily, the computer-readable storage medium may be an internal storage unit of the network management device described in the aforementioned embodiment, such as a hard disk or memory of the network management device. The computer-readable storage medium may also be an external storage device of the network management device, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) card, a flash memory card, etc., equipped on the network management device.

[0159] In some embodiments, a device is provided, comprising a processor and a memory, wherein the memory is used to store a computer program; the processor is used to execute the computer program and implement the positioning method based on the attributes of the candidate positioning area provided by the first aspect of the present invention when executing the computer program.

[0160] It should be understood that the processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc.

[0161] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in the present invention, and such modifications or substitutions are intended to be within the scope of protection of the present invention. Therefore, the scope of protection of the present invention shall be subject to the scope of protection of the claims.

Claims

1. A positioning method based on attributes of a positioning candidate area, characterized in that: The steps include: Obtain the spatial model of the candidate positioning area covered by the base station, roughly divide the candidate positioning area according to the working parameters of the base stations in the candidate positioning area, obtain the roughly divided area closest to each base station, and obtain the measurement report of each base station; According to the area attributes of each coarsely divided area, obtaining the line-of-sight transmission base stations and non-line-of-sight transmission base stations of each coarsely divided area; Determine the coarse-divided area where the target device may be located, obtain a set of line-of-sight base stations in the coarse-divided area where the target device may be located, and calculate the positioning information of the target device based on measurement reports of the line-of-sight base stations. Divide the coarse divided area into fine divided areas, and determine the fine divided area to which the target device belongs based on the positioning information of the target device; Based on the location information of the target device and the subdivided area to which it belongs, the base station data is filtered and the location information of the target device is updated; Calculate the positioning error change of the positioning information, determine whether the positioning error change meets the convergence condition, and if so, output the positioning information of the target device; if not, return to the step of dividing the coarse divided area into fine divided areas, and determine the fine divided area to which the target device belongs based on the positioning information of the target device to perform iterative calculation until the positioning error change meets the convergence condition.

2. The positioning method based on the attributes of the candidate positioning area according to claim 1, characterized in that: When the target device may be located in more than one coarsely divided area, the set of line-of-sight base stations is the union of the line-of-sight base stations in the coarsely divided areas where the target device may be located.

3. The positioning method based on the attributes of the candidate positioning area according to claim 1, characterized in that: Based on the location information of the target device and the subdivided area to which it belongs, filtering the base station data and updating the location information of the target device include the following steps: According to the regional attributes of each subdivided area, obtaining the line-of-sight transmission base stations and non-line-of-sight transmission base stations of each subdivided area; The subdivided area where the target device is located is determined according to the positioning information, a line-of-sight propagation base station set of the subdivided area where the target device is located is obtained, and the positioning information of the target device is updated according to the measurement report of the line-of-sight propagation base station set.

4. The positioning method based on the attributes of the candidate positioning area according to claim 1, characterized in that: Based on the location information of the target device and the subdivided area to which it belongs, filtering the base station data and updating the location information of the target device include the following steps: According to the positioning information of the target device, the measurement error of each base station is calculated to obtain an error set; The base station data with an error value less than the error threshold is selected from the error set to calculate and update the positioning information of the target device.

5. The positioning method based on the attributes of the candidate positioning area according to claim 1, characterized in that: The steps of determining whether the change in positioning error satisfies the convergence condition include: If the change in positioning error is less than the threshold, the convergence condition is met; If the change in positioning error is greater than or equal to the threshold, the convergence condition is not met.

6. The positioning method based on the attributes of the candidate positioning area according to claim 1, characterized in that: The steps of coarsely dividing the positioning candidate area and dividing the coarsely divided area into finely divided areas adopt the principle of 3D ray tracing.

7. The positioning method based on the attributes of the candidate positioning area according to claim 1, characterized in that: The measurement report includes base station coordinates and measurement delay.

8. A computer-readable storage medium, characterized in that The computer-readable storage medium stores at least one instruction, at least one program, code set, or instruction set, and the at least one instruction, at least one program, code set, or instruction set is loaded and executed by the processor to implement the positioning method based on the attributes of the candidate positioning area as described in any one of claims 1 to 7.

9. A device, characterized in that The device includes a processor and a memory, wherein the memory stores at least one instruction, at least one program, code set, or instruction set, and the at least one instruction, at least one program, code set, or instruction set is loaded and executed by the processor to implement the positioning method based on the attributes of the positioning candidate area according to any one of claims 1 to 7.

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