A wireless terminal distribution position calculation method, device, equipment and storage medium

Abstract

The application discloses a wireless terminal distribution position calculation method, device and equipment and a storage medium. Based on the idea of a Monte Carlo random sampling algorithm, sample points are randomly generated. Whether a sample point is a terminal existing point is judged by whether the RSSI information of the sample point satisfies a terminal condition. The strength grade table of the terminal condition is updated. Sample points are selected by randomly sampling with replacement in a selected area. Whether the sample satisfies the terminal condition is judged. The hit rate of the sample to the terminal condition is improved by resampling, so that a possible terminal distribution is obtained. The statistical value of all terminal distributions is used to realize the calculation of the accurate terminal position distribution. Through cyclic iteration, the random selection of the sample points, the judgment and the judgment process of the strength grade table are repeated, the number of the sample points is improved, and the data volume is improved. Whether the terminal exists is judged by a third threshold value, and the accuracy of the terminal position distribution is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of positioning tracking, in particular to a wireless terminal distribution position calculation method, device, equipment and storage medium. BACKGROUND

[0002] With the development of wireless communication technology, various wireless network devices are distributed in various scenes of daily life, and the terminal position distribution of wireless network devices plays a crucial role in improving the quality of communication services and the efficiency of device management.

[0003] The terminal position distribution method in the prior art relies on WLAN positioning algorithm, which cannot be applied to terminals connected randomly. SUMMARY

[0004] In order to solve the above problems, the present application provides a wireless terminal distribution position calculation method, device, equipment and storage medium, which accurately realizes the calculation of the position distribution of wireless terminals.

[0005] The embodiment of the present application provides a wireless terminal distribution position calculation method, which comprises the following steps:

[0006] The number of access terminals of each AP at different RSSI levels in a preset space range is counted, and an initial intensity level table of each AP is generated;

[0007] Sample points are randomly generated in the space range, and the RSSI level of each sample point at each AP is calculated;

[0008] It is determined whether the RSSI level of the sample point at each AP meets the terminal condition of the intensity level table of each AP, so as to correspondingly judge whether the coordinate of the sample point is a terminal existence point;

[0009] The judgment result of the sample point is counted, and the sample point judged as a terminal existence point is deleted from the number of access terminals counted from the intensity level table of each AP, and the intensity level table of each AP is updated;

[0010] When the updated intensity level table meets the preset condition, the sample points are randomly generated again, and it is judged whether the generated sample points are terminal existence points, the judgment result of the sample points is counted, the intensity level table of each AP is updated according to the judgment result, and the process is repeated until the updated intensity level table does not meet the preset condition;

[0011] When the updated intensity level table does not meet the preset condition, the terminal distribution probability in the space range is determined according to the counting of the judgment results of all generated sample points.

[0012] Preferably, the statistics of the number of access terminals of each AP in different RSSI levels within a preset spatial range generates an initial intensity level table of each AP, specifically comprising:

[0013] By acquiring the RSSI signals of each AP and the access terminals, the RSSI values of each AP and different terminals are determined.

[0014] The terminals with RSSI values less than a preset value are filtered out from the terminals connected to each AP.

[0015] According to the application scenario of the spatial range, a corresponding level division table is obtained from a preset level library, the number of access terminals of each AP in different RSSI levels is counted, and an initial intensity level table of each AP is generated.

[0016] As a preferred solution, the sample points are randomly generated within the spatial range, and the RSSI levels of the sample points at each AP are calculated, specifically comprising:

[0017] According to a preset selection rule, one RSSI level in the intensity level table of each AP is selected as a point selection level, and the AP with the largest number of access terminals in the point selection level is determined as an object AP.

[0018] Within the spatial range, a grid is generated at a preset interval, and a grid intersection point within a distance range corresponding to the point selection level is randomly selected as a sample point, with the object AP as the center.

[0019] The distance of the generated sample point to each AP is calculated, converted into a corresponding RSSI value, and the RSSI level of the sample point at each AP is calculated.

[0020] As an improvement of the above solution, according to the preset selection rule, one RSSI level in the intensity level table of each AP is selected as a point selection level, specifically comprising:

[0021] The initial number of each RSSI level in the initial intensity level table is calculated, wherein the initial number of each RSSI level is the sum of the number of access terminals of the RSSI level in the initial intensity level table of all APs.

[0022] The RSSI level with the highest level is selected as the current level, and it is determined whether the ratio of the number of access terminals of the current level to the initial number corresponding to the level is greater than a preset first threshold value, wherein the number of access terminals of the current level is the sum of the number of access terminals of the current level in the current intensity level table of all APs.

[0023] If not, the next level with the next highest level is selected to update as the current level, until the ratio of the number of access terminals of the current level to the initial number corresponding to the level is greater than the first threshold value.

[0024] If yes, the updated current level is taken as the selected level.

[0025] As an improvement of the above scheme, the first threshold is inversely proportional to the positioning accuracy required by the scene where the spatial range is located, and the first threshold is proportional to the calculation speed required by the scene where the spatial range is located.

[0026] As a preferred scheme, the terminal condition of whether the RSSI level of the sample point at each AP meets the strength level table of each AP is determined to correspondingly judge whether the coordinates of the sample point are terminal existence points, and specifically includes:

[0027] Judge whether the number of access terminals of the RSSI level corresponding to the sample point in the strength level table of each AP is greater than 0;

[0028] If yes, it is determined that the sample point is a terminal existence point, and the coordinates of the sample point are recorded as a terminal existence point;

[0029] If no, it is determined that the sample point is not a terminal existence point, and the coordinates of the sample point are recorded as a terminal non-existence point.

[0030] Preferably, the determination result of the sample point is counted, and specifically includes:

[0031] When the determination result is that the sample point is a terminal existence point, the first statistical probability of the sample point is increased by a preset step value;

[0032] When the determination result is that the sample point is not a terminal existence point, the second statistical probability of the sample point is increased by the step value.

[0033] Preferably, the determination result of the sample point is counted, and specifically further includes:

[0034] When the determination result is that the sample point is a terminal existence point, the coordinates of the sample point are added in a preset terminal existence list, and the statistical number corresponding to the sample point is increased by 1;

[0035] When the determination result is that the sample point is not a terminal existence point, the coordinates of the sample point are added in a preset terminal non-existence list, and the statistical number corresponding to the sample point is increased by 1.

[0036] As a preferred scheme, the sample point determined as a terminal existence point is deleted from the number of access terminals counted from the strength level table of each AP, and the strength level table of each AP is updated, and specifically includes:

[0037] When the judgment result is that the sample point is a terminal existing point, the number of access terminals of the RSSI level corresponding to the sample point in the intensity level table of each AP is reduced by 1, and the intensity level table of each AP is updated.

[0038] Preferably, when the updated intensity level table satisfies the preset condition, the sample point is randomly generated again, and whether the generated sample point is a terminal existing point is judged, the judgment result of the sample point is counted, and the intensity level table of each AP is updated according to the judgment result until the updated intensity level table does not satisfy the preset condition, and specifically includes:

[0039] When the ratio of the number of access terminals in the intensity level table of any AP after updating to the number of access terminals in the initial intensity level table of the AP is greater than a preset second threshold value, it is determined that the updated intensity level table satisfies the preset condition, wherein the number of access terminals in the intensity level table of any AP is the sum of the number of access terminals of all RSSI levels.

[0040] The sample point is randomly generated again, and whether the generated sample point is a terminal existing point is judged, the judgment result of the sample point is counted, and the intensity level table of each AP is updated according to the judgment result, and the updated intensity level table is judged again until the ratio of the number of access terminals in the intensity level table of any AP after updating to the number of access terminals in the initial intensity level table of the AP is not greater than the preset second threshold value.

[0041] As an improvement of the above scheme, the second threshold value is inversely proportional to the positioning accuracy required by the scene where the space range is located, and the second threshold value is proportional to the calculation speed required by the scene where the space range is located.

[0042] Preferably, according to the statistics of the judgment results of all generated sample points, the terminal distribution probability in the space range is determined, and specifically includes:

[0043] The terminal existing list and the terminal non-existing list generated according to the statistical result are obtained.

[0044] The statistical number Yi of the sample point i in the terminal existing list and the corresponding statistical number Ni of the sample point i in the terminal non-existing list are obtained.

[0045] The terminal distribution probability Pi of the sample point i at the coordinates is determined according to the statistical number Yi and the statistical number Ni, that is, Pi=Yi / (Yi+Ni).

[0046] As a preferred scheme, when the updated intensity level table does not satisfy the preset condition, the method further includes:

[0047] The iteration number is increased by 1, and the initial iteration number is 0. It is judged whether the iteration number is greater than a preset iteration threshold value.

[0048] If not, randomly generate sample points again and determine whether the generated sample points are terminal points. Continuously count the determination results of the sample points, update the intensity level table of each AP according to the determination results, and perform a judgment based on preset conditions. When the updated intensity level table does not meet the preset conditions, increment the iteration count by 1 and perform the iteration count judgment again until the iteration count is greater than the iteration threshold.

[0049] When the number of iterations is greater than the iteration threshold, obtain the statistical number Yi of sample point i in the terminal existence list and the statistical number Ni of sample point i in the terminal non-existence list.

[0050] When the difference between the statistical quantity Yi and the statistical quantity Ni of sample point i is greater than the product of the iteration threshold and the preset third threshold, it is determined that there is a terminal at the coordinates of sample point i, and the terminal distribution probability Pi = Yi / (Yi+Ni) of sample point i is calculated.

[0051] When the difference between the statistical quantity Yi and the statistical quantity Ni of sample point i is not greater than the product of the iteration threshold and the preset third threshold, it is determined that there is no terminal at the coordinates of sample point i.

[0052] At the coordinates of sample point i where a terminal is determined to exist, a heat map corresponding to the magnitude of the terminal distribution probability Pi is generated, thus generating a heat map of the terminal distribution within the spatial range.

[0053] Furthermore, the third threshold is inversely proportional to the positioning accuracy required by the scene in which the spatial range is located, and the third threshold is directly proportional to the calculation speed required by the scene in which the spatial range is located.

[0054] Another embodiment of the present invention provides a wireless terminal distribution location calculation device, the device comprising:

[0055] The strength level table generation module is used to count the number of access terminals of each AP at different RSSI levels within a preset spatial range and generate an initial strength level table for each AP.

[0056] The sample point generation module is used to randomly generate sample points within the spatial range and calculate the RSSI level of the sample points at each AP.

[0057] The judgment module is used to determine whether the RSSI level of the sample point at each AP meets the terminal condition of the intensity level table of each AP, so as to determine whether the coordinates of the sample point are terminal points.

[0058] The update module is used to statistically analyze the judgment results of the sample points, delete the sample points that are judged to be terminal points from the number of access terminals counted in the strength level table of each AP, and update the strength level table of each AP.

[0059] The loop module is used to randomly generate sample points again when the updated intensity level table meets the preset conditions, and determine whether the generated sample points are terminal points, count the judgment results of the sample points, and update the intensity level table of each AP according to the judgment results, until the updated intensity level table no longer meets the preset conditions.

[0060] The probability distribution calculation module is used to determine the terminal distribution probability within the spatial range based on the statistical results of the judgment results of all generated sample points when the updated intensity level table does not meet the preset conditions.

[0061] Preferably, the level table generation module is specifically used for:

[0062] By acquiring the RSSI signal of each AP and the connected terminal, the RSSI value of each AP and different terminals can be determined.

[0063] Filter out terminals with RSSI values ​​lower than a preset value from each AP connection;

[0064] Based on the application scenario of the spatial range, a preset level library is queried to obtain the corresponding level classification table. The number of access terminals of each AP at different RSSI levels is counted to generate an initial strength level table for each AP.

[0065] Preferably, the sample point generation module is specifically used for:

[0066] According to the preset selection rules, select one RSSI level from the strength level table of each AP as the selection level, and determine the AP with the most connected terminals in the selection level as the target AP.

[0067] Within the spatial range, a grid is generated at a preset interval, and grid intersections are randomly selected as sample points within a distance range corresponding to the selection level, with the object AP as the center.

[0068] Calculate the distance from the generated sample point to each AP, convert it into the corresponding RSSI value, and calculate the RSSI level of the sample point at each AP.

[0069] Preferably, the sample point generation module is further used for:

[0070] Calculate the initial number of each RSSI level in the initial strength level table, where the initial number of each RSSI level is the sum of the number of access terminals of that RSSI level in the initial strength level table of all APs;

[0071] Select the highest RSSI level as the current level, and determine whether the ratio of the number of access terminals at the current level to the initial number corresponding to the level is greater than a preset first threshold. The number of access terminals at the current level is the sum of the number of access terminals at the current level in the current strength level table of all APs.

[0072] If not, select the next lower level to update to the current level, until the ratio of the number of access terminals at the current level to the initial number corresponding to that level is greater than the first threshold.

[0073] If so, the updated current level shall be used as the selected point level.

[0074] Furthermore, the first threshold is inversely proportional to the positioning accuracy required by the scene in which the spatial range is located, and the first threshold is directly proportional to the calculation speed required by the scene in which the spatial range is located.

[0075] As a preferred embodiment, the determination module is specifically used for:

[0076] Determine whether the number of access terminals corresponding to the RSSI level of each sample point in the strength level table of each AP is greater than 0.

[0077] If so, determine that the sample point is a terminal point and record the coordinates of the sample point as a terminal point.

[0078] If not, determine that the sample point is not a terminal point, and record the coordinates of the sample point as a terminal point that does not exist.

[0079] Preferably, the update module is specifically used for:

[0080] When the judgment result is that the sample point is a terminal existence point, the first statistical probability of the sample point is increased by a preset step value;

[0081] When the judgment result is that the sample point is not a terminal point, the second statistical probability of the sample point is increased by a step value.

[0082] Preferably, the update module is further configured to:

[0083] When the judgment result is that the sample point is a terminal existence point, the coordinates of the sample point are added to the preset terminal existence list, and the statistical count corresponding to the sample point is incremented by 1. The initial statistical count of all sample points in the terminal existence list is 0.

[0084] When the judgment result is that the sample point is not a terminal existence point, the coordinates of the sample point are added to the preset terminal non-existence list, and the statistical count corresponding to the sample point is incremented by 1. The initial statistical count of all sample points in the terminal non-existence list is 0.

[0085] Preferably, the update module is further configured to:

[0086] When the determination result is that the sample point is a terminal presence point, the number of access terminals of the RSSI level corresponding to the sample point in the strength level table of each AP is reduced by 1, and the strength level table of each AP is updated.

[0087] Preferably, the loop module is specifically used for:

[0088] When the ratio of the number of access terminals in the strength level table of any AP after the update to the number of access terminals in the initial strength level table of the AP is greater than a preset second threshold, it is determined that the updated strength level table meets the preset condition, wherein the number of access terminals in the strength level table of any AP is the sum of the number of access terminals of all its RSSI levels.

[0089] Sample points are randomly generated again, and it is determined whether the generated sample points are terminal points. The determination results of the sample points are statistically analyzed, and the strength level table of each AP is updated according to the determination results. The updated strength level table is judged again until the ratio of the number of connected terminals in the strength level table of any AP after the update to the number of connected terminals in the initial strength level table of the AP is not greater than the preset second threshold.

[0090] Furthermore, the second threshold is inversely proportional to the positioning accuracy required by the scene in which the spatial range is located, and the second threshold is directly proportional to the calculation speed required by the scene in which the spatial range is located.

[0091] Preferably, the probability distribution calculation module is specifically used for:

[0092] Retrieve the list of existing terminals and the list of non-existent terminals generated based on the statistical results;

[0093] Get the statistical count Yi of sample point i in the terminal existence list, and the statistical count Ni of sample point i in the terminal non-existence list;

[0094] The terminal distribution probability Pi = Yi / (Yi+Ni) at the coordinates of sample point i is determined based on the statistical quantities Yi and Ni.

[0095] Preferably, the device further includes: an iteration module;

[0096] The iteration module is used to: when the updated intensity level table does not meet the preset conditions, increment the iteration count by 1, the initial iteration count is 0, and determine whether the iteration count is greater than the preset iteration threshold.

[0097] If not, randomly generate sample points again and determine whether the generated sample points are terminal points. Continuously count the determination results of the sample points, update the intensity level table of each AP according to the determination results, and perform a judgment based on preset conditions. When the updated intensity level table does not meet the preset conditions, increment the iteration count by 1 and perform the iteration count judgment again until the iteration count is greater than the iteration threshold.

[0098] When the number of iterations is greater than the iteration threshold, obtain the statistical number Yi of sample point i in the terminal existence list and the statistical number Ni of sample point i in the terminal non-existence list.

[0099] When the difference between the statistical quantity Yi and the statistical quantity Ni of sample point i is greater than the product of the iteration threshold and the preset third threshold, it is determined that there is a terminal at the coordinates of sample point i, and the terminal distribution probability Pi = Yi / (Yi+Ni) of sample point i is calculated.

[0100] When the difference between the statistical quantity Yi and the statistical quantity Ni of sample point i is not greater than the product of the iteration threshold and the preset third threshold, it is determined that there is no terminal at the coordinates of sample point i.

[0101] At the coordinates of sample point i where a terminal is determined to exist, a heat map corresponding to the magnitude of the terminal distribution probability Pi is generated, thus generating a heat map of the terminal distribution within the spatial range.

[0102] As an improvement to the above embodiments, the third threshold is inversely proportional to the positioning accuracy required by the scene in which the spatial range is located, and the third threshold is directly proportional to the calculation speed required by the scene in which the spatial range is located.

[0103] This invention also provides a terminal device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements a wireless terminal distribution location calculation method as described in any of the above embodiments.

[0104] This invention also provides a computer-readable storage medium, which includes a stored computer program, wherein, when the computer program is executed, it controls the device where the computer-readable storage medium is located to perform a wireless terminal distribution location calculation method as described in any of the above embodiments.

[0105] This invention provides a method, apparatus, device, and storage medium for calculating the distribution location of wireless terminals. Based on the idea of ​​the Monte Carlo random sampling algorithm, sample points are randomly generated. The presence of a sample point is determined by checking if its RSSI information meets terminal conditions. The strength level table of terminal conditions is updated. Sample points are selected by random sampling with replacement within a selected area. The accuracy of the sample meeting the terminal conditions is determined by resampling. This improves the hit rate of the sample meeting the terminal conditions, thus obtaining a possible terminal distribution. The statistical values ​​of all terminal distributions are used to accurately calculate the terminal location distribution. The process of randomly selecting and judging sample points and judging the strength level table is repeated through iterative loops to increase the number of sample points and the amount of data. Finally, a third threshold is used to determine the presence of terminals, improving the accuracy of the terminal location distribution. Attached Figure Description

[0106] Figure 1 This is a flowchart illustrating a method for calculating the distribution location of a wireless terminal provided in an embodiment of the present invention;

[0107] Figure 2 This is a flowchart illustrating a method for calculating the distribution location of a wireless terminal according to another embodiment of the present invention;

[0108] Figure 3 This is a flowchart illustrating the point selection level determination method provided in an embodiment of the present invention;

[0109] Figure 4 This is a thermal map of the spatial range provided in an embodiment of the present invention;

[0110] Figure 5 This is a schematic diagram of the structure of a wireless terminal distribution location calculation device provided in an embodiment of the present invention;

[0111] Figure 6 This is a schematic diagram of the structure of a terminal device provided in an embodiment of the present invention. Detailed Implementation

[0112] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0113] Example 1

[0114] See Figure 1 This is a flowchart illustrating a method for calculating the distribution location of a wireless terminal provided in an embodiment of the present invention, the method comprising steps S1 to S6;

[0115] S1, count the number of access terminals of each AP at different RSSI levels within the preset spatial range, and generate an initial strength level table for each AP.

[0116] S2, randomly generate sample points within the spatial range, and calculate the RSSI level of the sample points at each AP;

[0117] S3, determine whether the RSSI level of the sample point at each AP satisfies the terminal condition of the intensity level table of each AP, so as to determine whether the coordinates of the sample point are terminal points.

[0118] S4, Calculate the judgment results of the sample points, delete the sample points that are judged to be terminal points from the number of access terminals counted in the strength level table of each AP, and update the strength level table of each AP.

[0119] S5. When the updated intensity level table meets the preset conditions, sample points are randomly generated again, and it is determined whether the generated sample points are terminal points. The judgment results of the sample points are statistically analyzed, and the intensity level table of each AP is updated according to the judgment results until the updated intensity level table does not meet the preset conditions.

[0120] S6, when the updated intensity level table does not meet the preset conditions, the terminal distribution probability within the spatial range is determined based on the statistics of the judgment results of all generated sample points.

[0121] In the specific implementation of this embodiment, a number of wireless terminals and a number of wireless APs, i.e. wireless access points, are distributed within a set spatial range. Each terminal is discovered by each AP. Different APs obtain the RSSI signal of each distributed terminal. Each AP confirms the RSSI level of each connected terminal and counts the number of access terminals at different RSSI levels for each AP. Each terminal generates a strength level table that corresponds to the number of access terminals at different RSSI levels.

[0122] Sample points are randomly generated at any location within the spatial range. The RSSI level of the connection signal between the sample point and each AP is calculated based on the location of the sample point and the locations of other AP terminals.

[0123] Verify whether the RSSI level of the generated sample point and the connection signal of each AP meets the terminal condition of the strength level table of each AP. The terminal condition is that the sample point with a terminal can be found in each AP in the strength level table with an RSSI level, and the number of terminal accesses in this RSSI level is greater than 0. That is, if it is determined that the sample point has a terminal, then the RSSI level relationship between it and the connection information of each AP should conform to the strength level table of the corresponding AP.

[0124] The system determines whether a sample point is a terminal location based on whether the terminal conditions are met, and then counts the results of the terminal location determination. That is, when a sample point is determined to have a terminal, the terminal of that sample point is removed from the number of access terminals counted in the strength level table, and the strength level table of each AP is updated so that the algorithm can converge when determining subsequent sample points and complete the calculation of terminal distribution.

[0125] The updated intensity level table is judged by preset conditions. When the updated intensity level table meets the preset conditions, it means that the updated intensity level table meets the requirements for judging sample points. At this time, sample points are randomly generated again, and it is judged whether the generated sample points are terminal existence points. The intensity level table is updated again according to the judgment result, and the updated intensity level table is judged again by the preset conditions until the updated intensity level table does not meet the preset conditions.

[0126] When the updated intensity level table does not meet the preset conditions, it indicates that the updated intensity level table does not meet the requirements for judging the sample points. Based on the statistics of whether all generated sample points are terminal points, the terminal distribution probability within the spatial range is determined.

[0127] Based on the idea of ​​Monte Carlo random sampling algorithm, sample points are randomly generated. The RSSI information of the sample points is used to determine whether the sample points are terminal points. The intensity level table of terminal conditions is updated. By randomly sampling with replacement in the selected area, sample points are selected and it is determined whether the samples meet the terminal conditions. Resampling is used to improve the hit rate of the samples to the terminal conditions, thereby obtaining a possible terminal distribution. The statistical values ​​of all terminal distributions are used to realize the accurate calculation of the terminal location distribution.

[0128] Example 2

[0129] In yet another embodiment provided by the present invention, see Figure 2 This is a flowchart illustrating a method for calculating the distribution location of a wireless terminal, provided in another embodiment of the present invention.

[0130] Step S1 specifically includes:

[0131] S101, Determine the RSSI value of each terminal connected to each AP;

[0132] S102, Determine if the RSSI value is greater than -75dB?

[0133] S103, If not, delete this RSSI value;

[0134] S104, if so, retain this RSSI value;

[0135] S105, Obtain the classification table for each AP and determine the classification level;

[0136] S106, generate the initial intensity level table for each AP.

[0137] By acquiring the RSSI signals of each AP and the connected terminals, the RSSI information of each terminal is obtained, and the RSSI values ​​of each AP and different terminals are determined.

[0138] Filter out terminals with RSSI values ​​less than a preset value from each AP connection. The first preset value can be selected as -75dB. Filtering out connections with values ​​less than -75dB avoids excessive measurement errors due to excessively small RSSI values ​​and improves accuracy.

[0139] Based on the application scenario within the specified spatial range, a preset level database is queried to obtain the corresponding level classification table. The classification of RSSI intensity levels affects the positioning accuracy of terminal distribution, whether the algorithm can converge, and the convergence speed. Therefore, it is necessary to repeatedly verify the application scenarios in different spatial ranges to achieve the best results and retain the level classification table with the best positioning effect. See Table 1 for an example of a level classification table:

[0140] Table 1, Classification Table

[0141] RSSI level Distance range (m) RSSI value (dB) 0 0～3 ～-19 1 3～6 -19～-31 2 6～10 -31～-40 3 10～15 -40～-47 4 15～20 -47～-52 5 20～25 -52～-56 6 25～30 -56～-59 7 30～40 -59～-64 8 40～50 -64～-68 9 50～60 -68～-71 10 60～70 -71～-74 11 70～80 -74～-76

[0142] The grading table in Table 1 includes the correspondence between the distance range and RSSI value for each RSSI level. The grading table obtained by querying the spatial range determines the grading level corresponding to each AP. The number of access terminals of each AP at different RSSI levels is counted, and an initial strength level table for each AP is generated.

[0143] The initial strength level table includes the number of access terminals for different APs at different RSSI levels, for example, {'AP1':{'1':20,'2':5,'3':10,'4':0,'5':0,'6':0,'7':0,'8':0},'AP2':{'1':0,'2':5,'3':10,'4':0,'5':20,'6':0,'7':0,'8':0},'AP3':{'1':10,'2':5,'3':10,'4':0,'5':0,'6':20,'7':0,'8':0}}). The above strength level table discloses the number of access terminals for AP1, AP2, and AP3 at levels '1' to '8'.

[0144] This embodiment improves the accuracy of the intensity rating table by pre-screening. In other embodiments, the screening scheme may not be used, and the implementation of the scheme will not be affected.

[0145] This embodiment ensures the effectiveness of the classification by querying a classification table that has been repeatedly verified for different scenarios, thereby improving the accuracy of terminal distributed positioning and the speed of algorithm convergence. In other embodiments, the classification table query method may not be used; instead, the same pre-set classification table can be used to classify RSSI values ​​without affecting the implementation of the scheme.

[0146] Example 3

[0147] In another embodiment provided by the present invention, step S2 specifically includes:

[0148] S201, Select an RSSI level as the selection level;

[0149] S202, determine the AP with the most access terminals in the selected location level as the target AP;

[0150] S203, randomly select points as sample points within the range corresponding to the selection level of the object AP;

[0151] S204, determine the RSSI level of the sample point at each AP.

[0152] According to the preset selection rules, select one RSSI level from the strength level table of each AP as the selection level, query the strength level table to obtain the number of access terminals of each AP in the selection level, and determine the AP with the most access terminals as the target AP.

[0153] Within the spatial range, a grid is generated at preset intervals. The smaller the preset interval, the higher the positioning accuracy. Within the distance range corresponding to the selection level, grid intersections are randomly selected as sample points, with the object AP as the center.

[0154] The distance from the generated sample points to each AP is measured, and the relationship between the distance range and the RSSI value is established, i.e., the radio signal transmission formula:

[0155] Where P is the RSSI value from the sample point to the AP; P0 is the loss at a distance of 1m from the AP, tentatively set to -2dB; α is the dielectric coefficient, to be determined based on different environmental conditions; r0 = 1; dis is the distance from the sample point to the AP; σ is Gaussian white noise;

[0156] The RSSI value of the sample point and the AP is obtained according to the radio signal transmission formula. The RSSI level of the sample point at each AP is calculated according to the level classification table. For example, {'ap1': '2', 'ap2': '5', 'ap3': '1'}, that is, the RSSI level of the sample point at AP1 is 2, the RSSI level of the sample point at AP2 is 5, and the RSSI level of the sample point at AP3 is 1.

[0157] This embodiment prioritizes determining the selection level, identifies target APs based on the selection level, and prioritizes generating sample points around the AP with the largest number of connected terminals at the same RSSI level. This ensures the accuracy and convergence of the algorithm. In other embodiments, sample points can be randomly generated within the spatial range, and determining the RSSI level of sample points at different APs does not affect the implementation of the scheme.

[0158] Example 4

[0159] In yet another embodiment provided by the present invention, see Figure 3 This is a flowchart illustrating the point selection level determination method provided in an embodiment of the present invention.

[0160] The process of selecting an RSSI level from the intensity level table for each AP as the site selection level according to the preset selection rules specifically includes:

[0161] S2011, select the RSSI level with the highest intensity as the current level;

[0162] S2012, determine A j Is / A0>K1 true?

[0163] Where K1 is the number of access terminals at the current level, A j A j K1 is the initial quantity for the current level, and K1 is the preset first threshold.

[0164] S2013, If not, select the next stronger RSSI level to update the current level, and return to step S2012;

[0165] S2014, if so, use the updated current level as the selected point level;

[0166] Select the highest RSSI level as the current level, calculate the initial number of each RSSI level in the initial strength level table, and the initial number of each RSSI level is the sum of the number of access terminals of that RSSI level in the initial strength level table of all APs.

[0167] Determine the number of access terminals at the current level (A) j Whether the ratio of the initial quantity A0 corresponding to this level is greater than the preset first threshold K1, that is, to determine A j Is / A0>K1 true?

[0168] The number of access terminals at the current level is the sum of the number of access terminals at the current level as described in the current strength level table of all APs, and K1 can be 30%.

[0169] If not, it indicates that the number of access terminals in the current level does not meet the selected rule. The next level after the current level is selected to update the current level, and the ratio of the number of access terminals in the current level to the initial number corresponding to the current level is checked again to see if it is greater than the preset first threshold. If not, the next level after the current level is selected to update the current level, and the ratio of the number of access terminals in the current level to the initial number corresponding to the current level is checked again to see if it is greater than the preset first threshold, until the number of access terminals in the current level is greater than the initial number corresponding to the current level.

[0170] If so, the updated current level is used as the selected point level to determine the current level.

[0171] In this embodiment, the current level is filtered by a set selection rule to determine the highest level that meets the conditions as the current level. Sample points with stronger terminal signals are generated first, which better ensures that terminals closer to the AP are located first. These terminals have higher location accuracy, thus improving the accuracy of positioning. In other embodiments, the selection rule can be randomly defined to determine the current level, or the RSSI level with the highest number of accesses can be selected as the selection level without affecting the implementation of the scheme.

[0172] Example 5

[0173] As an improvement to the above embodiments, in the above embodiments, the first threshold is inversely proportional to the positioning accuracy required by the scene in which the spatial range is located, and the first threshold is directly proportional to the calculation speed required by the scene in which the spatial range is located.

[0174] The larger the first threshold, the faster the algorithm converges, but the lower the accuracy of the terminal thermal imaging. This is suitable for scenarios where real-time display lights have high computational speed requirements. Conversely, the smaller the first threshold, the slower the algorithm converges, but the higher the accuracy of the terminal thermal imaging. This is suitable for scenarios where the terminal thermal imaging needs to cover the terminal location more accurately. The first threshold can be adjusted according to the specific scenario of the spatial range to change the algorithm characteristics and improve the algorithm's adaptability to different scenarios.

[0175] Example 6

[0176] In yet another embodiment provided by the present invention, see Figure 2 Step S3 specifically includes:

[0177] S301, determine whether the number of access terminals of RSSI level corresponding to the sample points in the strength level table of each AP is greater than 0.

[0178] S302, if so, the sample point is a terminal point;

[0179] S303, if not, the sample point is not a terminal point.

[0180] Obtain the current strength level table for each AP, and determine whether the number of access terminals of the RSSI level corresponding to the sample point in the strength level table of each AP is greater than 0.

[0181] Traverse all AP strength registration tables. When the number of access terminals at the RSSI level of the sample point in the strength level table of each AP is greater than 0, it indicates that the RSSI level of the sample point and each AP meets the requirements of the current strength level table. The sample point is determined to meet the terminal condition, and the corresponding judgment result is that the sample point is a terminal existence point.

[0182] Traverse all AP strength registration tables. If the number of access terminals at the RSSI level of the sample point in the strength level table of an AP is not greater than 0, it indicates that the RSSI level of the sample point does not meet the requirements of the current strength level table. The sample point is determined not to meet the terminal condition, and the corresponding judgment result is that the sample point is not a terminal existence point.

[0183] By setting terminal conditions using an intensity level table, it is possible to determine whether a terminal exists at a sample point, thus enabling precise terminal location.

[0184] Example 7

[0185] In another embodiment provided by the present invention, the judgment result of the statistical sample includes:

[0186] The judgment result of the sample point is specifically used for the probability calculation of each subsequent sample point;

[0187] Therefore, when determining that the location of a sample point is a terminal presence point, the first statistical probability at the coordinates of the sample point is increased by a step value. The step value is a preset value, and the step value is the same for all sample points. It can be set according to the number of terminals within the set range.

[0188] When it is determined that the location of the sample point is not a terminal location, the second statistical probability at the coordinates of the sample point is increased by a step value. The step value of the second statistical probability is the same as the step value of the first statistical probability, and can be set according to the number of terminals within the set range.

[0189] The initial statistical probability of each sample point is 0;

[0190] By judging each sample point and calculating its probability of occurrence, the probability of a terminal existing within a set range can be statistically analyzed, enabling accurate analysis of the terminal's location distribution within that range.

[0191] Example 8

[0192] In yet another embodiment provided by the present invention, see Figure 2The judgment results of the statistical samples include:

[0193] S401, when it is determined through step S3 that the sample point is a terminal point, add the coordinates of sample point i in L1, increment the statistical count of sample point i by 1, and jump to S403.

[0194] S402, when it is determined through step S3 that the sample point is a terminal non-existent point, add the coordinates of sample point i in L2, increment the statistical count of sample point i by 1, and jump to S5;

[0195] When the judgment result is that the sample point is a terminal existence point, the coordinates of the sample point i are added to the preset terminal existence list L1, and the statistical count corresponding to the sample point i is incremented by 1. In the initial terminal existence list L1, the statistical counts of all sample points are 0.

[0196] When the judgment result is that sample point i is not a terminal existence point, the coordinates of sample point i are added to the preset terminal non-existent list L2, and the statistical count corresponding to sample point i is incremented by 1. The initial statistical count of all sample points in the initial terminal non-existent list L2 is 0.

[0197] This embodiment uses a preset terminal presence list L1 and a terminal non-existence list L2 to count the number of points where terminals exist and the number of points where terminals do not exist, respectively. This allows for the classification and storage of sample points, improving data storage efficiency and data retrieval efficiency. In other embodiments, the judgment result of each generated sample point can be directly counted without affecting the implementation of the scheme.

[0198] Example 9

[0199] In another embodiment of the present invention, the step of deleting the sample points identified as terminal presence points from the number of access terminals counted in the strength level table of each AP, and updating the strength level table of each AP, specifically includes:

[0200] See Figure 2 After determining in step S3 that the sample point is a terminal point, the following steps are executed:

[0201] S403, decrement the number of access terminals of RSSI level corresponding to the sample point in the strength level table of each AP by 1, update the strength level table of each AP, and jump to S5.

[0202] When the judgment result is that the sample point is a terminal existence point, the number of access terminals at the RSSI level of sample point i in the strength level table of all APs is reduced by 1, so as to update the strength level table of each AP.

[0203] The intensity level table is updated based on the judgment results, and the next sample point is judged based on the updated intensity level table to ensure the accuracy of each judgment of the intensity level table.

[0204] Example 10

[0205] In yet another embodiment provided by the present invention, see Figure 2 Step S5 specifically includes:

[0206] S501, determine T k Is / T0>K2 true? Where T k T0 represents the number of access terminals for any AP in the updated strength level table, T0 represents the initial number of access terminals for that AP in the strength level table, and K2 represents the preset second threshold.

[0207] S502, if so, determine that the updated intensity level table meets the preset conditions, and jump to step S2;

[0208] S503, if not, determine that the updated intensity level table does not meet the preset conditions, and jump to step S6;

[0209] Determine the number T of access terminals for any AP in the updated strength level table. k Whether the ratio of the number of connected terminals T0 in the initial strength level table of the AP is greater than the preset second threshold K2, that is, to determine T k Is / T0>K2 true? K2 can be 30%, where the number of access terminals for any AP in the strength level table is the sum of the number of access terminals for all its RSSI levels.

[0210] If so, determine that the updated strength level table meets the preset conditions; randomly generate sample points within the spatial range and determine the RSSI level of the generated sample points at each AP; determine whether the RSSI level of the generated sample points at each AP meets the terminal conditions of the strength level table of each AP, so as to determine whether the sample point is a terminal presence point; count the judgment results of the sample points, and delete the sample points judged as terminal presence points from the number of access terminals counted in the strength level table of each AP, and update the strength level table of each AP; when the updated strength level table does not meet the preset conditions, randomly generate sample points again and determine whether the generated sample points are terminal presence points, continuously count the judgment results of the sample points, and update the strength level table of each AP according to the judgment results, until the updated strength level table does not meet the preset conditions.

[0211] In this embodiment, the updated strength level table is judged by setting a second threshold and the initial number of access terminals to determine whether the updated strength level table still meets the verification requirements of the sample points, thereby improving the accuracy of sample point verification.

[0212] Example 11

[0213] In another embodiment of the present invention, the second threshold in the above embodiment is inversely proportional to the positioning accuracy required by the scene in which the spatial range is located, and the second threshold is directly proportional to the calculation speed required by the scene in which the spatial range is located.

[0214] The larger the second threshold, the faster the algorithm converges, but the lower the accuracy of the terminal thermal imaging. This is suitable for scenarios where real-time display lights have high computational speed requirements. Conversely, the smaller the second threshold, the slower the algorithm converges, but the higher the accuracy of the terminal thermal imaging. This is suitable for scenarios where the terminal thermal imaging needs to cover the terminal location more accurately. The second threshold can be adjusted according to the specific scenario of the spatial range to change the algorithm characteristics and improve the algorithm's adaptability to different scenarios.

[0215] Example 12

[0216] In another embodiment provided by the present invention, step S6 specifically includes:

[0217] S601, when step S5 determines that the updated intensity level table does not meet the preset conditions, obtain the statistical count Y of sample point i. i And statistical quantity N i , where Y i Let N be the number of sample points i in the terminal existence list L1. i Count the number of sample points i in the terminal non-existent list L2;

[0218] S602, Calculate the terminal distribution probability P of sample point i. i Determine the location distribution of the terminals within the spatial range.

[0219] By obtaining the terminal presence list L1 and terminal non-existence list L2 generated based on the judgment results of all generated sample points, the statistical count Y of sample point i in the terminal presence list L1 is obtained. i And the statistical number N corresponding to sample point i not existing in the terminal list L2. i ;

[0220] According to the statistical quantity Y i And statistical quantity N i Determine the terminal distribution probability P at the coordinates of sample point i. i =Y i / (Y i +N i To determine the location distribution of terminals within the spatial range.

[0221] In this embodiment, the terminal location distribution is determined by calculating the terminal distribution probability based on the terminal presence list and the terminal absence list, i.e., the distribution probability of the terminal in a spatial range, which makes the terminal location distribution more accurate. In other embodiments, the terminal location distribution can be directly confirmed by the location distribution of sampling points in the terminal presence list without affecting the implementation of the scheme.

[0222] Example 13

[0223] In another embodiment of the present invention, when the updated intensity level table does not meet the preset conditions, the method further includes:

[0224] S701, when step S6 determines that the updated intensity level table does not meet the preset conditions, the iteration count d is incremented by 1.

[0225] S702, Determine whether d > D is true?

[0226] Where D is the preset iteration threshold;

[0227] S703, if not, determine that the number of iterations has not reached the target, and return to step S2;

[0228] S704, if so, determine that the number of iterations has reached the target, and obtain the statistical count Y of sample point i. i And statistical quantity N i , where Y i Let N be the number of sample points i in the terminal existence list L1. i Count the number of sample points i in the terminal non-existent list L2;

[0229] S705, determine (Y) i -N i Is the following condition true: ) / D>K3?

[0230] S706, if not, determine that there is no terminal at the coordinates of sample point i, and jump to S708;

[0231] S707, If so, determine that a terminal exists at the coordinates of sample point i, and calculate the terminal distribution probability P. i ;

[0232] S708, generate a heat map of terminal distribution;

[0233] Increment the iteration count by 1, and check if the iteration count is greater than the preset iteration threshold. The initial iteration count is 0.

[0234] If not, randomly generate sample points within the spatial range and determine the RSSI level of the generated sample points at each AP; determine whether the RSSI level of the generated sample points at each AP meets the terminal conditions of the current strength level table, so as to determine whether the generated sample points are terminal presence points; continuously update the terminal presence list and terminal non-existence list according to the judgment results, and delete the sample points judged as terminal presence points from the number of access terminals counted in the strength level table of each AP, and update the strength level table of each AP; when the updated strength level table meets the preset conditions, randomly generate sample points again and determine whether the generated sample points are terminal presence points, continuously count the judgment results of the sample points, and update the strength level table of each AP according to the judgment results until the updated strength level table meets the preset conditions; when the updated strength level table does not meet the preset conditions, increment the iteration count by 1, and judge the iteration count again until the iteration count is greater than the iteration threshold D.

[0235] When the number of iterations exceeds the iteration threshold D, obtain the statistical number Y of sample point i in the terminal's list. i And the statistical number N corresponding to sample point i not existing in the terminal list. i ;

[0236] When the statistical quantity Y of sample point i i And statistical quantity N i When the difference is greater than the product of the iteration threshold D and the preset third threshold K3, that is, (Y) i -N i When ) / D>K3, determine that there is a terminal at the coordinates of sample point i, and calculate the terminal probability distribution P. i =Y i / (Y i +N i ), wherein K3 can preferably be 0.15;

[0237] When the statistical quantity Y of sample point i i And statistical quantity N i When the difference is not greater than the product of the iteration threshold D and the preset third threshold, it is determined that there is no terminal at the coordinates of sample point i.

[0238] At the coordinates of sample point i where a terminal is determined to exist, generate a value corresponding to the terminal distribution probability P. i The size of the heat points corresponds to the size of the heat points, and a heat map of the terminal distribution within the spatial range is generated.

[0239] See Figure 4 This is a spatial range heat map provided in the embodiments of the present invention; in the figure, the larger the heat points, the greater the probability of the existence of terminals, and the denser the distribution of heat points, the greater the density of terminal distribution.

[0240] In this embodiment, the size of the heat points reflects the probability of terminal distribution, which can intuitively show the location of the terminals. In other embodiments, the color of the heat points can be used to represent the distribution probability, which does not affect the implementation of the solution.

[0241] This embodiment increases the number of sample points and the amount of data by iterating D times, repeating the random selection, judgment, and intensity level table judgment process of sample points; and improves the accuracy of terminal location distribution by using a third threshold to determine whether a terminal exists.

[0242] Example 14

[0243] In another embodiment provided by the present invention, the third threshold in the above embodiment is inversely proportional to the positioning accuracy required by the scene in which the spatial range is located, and the third threshold is directly proportional to the calculation speed required by the scene in which the spatial range is located.

[0244] The larger the third threshold, the faster the algorithm converges, but the lower the accuracy of the terminal thermal imaging. This is suitable for scenarios where real-time display lights have high computational speed requirements. Conversely, the smaller the third threshold, the slower the algorithm converges, but the higher the accuracy of the terminal thermal imaging. This is suitable for scenarios where the terminal thermal imaging needs to cover the terminal location more accurately. The third threshold can be adjusted according to the specific scenario of the spatial range to change the algorithm characteristics and improve the algorithm's adaptability to different scenarios.

[0245] Example 15

[0246] See Figure 5 This is a schematic diagram of the structure of a wireless terminal distribution location calculation device provided in an embodiment of the present invention. The device includes: a level table generation module, a sample point generation module, a judgment module, an update module, a loop module, and a distribution probability calculation module.

[0247] The strength level table generation module is used to count the number of access terminals of each AP at different RSSI levels within a preset spatial range and generate an initial strength level table for each AP.

[0248] The sample point generation module is used to randomly generate sample points within the spatial range and calculate the RSSI level of the sample points at each AP.

[0249] The judgment module is used to determine whether the RSSI level of the sample point at each AP meets the terminal condition of the intensity level table of each AP, so as to determine whether the coordinates of the sample point are terminal points.

[0250] The update module is used to statistically analyze the judgment results of the sample points, delete the sample points that are judged to be terminal points from the number of access terminals counted in the strength level table of each AP, and update the strength level table of each AP.

[0251] The loop module is used to randomly generate sample points again when the updated intensity level table meets the preset conditions, and determine whether the generated sample points are terminal points, count the judgment results of the sample points, and update the intensity level table of each AP according to the judgment results, until the updated intensity level table no longer meets the preset conditions.

[0252] The probability distribution calculation module is used to determine the terminal distribution probability within the spatial range based on the statistical results of the judgment results of all generated sample points when the updated intensity level table does not meet the preset conditions.

[0253] The wireless terminal distribution location calculation device provided in this embodiment can execute all the steps and functions of the wireless terminal distribution location calculation method provided in any of the above embodiments. The specific functions of the device will not be described in detail here.

[0254] Example 16

[0255] See Figure 6 This is a schematic diagram of a terminal device provided in an embodiment of the present invention. The terminal device includes a processor, a memory, and a computer program stored in the memory and executable on the processor, such as a wireless terminal location calculation program. When the processor executes the computer program, it implements the steps in the various embodiments of the wireless terminal location calculation method described above, for example... Figure 1 The steps S1 to S6 are shown. Alternatively, when the processor executes the computer program, it implements the functions of each module in the above-described device embodiments.

[0256] For example, the computer program can be divided into one or more modules, which are stored in the memory and executed by the processor to complete the present invention. The one or more modules can be a series of computer program instruction segments capable of performing specific functions, which describe the execution process of the computer program in the wireless terminal location calculation device. For example, the computer program can be divided into a detection module, an output power control module, and a window control module. The specific functions of each module have been described in detail in the wireless terminal location calculation method provided in any of the above embodiments, and the specific functions of the device will not be repeated here.

[0257] The wireless terminal location calculation device can be a desktop computer, laptop, handheld computer, or cloud server, etc. The wireless terminal location calculation device may include, but is not limited to, a processor and memory. Those skilled in the art will understand that the schematic diagram is merely an example of a wireless terminal location calculation device and does not constitute a limitation on such a device. It may include more or fewer components than illustrated, or combine certain components, or use different components. For example, the wireless terminal location calculation device may also include input / output devices, network access devices, buses, etc.

[0258] The processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor. The processor is the control center of the wireless terminal location computing device, connecting all parts of the device via various interfaces and lines.

[0259] The memory can be used to store the computer programs and / or modules. The processor implements various functions of the wireless terminal distributed location computing device by running or executing the computer programs and / or modules stored in the memory and calling the data stored in the memory. The memory may mainly include a program storage area and a data storage area. The program storage area may store the operating system, at least one application program required for a function (such as sound playback function, image playback function, etc.), etc.; the data storage area may store data created according to the use of the mobile phone (such as audio data, phonebook, etc.). In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as hard disk, memory, plug-in hard disk, smart media card (SMC), secure digital card (SD) card, flash card, at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0260] If the module integrated into the wireless terminal location calculation device is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the above embodiments of the present invention can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc. It should be noted that the content contained in the computer-readable medium may be appropriately added to or subtracted from the content as required by the legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the computer-readable medium may not include electrical carrier signals and telecommunication signals.

[0261] It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of this invention, and these improvements and modifications are also considered to be within the scope of protection of this invention.

Claims

1. A method of calculating the distribution of positions of wireless terminals, characterized in that, The method comprises: counting the number of access terminals of each AP at different RSSI levels in a preset spatial range, and generating an initial intensity level table of each AP; randomly generating sample points in the spatial range, and calculating the RSSI level of each sample point at each AP; determining whether the RSSI level of the sample point at each AP meets the terminal condition of the intensity level table of each AP, to correspondingly judge whether the coordinate of the sample point is a terminal existence point; counting the judgment result of the sample point, deleting the sample point judged as a terminal existence point from the number of access terminals counted in the intensity level table of each AP, and updating the intensity level table of each AP; when the updated intensity level table meets a preset condition, randomly generating sample points again, judging whether the generated sample points are terminal existence points, counting the judgment result of the sample points, updating the intensity level table of each AP according to the judgment result, and stopping until the updated intensity level table does not meet the preset condition; when the updated intensity level table does not meet the preset condition, determining the terminal distribution probability in the spatial range according to the counting of the judgment result of all generated sample points.

2. The wireless terminal distributed position calculation method according to claim 1, characterized by, The counting of the number of access terminals of each AP at different RSSI levels in a preset spatial range, and the generation of an initial intensity level table of each AP, specifically comprises: determining the RSSI value of each AP and different terminals by acquiring the RSSI signal of each AP and the access terminal; filtering out the terminal with an RSSI value less than a preset value among the terminals connected to each AP; querying a preset level library according to the application scenario of the spatial range, obtaining a corresponding level division table, counting the number of access terminals of each AP at different RSSI levels, and generating an initial intensity level table of each AP.

3. The wireless terminal distributed position calculation method of claim 1, wherein, The randomly generating sample points in the spatial range, and the calculation of the RSSI level of each sample point at each AP, specifically comprises: selecting one RSSI level in the intensity level table of each AP as a point selection level according to a preset selection rule, and determining the AP with the largest number of access terminals in the point selection level as an object AP; generating a grid at a preset interval in the spatial range, randomly selecting a grid intersection point as a sample point within a distance range corresponding to the point selection level and centered on the object AP; calculating the distance of the generated sample point to each AP, converting it into a corresponding RSSI value, and calculating the RSSI level of the sample point at each AP.

4. The wireless terminal distributed position calculation method according to claim 3, characterized by, The selecting one RSSI level in the intensity level table of each AP as a point selection level according to a preset selection rule specifically comprises: calculating the initial number of each RSSI level in the initial intensity level table, wherein the initial number of each RSSI level is the sum of the number of access terminals of the RSSI level in the initial intensity level table of all APs. selecting a highest RSSI level as a current level, and determining whether a ratio of a number of access terminals of the current level to an initial number corresponding to the current level is greater than a first threshold value, wherein the number of access terminals of the current level is a sum of the number of access terminals of the current level in a current strength level table of all APs; if not, selecting a next level of a next level of a same strength as the current level to update the current level until the ratio of the number of access terminals of the current level to the initial number corresponding to the current level is greater than the first threshold value; if yes, using the updated current level as the selected level.

5. The wireless terminal distributed position calculation method according to claim 4, characterized by, The first threshold value is inversely proportional to a positioning accuracy required by a scenario where the space range is located, and the first threshold value is proportional to a calculation speed required by the scenario where the space range is located.

6. The wireless terminal distributed position calculation method of claim 1 wherein, The determining whether the RSSI level of the sample point at each AP satisfies a terminal condition of the strength level table of each AP to correspondingly determine whether the coordinate of the sample point is a terminal existence point specifically includes: determining whether the number of access terminals of the RSSI level of the sample point in the strength level table of each AP is greater than 0; if yes, determining that the sample point is a terminal existence point, and recording the coordinate of the sample point as the terminal existence point; if not, determining that the sample point is not a terminal existence point, and recording the coordinate of the sample point as a terminal non-existence point.

7. The wireless terminal distributed position calculation method of claim 1, wherein, The statistics of the determination result of the sample point specifically includes: when the determination result is that the sample point is a terminal existence point, increasing a first statistical probability of the sample point by a preset step value; when the determination result is that the sample point is not a terminal existence point, increasing a second statistical probability of the sample point by the step value.

8. The wireless terminal distributed position calculation method of claim 1 wherein, The statistics of the determination result of the sample point further specifically includes: when the determination result is that the sample point is a terminal existence point, adding the coordinate of the sample point in a preset terminal existence list, and adding 1 to a statistical number corresponding to the sample point; when the determination result is that the sample point is not a terminal existence point, adding the coordinate of the sample point in a preset terminal non-existence list, and adding 1 to the statistical number corresponding to the sample point.

9. The wireless terminal distributed position calculation method of claim 1 wherein, The deleting the sample point determined as a terminal existence point from the number of access terminals of the RSSI level corresponding to the sample point in the strength level table of each AP, and updating the strength level table of each AP specifically includes: when the determination result is that the sample point is a terminal existence point, reducing 1 from the number of access terminals of the RSSI level corresponding to the sample point in the strength level table of each AP, and updating the strength level table of each AP.

10. The wireless terminal distributed position calculation method of claim 1 wherein, The again generating a sample point when the updated strength level table satisfies a preset condition, determining whether the generated sample point is a terminal existence point, and updating the strength level table of each AP according to a determination result of the sample point until the updated strength level table does not satisfy the preset condition, specifically includes: determining that the updated strength level table meets the preset condition when a ratio of a number of access terminals in the updated strength level table of any AP to a number of access terminals in the initial strength level table of the AP is greater than a preset second threshold value, wherein the number of access terminals in the strength level table of any AP is a sum of the number of access terminals in all RSSI levels of the AP; randomly generating sample points again, determining whether the generated sample points are terminal existence points, counting the determination results of the sample points, updating the strength level table of each AP according to the determination results, and determining the updated strength level table again until the ratio of the number of access terminals in the updated strength level table of any AP to the number of access terminals in the initial strength level table of the AP is not greater than the preset second threshold value.

11. The wireless terminal distributed position calculation method according to claim 10, wherein, The second threshold value is inversely proportional to the positioning accuracy required by a scene where the space range is located, and the second threshold value is proportional to the calculation speed required by the scene where the space range is located.

12. The wireless terminal distributed position calculation method of claim 1 wherein, The terminal distribution probability in the space range is determined according to the counting of the determination results of all the generated sample points, and specifically includes: obtaining a terminal existence list and a terminal nonexistence list generated according to the counting results; Obtaining the statistical number Y of sample point i in the terminal existence list i and the corresponding statistical number N of sample point i in the terminal nonexistence list i ; According to the statistical quantity Y i and the statistical quantity N i determining the terminal distribution probability P at the coordinates of the sample point i i = Y i / (Y i +N i ).

13. The wireless terminal distributed position calculation method of claim 1 wherein, When the updated strength level table does not meet the preset condition, the method further includes: adding 1 to the iteration number, and determining whether the iteration number is greater than a preset iteration threshold value, wherein the initial iteration number is 0; If not, the sample points are randomly generated again, it is determined whether the generated sample points are terminal existence points, the determination results of the sample points are continuously counted, the strength level table of each AP is updated according to the determination results, and the determination of the preset condition is performed; when the updated strength level table does not meet the preset condition, the iteration number is added by 1 again, the iteration number is determined again, and the iteration is performed until the iteration number is greater than the iteration threshold value. when the iteration number is greater than the iteration threshold value, obtaining a statistical quantity Y of the sample point i in the terminal existing list i and a corresponding statistical quantity N of the sample point i in the terminal non-existing list i ; When the difference between the statistical quantity Y i and the statistical quantity N i of the sample point i is greater than the product of the iteration threshold and a preset third threshold, it is determined that there is a terminal at the coordinate of the sample point i, and the terminal distribution probability P i of the sample point i is calculated as Y i / (Y i +N i ). when the difference between the statistical quantity Y i and the statistical quantity N i is not greater than the product of the iteration threshold and a preset third threshold, it is determined that no terminal exists at the coordinate of the sample point i; determining that there is a terminal, generating a terminal distribution probability P i corresponding to the size of the heat point, generating a heat map of the terminal distribution in the spatial range.

14. The wireless terminal distributed position calculation method according to claim 13, wherein, The third threshold value is inversely proportional to the positioning accuracy required by a scene where the space range is located, and the third threshold value is proportional to the calculation speed required by the scene where the space range is located.

15. A wireless terminal distribution location calculation apparatus characterized by comprising: The device includes: a level table generation module configured to count the number of access terminals of each AP in different RSSI levels in a preset space range, and generate an initial strength level table of each AP; a sample point generation module configured to randomly generate sample points in the space range, and calculate the RSSI level of the sample points at each AP; a determination module configured to determine whether the RSSI level of the sample points at each AP meets the terminal condition of the strength level table of each AP, so as to correspondingly determine whether the coordinates of the sample points are terminal existence points; an updating module configured to count the determination results of the sample points, delete the sample points determined as terminal existence points from the number of access terminals counted by the strength level table of each AP, and update the strength level table of each AP; a loop module configured to randomly generate sample points again when the updated strength level table meets the preset condition, determine whether the generated sample points are terminal existence points, count the determination results of the sample points, update the strength level table of each AP according to the determination results, and stop until the updated strength level table does not meet the preset condition. A distribution probability calculation module is configured to determine a terminal distribution probability in the space range according to statistics of the judgment results of all the generated sample points when the updated intensity level table does not satisfy the preset condition.

16. A terminal device, comprising: The wireless terminal distribution position calculation method comprises a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, and the processor implements the wireless terminal distribution position calculation method according to any one of claims 1 to 14 when executing the computer program.

17. A computer-readable storage medium, characterized in that, The computer readable storage medium comprises a stored computer program, wherein the computer readable storage medium controls a device where the computer readable storage medium is located to execute the wireless terminal distribution position calculation method according to any one of claims 1 to 14 when the computer program runs.

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