Positioning method, device and computing equipment for dynamic weighting of multi-source data

Abstract

The embodiment of the present invention relates to the field of wireless positioning technology, and discloses a positioning method, device and computing equipment for dynamic weighting of multi-source data, the method comprising: obtaining the positions of multiple beacons near a test point, collecting signal characteristic values ​​of multiple beacons and establishing a fingerprint library; calculating the fingerprint library positioning coordinates of the test point at the current moment according to the fingerprint library and calculating the Euclidean distance, and applying a three-point positioning method to calculate the three-point positioning coordinates of the test point at the current moment; obtaining a first weight value according to the Euclidean distance, and combining the fingerprint library positioning coordinates and the three-point positioning coordinates according to the first weight value to obtain the combined first positioning coordinates; correcting the first positioning coordinates according to inertial navigation to obtain the final positioning coordinates. Through the above-mentioned method, the embodiment of the present invention combines the three-point positioning and fingerprint library weighted positioning technologies, and screens out abnormal points through inertial navigation in a short time to improve positioning accuracy.

Description

Technical Field

[0001] The embodiments of the present invention relate to the field of wireless positioning technology, and in particular to a positioning method, device and computing equipment for dynamically weighting multi-source data. Background Art

[0002] In indoor positioning calculations, fingerprint database, three-point positioning, and inertial navigation are all commonly used technologies. Fingerprint database is a common positioning technology. Generally, fingerprint databases use KNN, or K-nearest neighbor algorithm, or WKNN, or weighted K-nearest neighbor algorithm. Both collect the signal strength of several beacons at the test point, match the collected signal feature values ​​with the data in the fingerprint database collected offline, and the location coordinates of the fingerprint record with the highest matching degree and the most similarity are the coordinates of the test point. The accuracy of indoor positioning is closely related to the collected fingerprint database data. Moreover, since the signal feature values ​​collected at the same point often fluctuate, there will be a certain deviation in the positioning of the fingerprint database itself.

[0003] Three-point positioning is a method of calculating the test point based on the distance from the test point to the base station and the coordinates of the base station itself. Three-point positioning is mainly affected by the coordinate position of the beacon and the calculated distance. Generally speaking, the distance is calculated based on the signal characteristic value or time difference. The positioning accuracy may also be affected by factors such as signal fluctuations or external interference.

[0004] Inertial navigation is based on Newton's laws of mechanics and is a widely used positioning method in indoor positioning. The positioning error of inertial navigation increases over time, and the long-term accuracy is poor. Generally, the positioning accuracy in a short period of time is more accurate. Summary of the invention

[0005] In view of the above problems, the embodiments of the present invention provide a positioning method, apparatus and computing device for dynamically weighting multi-source data, which overcome the above problems or at least partially solve the above problems.

[0006] According to one aspect of an embodiment of the present invention, a positioning method for dynamically weighting multi-source data is provided, the method comprising: obtaining positions of multiple beacons near a test point, collecting signal characteristic values ​​of the multiple beacons and establishing a fingerprint library; calculating the fingerprint library positioning coordinates of the test point at the current moment according to the fingerprint library and calculating the Euclidean distance, and applying a three-point positioning method to calculate the three-point positioning coordinates of the test point at the current moment; obtaining a first weight according to the Euclidean distance, and combining the fingerprint library positioning coordinates and the three-point positioning coordinates according to the first weight to obtain a combined first positioning coordinate; and correcting the first positioning coordinate according to inertial navigation to obtain a final positioning coordinate.

[0007] In an optional manner, obtaining the first weight according to the Euclidean distance includes: obtaining the first weight by applying different calculation methods according to the Euclidean distance.

[0008] In an optional manner, combining the fingerprint library positioning coordinates and the three-point positioning coordinates according to the first weight to obtain the combined first positioning coordinates includes: determining the weight corresponding to the fingerprint library positioning coordinates and the weight corresponding to the three-point positioning coordinates according to the first weight; performing weighted calculation according to the fingerprint library positioning coordinates, the three-point positioning coordinates and the corresponding weights to obtain the combined first positioning coordinates.

[0009] In an optional manner, the first positioning coordinates are corrected according to inertial navigation to obtain the final positioning coordinates, including: determining whether there are positioning coordinates at the previous moment; if so, calculating whether the difference between the inertial navigation of the previous moment and the current time period and the distance between the positioning coordinates at the previous moment and the positioning coordinates at the current time exceeds a threshold; if it exceeds the threshold, adjusting and updating the first positioning coordinates of the test point at the current moment; if it does not exceed the threshold, or there are no positioning coordinates at the previous moment, outputting the first positioning coordinates as the positioning result of the test point at the current moment.

[0010] In an optional manner, before determining whether there are positioning coordinates at the previous moment, the step includes: determining whether there is a re-positioning mark; if yes, clearing the re-positioning mark, and using the first positioning coordinates as the final positioning result of the test point at the current moment; if not, executing the step of determining whether there are positioning coordinates at the previous moment.

[0011] In an optional manner, the adjustment and update of the first positioning coordinates of the test point at the current moment includes: determining whether the number of returns exceeds a threshold, if not, updating the first weight, returning to the step of combining the fingerprint library positioning coordinates and the three-point positioning coordinates according to the first weight to obtain the combined first positioning coordinates, and calculating the number of returns; if the number of returns exceeds a preset number, adding a repositioning mark; and taking the positioning coordinates at the previous moment plus the difference calculated by the inertial navigation as the positioning result.

[0012] In an optional manner, the method further includes: determining whether the pedestrian is moving, or whether the time of inactivity exceeds a threshold; if the pedestrian is moving, or the time of inactivity exceeds the threshold, returning to the steps of calculating the fingerprint library positioning coordinates of the test point at the current moment according to the fingerprint library and calculating the Euclidean distance, and applying the three-point positioning method to calculate the three-point positioning coordinates of the test point at the current moment to re-position at the current moment; otherwise, directly outputting the positioning coordinates of the previous moment.

[0013] According to another aspect of an embodiment of the present invention, a positioning device for dynamically weighting multi-source data is provided, the device comprising: a data acquisition unit, used to obtain the positions of multiple beacons near a test point, collect signal characteristic values ​​of the multiple beacons and establish a fingerprint library; a first positioning unit, used to calculate the fingerprint library positioning coordinates of the test point at the current moment according to the fingerprint library and calculate the Euclidean distance, and calculate the three-point positioning coordinates of the test point at the current moment using a three-point positioning method; a combined positioning unit, used to obtain a first weight value according to the Euclidean distance, and combine the fingerprint library positioning coordinates and the three-point positioning coordinates according to the first weight value to obtain a combined first positioning coordinate; a positioning correction unit, used to correct the first positioning coordinate according to inertial navigation to obtain a final positioning coordinate.

[0014] According to another aspect of an embodiment of the present invention, there is provided a computing device, comprising: a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface communicate with each other via the communication bus;

[0015] The memory is used to store at least one executable instruction, and the executable instruction enables the processor to execute the steps of the above-mentioned multi-source data dynamic weighted positioning method.

[0016] According to another aspect of the embodiments of the present invention, a computer storage medium is provided, wherein at least one executable instruction is stored in the storage medium, and the executable instruction enables the processor to execute the steps of the above-mentioned multi-source data dynamic weighted positioning method.

[0017] The embodiment of the present invention obtains the positions of multiple beacons near a test point, collects signal characteristic values ​​of the multiple beacons and establishes a fingerprint library; calculates the fingerprint library positioning coordinates of the test point at the current moment according to the fingerprint library and calculates the Euclidean distance, and applies a three-point positioning method to calculate the three-point positioning coordinates of the test point at the current moment; obtains a first weight according to the Euclidean distance, and combines the fingerprint library positioning coordinates and the three-point positioning coordinates according to the first weight to obtain the combined first positioning coordinates; corrects the first positioning coordinates according to inertial navigation to obtain the final positioning coordinates. By jointly using the three-point positioning and fingerprint library weighted positioning technology, the problem of three-point positioning being seriously affected by fluctuations and external interference can be solved. By filtering out abnormal points through inertial navigation in a short time, the problem of error accumulation due to a long time is avoided, and the positioning accuracy can be improved.

[0018] The above description is only an overview of the technical solution of the embodiment of the present invention. In order to more clearly understand the technical means of the embodiment of the present invention, it can be implemented according to the contents of the specification. In order to make the above and other purposes, features and advantages of the embodiment of the present invention more obvious and easy to understand, the specific implementation mode of the present invention is specifically listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present invention. Moreover, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings:

[0020] Figure 1 A schematic diagram of the process of a multi-source data dynamic weighted positioning method provided by an embodiment of the present invention is shown;

[0021] Figure 2 A schematic diagram of another multi-source data dynamic weighted positioning method provided by an embodiment of the present invention is shown;

[0022] Figure 3 A schematic diagram of the structure of a positioning device for dynamically weighting multi-source data provided by an embodiment of the present invention is shown;

[0023] Figure 4 A schematic diagram of the structure of a computing device provided by an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0024] The exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present invention are shown in the accompanying drawings, it should be understood that the present invention can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided in order to enable a more thorough understanding of the present invention and to enable the scope of the present invention to be fully communicated to those skilled in the art.

[0025] Figure 1 FIG. 1 is a flow chart of a method for positioning a multi-source data dynamically weighted according to an embodiment of the present invention. The method for positioning a multi-source data dynamically weighted according to an embodiment of the present invention is applied to a server, such as Figure 1 As shown, the positioning method of dynamic weighting of multi-source data includes:

[0026] Step S11: obtaining the positions of multiple beacons near the test point, collecting signal feature values ​​of the multiple beacons and establishing a fingerprint library.

[0027] In an embodiment of the present invention, preliminary preparations for indoor positioning are performed to obtain the beacon positions near the test site, specifically the beacon positions in the indoor space within a certain range of the test point (the beacon may refer to a base station, Bluetooth, WIFI, etc.). The test point collects signal characteristic values ​​of multiple locations, and generates a fingerprint library based on the collected signal characteristic value information data. If there are multiple types of beacons, such as base stations, Bluetooth, WIFI, etc., they can be sorted or marked when generating the fingerprint library. The test point also receives multiple beacon signals. Multiple beacons, such as base stations, Bluetooth, and WIFI, generate a signal characteristic value fingerprint library. When calculating the fingerprint library, different weights can be given according to different types, and weighted calculations can be performed to achieve combined positioning of multiple devices.

[0028] Step S12: Calculate the fingerprint library positioning coordinates of the test point at the current moment according to the fingerprint library and calculate the Euclidean distance, and calculate the three-point positioning coordinates of the test point at the current moment by applying a three-point positioning method.

[0029] In an embodiment of the present invention, the fingerprint library positioning coordinates of the test point at the current moment are weighted by different beacons according to the fingerprint library; and the Euclidean distance between the fingerprint library positioning coordinates and the actual position of the test point is calculated. Among them, the fingerprint library positioning adopts WKNN fingerprint library positioning. At the same time, the three-point positioning method is used to calculate the three-point positioning coordinates of the test point at the current moment.

[0030] Step S13: obtaining a first weight according to the Euclidean distance, and combining the fingerprint database positioning coordinates and the three-point positioning coordinates according to the first weight to obtain a combined first positioning coordinate.

[0031] In the embodiment of the present invention, different calculation methods can be applied to obtain the first weight according to the previously calculated Euclidean distance. The calculation method is not fixed to obtain different first weights, so as to facilitate dynamic updating of the first weight during recalculation.

[0032] In step S13, the weight corresponding to the fingerprint library positioning coordinates and the weight corresponding to the three-point positioning coordinates are determined according to the first weight; weighted calculation is performed according to the fingerprint library positioning coordinates, the three-point positioning coordinates and the corresponding weights to obtain the combined first positioning coordinates. When the Euclidean distance between the test point and the k nearest neighbor points is closer, the WKNN fingerprint library positioning method is more reliable and has a higher confidence level. It should be given a higher weight, and the weight given to the three-point positioning coordinates is correspondingly lower. The control of the dynamic weight should be controlled between 0.5-1. In the weighted combined positioning of WKNN fingerprint library positioning and three-point positioning, the added first weight can be dynamically calculated by listing multiple formulas based on the Euclidean distance calculated in the WKNN fingerprint library, the maximum Euclidean distance, the maximum signal strength of the three-point positioning, the average signal strength, etc. The formula can be dynamically replaced when the weighted positioning results of the WKNN fingerprint library and the three-point positioning are checked by subsequent inertial navigation and exceed the threshold.

[0033] The embodiment of the present invention uses three-point positioning and WKNN fingerprint library weighted positioning technology in combination, which can solve the problem that three-point positioning is seriously affected by fluctuations and external interference, and improve positioning accuracy.

[0034] Step S14: Correct the first positioning coordinates according to inertial navigation to obtain final positioning coordinates.

[0035] In an embodiment of the present invention, it is determined whether there are positioning coordinates at the last moment; if there are, the difference between the distance between the inertial navigation of the last moment and the current time period and the positioning coordinates at the last moment and the positioning coordinates at the current time is calculated to see whether it exceeds a threshold value. If it exceeds the threshold value, the first positioning coordinates of the test point at the current moment are adjusted and updated; if it does not exceed the threshold value, or there are no positioning coordinates at the last moment, the first positioning coordinates are output as the positioning result of the test point at the current moment. Specifically, the first distance between the last moment and the current moment is calculated according to the inertial navigation, and the difference between the first distance and the second distance is calculated according to the second distance between the first positioning coordinates obtained at the last moment and the first positioning coordinates obtained at the current time. If the difference exceeds the threshold value, it is necessary to adjust and update the first positioning coordinates of the test point at the current moment. If there are no positioning coordinates at the last moment or the difference does not exceed the threshold value, the first positioning coordinates calculated in step S13 are determined as the positioning result at the current moment.

[0036] Before the step of determining whether there are positioning coordinates at the previous moment, determine whether there is a re-positioning mark; if yes, clear the re-positioning mark, and use the first positioning coordinates as the final positioning result of the test point at the current moment; if not, execute the step of determining whether there are positioning coordinates at the previous moment.

[0037] In an embodiment of the present invention, when adjusting and updating the first positioning coordinates of the test point at the current moment, it is determined whether the number of returns exceeds the threshold. If not, the first weight is updated, and the step of combining the fingerprint library positioning coordinates and the three-point positioning coordinates according to the first weight is returned to obtain the combined first positioning coordinates, and the number of returns is calculated. Among them, the updated first weight is obtained by applying different calculation methods according to the Euclidean distance. After weighted calculation of the fingerprint library positioning coordinates and the three-point positioning coordinates is performed according to the first weight each time, the weight calculated for the same test point is recorded, and the weight is dynamically replaced when recalculating. If the number of returns exceeds the preset number, a repositioning mark is added; the positioning coordinates at the previous moment plus the difference calculated by the inertial navigation are used as the positioning result. The preset number of times can be set as needed and is not limited here. The embodiment of the present invention verifies the error of the weighted average result of the WKNN algorithm and the three-point positioning algorithm through the inertial navigation results in a short period of time, and repositions when the error exceeds the error threshold. Repositioning can adjust the weighted first weight of the WKNN algorithm and the three-point positioning algorithm, such as unidirectional increase or decrease, or calculate the first weight according to some data of the WKNN algorithm and the three-point positioning algorithm, such as: 1 / (1+Euclidean distance / maximum Euclidean distance), where the Euclidean distance is the Euclidean distance of the current WKNN positioning result, and the maximum Euclidean distance is the maximum value of all Euclidean distances. The specific use of increasing, decreasing, or specifying an array can be adjusted according to actual conditions. The three-point positioning and the weighted positioning of the WKNN fingerprint library are verified by the inertial navigation information in a short period of time. If a certain threshold is exceeded, the first weight is dynamically adjusted according to the pre-set formula or imported array to filter out abnormal points and improve the average positioning accuracy. The inertial navigation in a short period of time also avoids the problem of error accumulation due to a long time.

[0038] The embodiment of the present invention is based on the weighted combined positioning of the WKNN fingerprint library and three-point positioning, and removes abnormal points through inertial navigation screening. By performing multiple screenings, the probability of screening out abnormal points and real abnormalities is increased; the result of the previous positioning plus the result of inertia can be used to replace the abnormal point, thereby improving the average positioning accuracy. When the fingerprint library is not collected in advance, positioning combining three-point positioning and inertial navigation can be performed at the same time. Similarly, when the base station coordinates are not obtained, positioning combining fingerprint library positioning and inertial navigation can be performed.

[0039] In an embodiment of the present invention, after obtaining the positioning result at the current moment, it is determined whether the pedestrian (i.e., the test point) is moving, or whether the time of inactivity exceeds a threshold. If the pedestrian is moving, or the time of inactivity exceeds a threshold, the steps of calculating the fingerprint library positioning coordinates of the test point at the current moment according to the fingerprint library and calculating the Euclidean distance, and applying the three-point positioning method to calculate the three-point positioning coordinates of the test point at the current moment are returned to re-position the current moment; otherwise, the positioning coordinates of the previous moment are directly output. That is, if the pedestrian is moving or has not moved for too long, it is necessary to re-position the test point where the pedestrian is located; otherwise, it is not necessary to re-position, and the positioning coordinates of the previous moment can be directly output.

[0040] The complete multi-source data dynamic weighted positioning method of the embodiment of the present invention is as follows Figure 2 As shown, including:

[0041] Step 200: Preliminary preparation for indoor positioning.

[0042] Specifically, the beacon positions in a certain range of indoor space are tested, the signal characteristic values ​​of multiple positions are collected at the test points, and a fingerprint library is generated according to the collected signal characteristic value information data.

[0043] Step 201: The test point receives multiple beacon signals.

[0044] The test point receives beacon signals of beacons in a certain range of indoor spaces.

[0045] Step 202: Calculate the WKNN fingerprint library positioning coordinates of the test point based on the collected fingerprint library, perform weighting according to different beacons, and record the calculated Euclidean distance.

[0046] The fingerprint library positioning coordinates of the test point at the current moment are calculated by weighting different beacons according to the fingerprint library, and the Euclidean distance between the fingerprint library positioning coordinates and the actual position of the test point is calculated at the same time.

[0047] Step 203: Calculate the three-point positioning coordinates of the test point.

[0048] Specifically, a three-point positioning method is used to calculate the three-point positioning coordinates of the test point at the current moment.

[0049] Step 204: Calculate the first positioning coordinates by adding weights to the fingerprint library positioning coordinates and the three-point positioning of the test point according to the Euclidean distance.

[0050] A first weight is obtained according to the Euclidean distance, and the fingerprint database positioning coordinates and the three-point positioning coordinates are combined according to the first weight to obtain a combined first positioning coordinate.

[0051] Step 205: Determine whether there is a relocation mark. If yes, execute step 207; if no, execute step 206.

[0052] If there is a repositioning mark, it means that the first positioning coordinates were adjusted according to inertial navigation at the last moment.

[0053] Step 206: Determine whether there is a positioning coordinate at the last moment. If yes, execute step 209; if no, execute step 208.

[0054] Step 207: Clear the relocation flag and then execute step 208.

[0055] Step 208: Output the first positioning coordinates as the positioning result, and then jump to step 214.

[0056] That is, the first positioning coordinates calculated in step 204 are output as the positioning result of the test point at the current moment.

[0057] Step 209: Determine whether the difference between the inertial navigation of the last moment and the current time period and the distance between the last moment positioning coordinate and the current time positioning coordinate exceeds a threshold. If yes, execute step 210; if no, execute step 208.

[0058] If the difference between the inertial navigation of the last moment and the current time period and the distance between the last moment positioning coordinate and the current time positioning coordinate exceeds the threshold, it indicates that the first positioning coordinate data calculated at the current moment is abnormal and needs to be adjusted. Otherwise, it indicates that the first positioning coordinate data calculated at the current moment in step 204 is normal, and then step 208 is executed to directly output the first positioning coordinate calculated in step 204 as the positioning result of the test point at the current moment.

[0059] Step 210: Determine whether the number of returns exceeds a preset number. If yes, execute step 212; if no, execute step 211.

[0060] It is determined whether the number of times of re-adjusting the first positioning coordinates in step 204 exceeds the preset number. If not, the first weight is updated, and the process returns to step 204 to recalculate the first positioning coordinates according to the updated first weight, and the process repeats in this way until the updated first positioning coordinate data is normal, or the number of returns exceeds the preset number. If the number of returns exceeds the preset number, step 212 is executed.

[0061] Step 211: Update the first weight and then return to step 204.

[0062] Step 212: Add a relocation mark.

[0063] If the number of returns exceeds the preset number, it is necessary to apply inertial navigation to correct the first positioning coordinates calculated in step 204, so a repositioning mark is added.

[0064] Step 213: Output the difference between the last moment positioning coordinate and the inertial navigation calculation as the positioning result. Then execute step 214.

[0065] The method of using inertial navigation to correct the first positioning coordinates calculated in step 204 is: outputting the positioning coordinates at the last moment plus the difference calculated by the inertial navigation as the positioning result.

[0066] At this point, the positioning of the test point at the current moment is completed.

[0067] Step 214: Determine whether the pedestrian is moving, or whether the inactivity time exceeds a threshold. If yes, return to step 202; if no, execute step 215.

[0068] Determine whether the pedestrian (test point) is moving based on inertial navigation. If the result of inertial navigation changes, it means that the pedestrian is moving, otherwise the pedestrian is not moving. If the pedestrian is moving, or the time when the pedestrian is not moving exceeds the threshold, the test point needs to be relocated, and return to step 202. Otherwise, the test point does not need to be relocated.

[0069] Step 215: Output the positioning coordinates of the last moment.

[0070] If the pedestrian's inactivity time does not exceed the threshold, it means that there is no need to reposition the test point, and the positioning coordinates of the previous moment can be directly output as the positioning result of the current moment.

[0071] The embodiment of the present invention obtains the positions of multiple beacons near a test point, collects signal characteristic values ​​of the multiple beacons and establishes a fingerprint library; calculates the fingerprint library positioning coordinates of the test point at the current moment according to the fingerprint library and calculates the Euclidean distance, and applies a three-point positioning method to calculate the three-point positioning coordinates of the test point at the current moment; obtains a first weight according to the Euclidean distance, and combines the fingerprint library positioning coordinates and the three-point positioning coordinates according to the first weight to obtain the combined first positioning coordinates; corrects the first positioning coordinates according to inertial navigation to obtain the final positioning coordinates. By jointly using the three-point positioning and fingerprint library weighted positioning technology, the problem of three-point positioning being seriously affected by fluctuations and external interference can be solved. By filtering out abnormal points through inertial navigation in a short time, the problem of error accumulation due to a long time is avoided, and the positioning accuracy can be improved.

[0072] Figure 3 FIG. 1 is a schematic diagram showing the structure of a positioning device for dynamically weighting multi-source data according to an embodiment of the present invention. Figure 3As shown, the multi-source data dynamic weighted positioning device includes: a data acquisition unit 301, a first positioning unit 302, a combined positioning unit 303 and a positioning correction unit 304. Among them:

[0073] The data acquisition unit 301 is used to obtain the positions of multiple beacons near the test point, collect signal characteristic values ​​of the multiple beacons and establish a fingerprint library; the first positioning unit 302 is used to calculate the fingerprint library positioning coordinates of the test point at the current moment according to the fingerprint library and calculate the Euclidean distance, and apply the three-point positioning method to calculate the three-point positioning coordinates of the test point at the current moment; the combined positioning unit 303 is used to obtain a first weight according to the Euclidean distance, and combine the fingerprint library positioning coordinates and the three-point positioning coordinates according to the first weight to obtain the combined first positioning coordinates; the positioning correction unit 304 is used to correct the first positioning coordinates according to inertial navigation to obtain the final positioning coordinates.

[0074] In an optional manner, the positioning unit 303 is used to: obtain the first weight by applying different calculation methods according to the Euclidean distance.

[0075] In an optional manner, the combined positioning unit 303 is used to: determine the weight corresponding to the fingerprint library positioning coordinates and the weight corresponding to the three-point positioning coordinates according to the first weight; perform weighted calculation according to the fingerprint library positioning coordinates, the three-point positioning coordinates and the corresponding weights to obtain the combined first positioning coordinates.

[0076] In an optional manner, the positioning correction unit 304 is used to: determine whether there are positioning coordinates at the previous moment; if so, calculate whether the difference between the inertial navigation of the previous moment and the current time period and the distance between the positioning coordinates at the previous moment and the positioning coordinates at the current time exceeds a threshold; if it exceeds the threshold, adjust and update the first positioning coordinates of the test point at the current moment; if it does not exceed the threshold, or there are no positioning coordinates at the previous moment, output the first positioning coordinates as the positioning result of the test point at the current moment.

[0077] In an optional manner, the positioning correction unit 304 is used to: determine whether there is a re-positioning mark; if so, clear the re-positioning mark, and use the first positioning coordinates as the final positioning result of the test point at the current moment; if not, execute the step of determining whether there are positioning coordinates at the previous moment.

[0078] In an optional manner, the positioning correction unit 304 is used to: determine whether the number of returns exceeds a threshold, if not, update the first weight, return to the step of combining the fingerprint library positioning coordinates and the three-point positioning coordinates according to the first weight to obtain the combined first positioning coordinates, and calculate the number of returns; if the number of returns exceeds a preset number, add a repositioning mark; and take the positioning coordinates at the previous moment plus the difference calculated by the inertial navigation as the positioning result.

[0079] In an optional manner, the positioning correction unit 304 is also used to: determine whether the pedestrian is moving, or whether the time of inactivity exceeds a threshold; if the pedestrian is moving, or the time of inactivity exceeds the threshold, return to the steps of calculating the fingerprint library positioning coordinates of the test point at the current moment according to the fingerprint library and calculating the Euclidean distance, and applying the three-point positioning method to calculate the three-point positioning coordinates of the test point at the current moment to re-position at the current moment; otherwise, directly output the positioning coordinates of the previous moment.

[0080] The embodiment of the present invention obtains the positions of multiple beacons near a test point, collects signal characteristic values ​​of the multiple beacons and establishes a fingerprint library; calculates the fingerprint library positioning coordinates of the test point at the current moment according to the fingerprint library and calculates the Euclidean distance, and applies a three-point positioning method to calculate the three-point positioning coordinates of the test point at the current moment; obtains a first weight according to the Euclidean distance, and combines the fingerprint library positioning coordinates and the three-point positioning coordinates according to the first weight to obtain the combined first positioning coordinates; corrects the first positioning coordinates according to inertial navigation to obtain the final positioning coordinates. By jointly using the three-point positioning and fingerprint library weighted positioning technology, the problem of three-point positioning being seriously affected by fluctuations and external interference can be solved. By filtering out abnormal points through inertial navigation in a short time, the problem of error accumulation due to a long time is avoided, and the positioning accuracy can be improved.

[0081] An embodiment of the present invention provides a non-volatile computer storage medium, wherein the computer storage medium stores at least one executable instruction, and the computer executable instruction can execute the multi-source data dynamic weighted positioning method in any of the above method embodiments.

[0082] The executable instructions may be used to cause the processor to perform the following operations:

[0083] Obtaining the positions of multiple beacons near the test point, collecting signal characteristic values ​​of the multiple beacons and establishing a fingerprint library;

[0084] Calculate the fingerprint library positioning coordinates of the test point at the current moment according to the fingerprint library and calculate the Euclidean distance, and calculate the three-point positioning coordinates of the test point at the current moment by applying a three-point positioning method;

[0085] Obtaining a first weight according to the Euclidean distance, and combining the fingerprint library positioning coordinates and the three-point positioning coordinates according to the first weight to obtain a combined first positioning coordinate;

[0086] The first positioning coordinates are corrected according to inertial navigation to obtain final positioning coordinates.

[0087] In an optional manner, the executable instruction causes the processor to perform the following operations:

[0088] Different calculation methods are applied according to the Euclidean distance to obtain the first weight.

[0089] In an optional manner, the executable instruction causes the processor to perform the following operations:

[0090] Determine, according to the first weight, a weight corresponding to the fingerprint library positioning coordinates and a weight corresponding to the three-point positioning coordinates;

[0091] A weighted calculation is performed according to the fingerprint library positioning coordinates, the three-point positioning coordinates and corresponding weights to obtain the combined first positioning coordinates.

[0092] In an optional manner, the executable instruction causes the processor to perform the following operations:

[0093] Determine whether there is positioning coordinates at the last moment;

[0094] If yes, then calculate whether the difference between the inertial navigation at the last moment and the current time period and the distance between the positioning coordinates at the last moment and the positioning coordinates at the current time exceeds a threshold; if it exceeds the threshold, adjust and update the first positioning coordinates of the test point at the current moment;

[0095] If the threshold is not exceeded, or there is no positioning coordinate at the previous moment, the first positioning coordinate is output as the positioning result of the test point at the current moment.

[0096] In an optional manner, the executable instruction causes the processor to perform the following operations:

[0097] Determine whether there is a relocation mark;

[0098] If yes, clear the repositioning flag, and use the first positioning coordinates as the final positioning result of the test point at the current moment;

[0099] If not, then the step of determining whether there are positioning coordinates at the previous moment is executed.

[0100] In an optional manner, the executable instruction causes the processor to perform the following operations:

[0101] Determine whether the number of returns exceeds a threshold, if not, update the first weight, return to the step of combining the fingerprint library positioning coordinates and the three-point positioning coordinates according to the first weight to obtain the combined first positioning coordinates, and calculate the number of returns;

[0102] If the number of returns exceeds the preset number, add a relocation mark;

[0103] The difference between the last moment positioning coordinate and the inertial navigation calculation is taken as the positioning result.

[0104] In an optional manner, the executable instruction causes the processor to perform the following operations:

[0105] Determine whether the pedestrian is moving, or whether the time of inactivity exceeds a threshold;

[0106] If the pedestrian moves, or the time of not moving exceeds the threshold, then return to the steps of calculating the fingerprint library positioning coordinates of the test point at the current moment according to the fingerprint library and calculating the Euclidean distance, and applying the three-point positioning method to calculate the three-point positioning coordinates of the test point at the current moment to re-position at the current moment;

[0107] Otherwise, directly output the positioning coordinates of the previous moment.

[0108] The embodiment of the present invention obtains the positions of multiple beacons near a test point, collects signal characteristic values ​​of the multiple beacons and establishes a fingerprint library; calculates the fingerprint library positioning coordinates of the test point at the current moment according to the fingerprint library and calculates the Euclidean distance, and applies a three-point positioning method to calculate the three-point positioning coordinates of the test point at the current moment; obtains a first weight according to the Euclidean distance, and combines the fingerprint library positioning coordinates and the three-point positioning coordinates according to the first weight to obtain the combined first positioning coordinates; corrects the first positioning coordinates according to inertial navigation to obtain the final positioning coordinates. By jointly using the three-point positioning and fingerprint library weighted positioning technology, the problem of three-point positioning being seriously affected by fluctuations and external interference can be solved. By filtering out abnormal points through inertial navigation in a short time, the problem of error accumulation due to a long time is avoided, and the positioning accuracy can be improved.

[0109] An embodiment of the present invention provides a computer program product, which includes a computer program stored on a computer storage medium, and the computer program includes program instructions. When the program instructions are executed by a computer, the computer executes the multi-source data dynamic weighted positioning method in any of the above method embodiments.

[0110] The executable instructions may be used to cause the processor to perform the following operations:

[0111] Obtaining the positions of multiple beacons near the test point, collecting signal characteristic values ​​of the multiple beacons and establishing a fingerprint library;

[0112] Calculate the fingerprint library positioning coordinates of the test point at the current moment according to the fingerprint library and calculate the Euclidean distance, and calculate the three-point positioning coordinates of the test point at the current moment by applying a three-point positioning method;

[0113] Obtaining a first weight according to the Euclidean distance, and combining the fingerprint library positioning coordinates and the three-point positioning coordinates according to the first weight to obtain a combined first positioning coordinate;

[0114] The first positioning coordinates are corrected according to inertial navigation to obtain final positioning coordinates.

[0115] In an optional manner, the executable instruction causes the processor to perform the following operations:

[0116] Different calculation methods are applied according to the Euclidean distance to obtain the first weight.

[0117] In an optional manner, the executable instruction causes the processor to perform the following operations:

[0118] Determine, according to the first weight, a weight corresponding to the fingerprint library positioning coordinates and a weight corresponding to the three-point positioning coordinates;

[0119] A weighted calculation is performed according to the fingerprint library positioning coordinates, the three-point positioning coordinates and corresponding weights to obtain the combined first positioning coordinates.

[0120] In an optional manner, the executable instruction causes the processor to perform the following operations:

[0121] Determine whether there is positioning coordinates at the last moment;

[0122] If yes, then calculate whether the difference between the inertial navigation at the last moment and the current time period and the distance between the positioning coordinates at the last moment and the positioning coordinates at the current time exceeds a threshold; if it exceeds the threshold, adjust and update the first positioning coordinates of the test point at the current moment;

[0123] If the threshold is not exceeded, or there is no positioning coordinate at the previous moment, the first positioning coordinate is output as the positioning result of the test point at the current moment.

[0124] In an optional manner, the executable instruction causes the processor to perform the following operations:

[0125] Determine whether there is a relocation mark;

[0126] If yes, clear the repositioning flag, and use the first positioning coordinates as the final positioning result of the test point at the current moment;

[0127] If not, then the step of determining whether there are positioning coordinates at the previous moment is executed.

[0128] In an optional manner, the executable instruction causes the processor to perform the following operations:

[0129] Determine whether the number of returns exceeds a threshold, if not, update the first weight, return to the step of combining the fingerprint library positioning coordinates and the three-point positioning coordinates according to the first weight to obtain the combined first positioning coordinates, and calculate the number of returns;

[0130] If the number of returns exceeds the preset number, add a relocation mark;

[0131] The difference between the last moment positioning coordinate and the inertial navigation calculation is taken as the positioning result.

[0132] In an optional manner, the executable instruction causes the processor to perform the following operations:

[0133] Determine whether the pedestrian is moving, or whether the time of inactivity exceeds a threshold;

[0134] If the pedestrian moves, or the time of not moving exceeds the threshold, then return to the steps of calculating the fingerprint library positioning coordinates of the test point at the current moment according to the fingerprint library and calculating the Euclidean distance, and applying the three-point positioning method to calculate the three-point positioning coordinates of the test point at the current moment to re-position at the current moment;

[0135] Otherwise, directly output the positioning coordinates of the previous moment.

[0136] The embodiment of the present invention obtains the positions of multiple beacons near a test point, collects signal characteristic values ​​of the multiple beacons and establishes a fingerprint library; calculates the fingerprint library positioning coordinates of the test point at the current moment according to the fingerprint library and calculates the Euclidean distance, and applies a three-point positioning method to calculate the three-point positioning coordinates of the test point at the current moment; obtains a first weight according to the Euclidean distance, and combines the fingerprint library positioning coordinates and the three-point positioning coordinates according to the first weight to obtain the combined first positioning coordinates; corrects the first positioning coordinates according to inertial navigation to obtain the final positioning coordinates. By jointly using the three-point positioning and fingerprint library weighted positioning technology, the problem of three-point positioning being seriously affected by fluctuations and external interference can be solved. By filtering out abnormal points through inertial navigation in a short time, the problem of error accumulation due to a long time is avoided, and the positioning accuracy can be improved.

[0137] Figure 4A schematic diagram of the structure of a computing device provided by an embodiment of the present invention is shown, and the specific embodiment of the present invention does not limit the specific implementation of the device.

[0138] like Figure 4 As shown, the computing device may include: a processor (processor) 402 , a communications interface (Communications Interface) 404 , a memory (memory) 406 , and a communication bus 408 .

[0139] The processor 402, the communication interface 404, and the memory 406 communicate with each other via the communication bus 408. The communication interface 404 is used to communicate with other devices such as a client or other server network elements. The processor 402 is used to execute the program 410, which can specifically execute the relevant steps in the above multi-source data dynamic weighted positioning method embodiment.

[0140] Specifically, the program 410 may include program codes, which include computer operation instructions.

[0141] The processor 402 may be a central processing unit (CPU), or an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present invention. The one or more processors included in the device may be processors of the same type, such as one or more CPUs; or may be processors of different types, such as one or more CPUs and one or more ASICs.

[0142] The memory 406 is used to store the program 410. The memory 406 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0143] The program 410 may be specifically configured to enable the processor 402 to perform the following operations:

[0144] Obtaining the positions of multiple beacons near the test point, collecting signal characteristic values ​​of the multiple beacons and establishing a fingerprint library;

[0145] Calculate the fingerprint library positioning coordinates of the test point at the current moment according to the fingerprint library and calculate the Euclidean distance, and calculate the three-point positioning coordinates of the test point at the current moment by applying a three-point positioning method;

[0146] Obtaining a first weight according to the Euclidean distance, and combining the fingerprint library positioning coordinates and the three-point positioning coordinates according to the first weight to obtain a combined first positioning coordinate;

[0147] The first positioning coordinates are corrected according to inertial navigation to obtain final positioning coordinates.

[0148] In an optional manner, the program 410 enables the processor to perform the following operations:

[0149] Different calculation methods are applied according to the Euclidean distance to obtain the first weight.

[0150] In an optional manner, the program 410 enables the processor to perform the following operations:

[0151] Determine, according to the first weight, a weight corresponding to the fingerprint library positioning coordinates and a weight corresponding to the three-point positioning coordinates;

[0152] A weighted calculation is performed according to the fingerprint library positioning coordinates, the three-point positioning coordinates and corresponding weights to obtain the combined first positioning coordinates.

[0153] In an optional manner, the program 410 enables the processor to perform the following operations:

[0154] Determine whether there is positioning coordinates at the last moment;

[0155] If yes, then calculate whether the difference between the inertial navigation at the last moment and the current time period and the distance between the positioning coordinates at the last moment and the positioning coordinates at the current time exceeds a threshold; if it exceeds the threshold, adjust and update the first positioning coordinates of the test point at the current moment;

[0156] If the threshold is not exceeded, or there is no positioning coordinate at the previous moment, the first positioning coordinate is output as the positioning result of the test point at the current moment.

[0157] In an optional manner, the program 410 enables the processor to perform the following operations:

[0158] Determine whether there is a relocation mark;

[0159] If yes, clear the repositioning flag, and use the first positioning coordinates as the final positioning result of the test point at the current moment;

[0160] If not, then the step of determining whether there are positioning coordinates at the previous moment is executed.

[0161] In an optional manner, the program 410 enables the processor to perform the following operations:

[0162] Determine whether the number of returns exceeds a threshold, if not, update the first weight, return to the step of combining the fingerprint library positioning coordinates and the three-point positioning coordinates according to the first weight to obtain the combined first positioning coordinates, and calculate the number of returns;

[0163] If the number of returns exceeds the preset number, add a relocation mark;

[0164] The difference between the last moment positioning coordinate and the inertial navigation calculation is taken as the positioning result.

[0165] In an optional manner, the program 410 enables the processor to perform the following operations:

[0166] Determine whether the pedestrian is moving, or whether the time of inactivity exceeds a threshold;

[0167] If the pedestrian moves, or the time of not moving exceeds the threshold, then return to the steps of calculating the fingerprint library positioning coordinates of the test point at the current moment according to the fingerprint library and calculating the Euclidean distance, and applying the three-point positioning method to calculate the three-point positioning coordinates of the test point at the current moment to re-position at the current moment;

[0168] Otherwise, directly output the positioning coordinates of the previous moment.

[0169] The embodiment of the present invention obtains the positions of multiple beacons near a test point, collects signal characteristic values ​​of the multiple beacons and establishes a fingerprint library; calculates the fingerprint library positioning coordinates of the test point at the current moment according to the fingerprint library and calculates the Euclidean distance, and applies a three-point positioning method to calculate the three-point positioning coordinates of the test point at the current moment; obtains a first weight according to the Euclidean distance, and combines the fingerprint library positioning coordinates and the three-point positioning coordinates according to the first weight to obtain the combined first positioning coordinates; corrects the first positioning coordinates according to inertial navigation to obtain the final positioning coordinates. By jointly using the three-point positioning and fingerprint library weighted positioning technology, the problem of three-point positioning being seriously affected by fluctuations and external interference can be solved. By filtering out abnormal points through inertial navigation in a short time, the problem of error accumulation due to a long time is avoided, and the positioning accuracy can be improved.

[0170] The algorithm or display provided herein is not inherently related to any particular computer, virtual system or other equipment. Various general purpose systems can also be used together with the teachings based on this. According to the above description, it is obvious to construct the structure required for this type of system. In addition, the embodiment of the present invention is not directed to any specific programming language yet. It should be understood that various programming languages ​​can be utilized to realize the content of the present invention described herein, and the description made to specific languages ​​above is for disclosing the best mode of the present invention.

[0171] In the description provided herein, a large number of specific details are described. However, it is understood that embodiments of the present invention can be practiced without these specific details. In some instances, well-known methods, structures and techniques are not shown in detail so as not to obscure the understanding of this description.

[0172] Similarly, it should be understood that in order to streamline the present invention and aid in understanding one or more of the various inventive aspects, in the above description of exemplary embodiments of the present invention, various features of the embodiments of the present invention are sometimes grouped together into a single embodiment, figure, or description thereof. However, this method of disclosure should not be interpreted as reflecting an intention that the claimed invention requires more features than those expressly recited in each claim.

[0173] Those skilled in the art will appreciate that the modules in the devices in the embodiments may be adaptively changed and arranged in one or more devices different from the embodiments. The modules or units or components in the embodiments may be combined into one module or unit or component, and in addition they may be divided into a plurality of submodules or subunits or subcomponents. Except that at least some of such features and / or processes or units are mutually exclusive, all features disclosed in this specification (including the accompanying claims, abstracts and drawings) and all processes or units of any method or device disclosed in this manner may be combined in any combination. Unless otherwise expressly stated, each feature disclosed in this specification (including the accompanying claims, abstracts and drawings) may be replaced by an alternative feature providing the same, equivalent or similar purpose.

[0174] It should be noted that the above embodiments illustrate the present invention rather than limit it, and that those skilled in the art may devise alternative embodiments without departing from the scope of the appended claims. In the claims, any reference symbol between brackets shall not be construed as a limitation on the claims. The word "comprising" does not exclude the presence of elements or steps not listed in the claims. The word "one" or "an" preceding an element does not exclude the presence of a plurality of such elements. The present invention may be implemented by means of hardware comprising a number of different elements and by means of a suitably programmed computer. In a unit claim enumerating a number of devices, several of these devices may be embodied by the same hardware item. The use of the words first, second, and third, etc. does not indicate any order. These words may be interpreted as names. The steps in the above embodiments, unless otherwise specified, should not be understood as limitations on the order of execution.

Claims

1. A positioning method for dynamically weighting multi-source data, characterized in that: The method comprises: Obtaining the positions of multiple beacons near the test point, collecting signal characteristic values ​​of the multiple beacons and establishing a fingerprint library; Calculate the fingerprint library positioning coordinates of the test point at the current moment according to the fingerprint library and calculate the Euclidean distance, and calculate the three-point positioning coordinates of the test point at the current moment by applying a three-point positioning method; Obtaining a first weight according to the Euclidean distance, and combining the fingerprint library positioning coordinates and the three-point positioning coordinates according to the first weight to obtain a combined first positioning coordinate; Correcting the first positioning coordinates according to inertial navigation to obtain final positioning coordinates includes: Determine whether there is a positioning coordinate at the previous moment, if so, calculate the first distance between the previous moment and the current moment according to the inertial navigation, calculate the difference between the first distance and the second distance according to the second distance between the first positioning coordinate obtained at the previous moment and the first positioning coordinate obtained at the current time, if the difference exceeds a threshold, adjust and update the first positioning coordinate of the test point at the current moment, if it does not exceed the threshold, or there is no positioning coordinate at the previous moment, output the first positioning coordinate as the positioning result of the test point at the current moment; wherein, when adjusting and updating, determine whether the number of returns exceeds a preset number, if not, update the first weight, return to the step of combining the fingerprint library positioning coordinates and the three-point positioning coordinates according to the first weight to obtain the combined first positioning coordinates, and calculate the number of returns, if the number of returns exceeds the preset number, add a re-positioning mark, and take the positioning coordinates at the previous moment plus the difference calculated by the inertial navigation as the positioning result; Among them, it also includes: Before determining whether there are positioning coordinates at the previous moment, determine whether there is a re-positioning mark; if yes, clear the re-positioning mark, and use the first positioning coordinates as the final positioning result of the test point at the current moment; if not, execute the step of determining whether there are positioning coordinates at the previous moment.

2. The method according to claim 1, characterized in that The obtaining of the first weight according to the Euclidean distance includes: Different calculation methods are applied according to the Euclidean distance to obtain the first weight.

3. The method according to claim 1, characterized in that The combining the fingerprint library positioning coordinates and the three-point positioning coordinates according to the first weight to obtain the combined first positioning coordinates includes: Determine, according to the first weight, a weight corresponding to the fingerprint library positioning coordinates and a weight corresponding to the three-point positioning coordinates; A weighted calculation is performed according to the fingerprint library positioning coordinates, the three-point positioning coordinates and corresponding weights to obtain the combined first positioning coordinates.

4. The method according to claim 1, characterized in that: The method further comprises: Determine whether the pedestrian is moving, or whether the time of inactivity exceeds a threshold; If the pedestrian moves, or the time of not moving exceeds the threshold, then return to the steps of calculating the fingerprint library positioning coordinates of the test point at the current moment according to the fingerprint library and calculating the Euclidean distance, and applying the three-point positioning method to calculate the three-point positioning coordinates of the test point at the current moment to re-position at the current moment; Otherwise, directly output the positioning coordinates of the previous moment.

5. A positioning device for dynamically weighting multi-source data, characterized in that: The device comprises: A data acquisition unit, used to obtain the positions of multiple beacons near the test point, collect signal characteristic values ​​of the multiple beacons and establish a fingerprint library; A first positioning unit, configured to calculate the fingerprint library positioning coordinates of the test point at the current moment according to the fingerprint library and calculate the Euclidean distance, and to calculate the three-point positioning coordinates of the test point at the current moment by applying a three-point positioning method; a combined positioning unit, configured to obtain a first weight according to the Euclidean distance, and combine the fingerprint library positioning coordinates and the three-point positioning coordinates according to the first weight to obtain a combined first positioning coordinate; The positioning correction unit is used to determine whether there is a positioning coordinate at the previous moment. If so, the first distance between the previous moment and the current moment is calculated according to the inertial navigation, and the difference between the first distance and the second distance is calculated according to the second distance between the first positioning coordinate obtained at the previous moment and the first positioning coordinate obtained at the current time. If the difference exceeds a threshold, the first positioning coordinate of the test point at the current moment is adjusted and updated. If it does not exceed the threshold, or there is no positioning coordinate at the previous moment, the first positioning coordinate is output as the positioning result of the test point at the current moment; wherein, when adjusting and updating, it is determined whether the number of returns exceeds a preset number. If not, Then the first weight is updated, and the step of combining the fingerprint library positioning coordinates and the three-point positioning coordinates according to the first weight to obtain the combined first positioning coordinates is returned, and the number of returns is calculated. If the number of returns exceeds the preset number, a repositioning mark is added, and the positioning coordinates at the previous moment plus the difference calculated by the inertial navigation is used as the positioning result; wherein, before determining whether there are positioning coordinates at the previous moment, determine whether there is a repositioning mark; if so, clear the repositioning mark, and use the first positioning coordinates as the final positioning result of the test point at the current moment; if not, execute the step of determining whether there are positioning coordinates at the previous moment.

6. A computing device, characterized in that include: A processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface communicate with each other via the communication bus; The memory is used to store at least one executable instruction, and the executable instruction enables the processor to execute the steps of the multi-source data dynamic weighted positioning method according to any one of claims 1-4.

7. A computer storage medium, characterized in that: The storage medium stores at least one executable instruction, and the executable instruction enables the processor to execute the steps of the multi-source data dynamic weighted positioning method according to any one of claims 1-4.

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