An electronic fence management method

Abstract

The application provides an electronic fence management method, which is based on an electronic fence management system composed of an electronic fence position calculation module, an electronic fence position self-calibration module and an electronic fence event triggering module. By measuring the deviation difference, the objects to be monitored are divided into reliable object sets and unreliable object sets. Then, the position information of the reliable object set is used as prior information to calibrate the position information of the unreliable object set, so as to realize the mutual calibration of the objects in the electronic fence system to improve the position measurement accuracy. Finally, the calibrated position information is used for electronic fence event triggering monitoring. By using the method, the accuracy of the electronic fence monitoring can be effectively improved without increasing the electronic fence hardware facilities.

Description

Technical Field

[0001] This application relates to the field of electronic fence management technology, and in particular to an electronic fence management method. Background Technology

[0002] The statements in this section are merely background information related to this application and do not necessarily constitute prior art.

[0003] With the advancement of informatization, security management systems based on high informatization have developed rapidly. Among them, the application of electronic fences is becoming increasingly popular. The principle of electronic fence application is to first set the target area, then sense the location of the terminal. When it is determined that the terminal has entered the target area, the corresponding monitoring event is triggered, thereby achieving seamless monitoring.

[0004] However, a challenge in the application of electronic fence technology is the inability to accurately perceive the location information of the terminal to be tracked, which greatly reduces the effectiveness of electronic fence applications. Especially indoors, due to the complexity of the building structure and the non-line-of-sight transmission of signals, conventional measurement methods cannot accurately obtain the location information of each terminal, ultimately leading to an increase in the false alarm and missed detection rate of electronic fence monitoring, which directly affects the user experience.

[0005] To address the issue of poor location accuracy in electronic fence systems, a typical industry improvement measure is to deploy more reference nodes and signal transceiver nodes with different modes to increase mode penetration and measurement recognition, thereby improving the sufficiency and accuracy of location acquisition in electronic fence systems. However, this approach requires a significant increase in hardware, leading to a substantial increase in the cost of electronic fence systems and putting cost pressure on the application of the solution, making it difficult to promote.

[0006] Therefore, for electronic fence systems, how to improve the monitoring accuracy of electronic fence systems without increasing equipment deployment, especially by using measurement results within the electronic fence subsystem to achieve self-calibration and improve monitoring accuracy, is a problem that the industry needs to solve. Summary of the Invention

[0007] To address the aforementioned issues, this application proposes an electronic fence management method that enables mutual calibration between objects within the electronic fence system to improve the accuracy of electronic fence monitoring. This method effectively enhances the accuracy of electronic fence monitoring without increasing the amount of electronic fence hardware.

[0008] This application provides an electronic fence management method based on an electronic fence management system consisting of an electronic fence location calculation module, an electronic fence location self-calibration module, and an electronic fence event triggering module, comprising the following steps:

[0009] Step 1: The electronic fence location calculation module calculates the measurement deviation of each tracked object based on the measurement values ​​of the tracked objects reported by each access point, and divides the tracked objects into a reliable object set S0, a secondary reliable object set S1, and an unreliable object set S2 based on the measurement deviation. It also estimates the location information set P0 corresponding to each member of the reliable object set S0 and the initial location information set P1 corresponding to each member of the secondary reliable object set S1.

[0010] Step 2: The electronic fence position self-calibration module uses the position information P0 of each object in S0 as prior information to calibrate the position information of each member in S1, and obtains the calibrated position information P1_modify of the members in S1. Then, using the position information P0 and P1_modify of each object in S0 and S1 as prior information, the position information of each member in S2 is estimated to obtain P2_estimate.

[0011] Step 3: The electronic fence event triggering module uses location information P0 to monitor electronic fence event triggering for members of object set S0, uses location information P1_modify to monitor electronic fence event triggering for members of object set S1, and uses location information P2_estimate to monitor electronic fence event triggering for members of object set S2.

[0012] Preferably, in step 1, the measured value is the time difference of arrival. The specific method for the electronic fence location calculation module to divide the reliable object set S0, the secondary reliable object set S1, and the unreliable object set S2, and to estimate the location information set P0 corresponding to each member of the reliable object set S0 and the initial location information set P1 corresponding to each member of the secondary reliable object set S1 is as follows:

[0013] Based on the formulas (1) to (9), the W value and the (x, y, z) value are calculated, and then the following processing is performed:

[0014] If the number of arrival time difference measurements of a UE is less than 4 or the W value calculated by equation (9) is less than 0, then the deviation of the UE is infinite and the UE is assigned to the unreliable object set S2. At this time, the UE has no initial position coordinates.

[0015] If the W value calculated by equation (9) is equal to 0, then the deviation of the UE is 0, the UE is assigned to the reliable object set S0, and the user's location coordinates (x, y, z) are calculated according to equation (6). The user's location coordinates are unique and are put into the location information set P0.

[0016] If there are two values obtained by calculating according to Equation (8), then two initial position coordinates (x_pos0, y_pos0, z_pos0) and (x_pos1, y_pos1, z_pos1) of the UE are obtained according to Equation (6). Then calculate the distance between these two coordinates Distance_pos0_to_pos1 =

[0017] ,

[0018] If Distance_pos0_to_pos1 < threshold1, then the deviation degree of the UE is 0, the UE is classified into the reliable object set S0, and the unique position coordinate of the UE is calculated according to ((x_pos0, y_pos0, z_pos0) + (x_pos1, y_pos1, z_pos1)) / 2 and put into the position information set P0;

[0019] If Distance_pos0_to_pos1 ≥ threshold1, then the deviation degree of the UE is threshold1, it is classified into the "sub - reliable object set S1", and (x_pos0, y_pos0, z_pos0) and (x_pos1, y_pos1, z_pos1) are used as the two initial position coordinates of the UE and put into the initial position information set P1;

[0020] In step 1, in Equations (1) to (9), is the master station coordinate, is the coordinate of the slave station i, and the value of i is 1, 2, 3, is the distance difference between the distance from the object to be tracked to the master station and the distance from the object to be tracked to the slave station i;

[0021] [[ID=...]] (1)

[0022] (2) <...> <...> (3) <0000...> <0000...> [[ID=3...]] (4) <0000...> <0000...> (5) <0000...> <0000...> ... (6) <0000...> <00...> (7) <0000...> <0000...> (8)

[0029] (9).

[0030] Preferably, in step 2, the position calibration module uses the position information P0 of each object in S0 as prior information, and then calibrates the position information of each member in S1. The specific method is as follows:

[0031] Step 2.1A: Clear P1_modify;

[0032] Step 2.2A: Determine whether S1 is empty. If yes, proceed to step 2.7A. If no, obtain a member K1 from S1 and delete the member from S1.

[0033] Step 2.3A: Obtain the two initial position information of member K, P0_K1 and P1_K1;

[0034] Step 2.4A: Select member K2 from S0 that is closest to P0_K, and select member K3 that is closest to P1_K;

[0035] Step 2.5A: Trigger base station scheduling members K1 and K2, K1 and K3 to perform sidelink measurements, and obtain the path loss measurement results of K1 and K2, K1 and K3 from the base station: Measure_1_to_2, Measure_2_to_1, Measure_1_to_3, Measure_3_to_1;

[0036] Step 2.6A, if

[0037] (Measure_1_to_2+Measure_2_to_1)>(Measure_1_to_3+Measure_3_to_1),

[0038] If the position of member K1 is corrected to P1_K1, then the position of member K1 is corrected to P0_K1, and K1 and its position information are written to P1_modify. Then, the process jumps to step 2.2A.

[0039] Step 2.7A: Output P1_modify.

[0040] Preferably, in step 2, the position calibration module uses the position information P0 and P1_modify of each object in S0 and S1 as prior information to estimate the position information of each member in S2 to obtain P2_estimate. The specific steps are as follows:

[0041] Step 2.1B: Clear P2_estimate, merge P0 and P1_modify information into P_combine. Each member includes the terminal ID and its unique location coordinates. Divide the area to be monitored into F grids according to the preset grid size. Each grid has unique coordinates and number.

[0042] Step 2.2B: Determine whether S2 is empty. If it is, proceed to step 2.7B. If not, obtain a member K1 from S2 and delete the member from S2.

[0043] Step 2.3B: Obtain the access point AP_i where member K1 resides, where i takes values ​​of 0, ..., I-1, and I is the number of access points where K1 resides;

[0044] Step 2.4B: Trigger the base station to schedule Terminal_i_j and K1, which are stationed under AP_i and belong to P_combine, to perform sidelink measurements. Obtain the path loss measurement results Measure_i_j_to_K1 and Measure_K1_to_i_j from the base station. Measure_i_j_to_K1 is the path loss measurement value from terminal j stationed under AP_i to member K1, and Measure_K1_to_i_j is the path loss measurement value from K1 to terminal j stationed under AP_i.

[0045] Step 2.5B: Select the P terminals with the smallest value of (Measure_i_j_to_K1 + Measure_K1_to_i_j) from i and j, and define the terminals. The value of p can be 0, ..., P-1;

[0046] Step 2.6B: Select the cell from the F cells that satisfies the terminal condition. With the origin of the coordinate system,

[0047] (Measure_) _to_K1+Measure_K1_to_ ) / 2

[0048] For cells with path loss, the center coordinates of the cell are used as member K1 relative to the terminal. Candidate location coordinate set The The number of grids is defined as From each candidate location coordinate set Each cell is selected to form a combination containing P cells. The cumulative value of the center coordinate distance between each pair of cells in each combination is calculated. The combination with the smallest cumulative value is selected. The mean coordinate of the P cells in the corresponding combination is calculated as the position coordinate Axis_K1 of member K1. Member K1 and its estimated coordinate Axis_K1 are written into P2_estimate, and then the process jumps to step 2.2B.

[0049] Step 2.7B: Output P2_estimate.

[0050] Preferably, in step 3, the fence event triggering monitoring includes, but is not limited to, the location being located within the target area and the location remaining within the target area for a time greater than a threshold T.

[0051] Compared with the prior art, the beneficial effects of this application are as follows:

[0052] This application divides the monitored objects into reliable and unreliable sets by measuring deviation differences. Then, using the location information of the reliable object set as prior information, the location information of the unreliable object set is calibrated. This achieves mutual calibration between objects in the electronic fence system, improving the accuracy of location measurement. Finally, the calibrated location information is used for electronic fence event triggering monitoring. Using this method, the accuracy of electronic fence monitoring can be effectively improved without increasing the hardware infrastructure of the electronic fence. Attached Figure Description

[0053] The accompanying drawings, which form part of this application, are used to provide a further understanding of this application. The illustrative embodiments of this application and their descriptions are used to explain this application and do not constitute an undue limitation of this application.

[0054] Figure 1 This is a schematic diagram of a method flow according to one embodiment of this application.

[0055] Figure 2 This is a schematic diagram of the system composition according to one embodiment of this application.

[0056] Figure 3 This is a schematic diagram of one embodiment of this application. Figure 1 ,

[0057] Figure 4 This is a schematic diagram of one embodiment of this application. Figure 2 . Detailed Implementation

[0058] The present application will be further described below with reference to the accompanying drawings and embodiments.

[0059] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the exemplary embodiments according to this disclosure. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms “comprising” and / or “including” are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0060] In this disclosure, terms such as "upper," "lower," "left," "right," "front," "back," "vertical," "horizontal," "side," and "bottom" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are merely relational terms determined for the convenience of describing the structural relationship of the various components or elements in this disclosure, and do not specifically refer to any component or element in this disclosure, nor should they be construed as limiting this disclosure.

[0061] like Figures 1 to 3 As shown, this application provides an electronic fence management system, including an electronic fence location calculation module, an electronic fence location self-calibration module, and an electronic fence event triggering module. The functions of each module are as follows:

[0062] Electronic fence location calculation module: This module calculates the measurement deviation of each tracked object based on the measurement values ​​of the tracked objects reported by each access point, and divides the tracked objects into a reliable object set S0, a secondary reliable object set S1, and an unreliable object set S2 based on the measurement deviation. It also estimates the location information set P0 corresponding to each member of the reliable object set S0 and the initial location information set P1 corresponding to each member of the secondary reliable object set S1.

[0063] Electronic fence position self-calibration module: This module uses the position information P0 of each object in S0 as prior information to calibrate the position information of each member in S1 to obtain the calibrated position information P1_modify of the members in S1. Then, using the position information P0 and P1_modify of each object in S0 and S1 as prior information, the position information of each member in S2 is estimated to obtain P2_estimate.

[0064] Electronic fence event triggering module: This module uses location information P0 to monitor electronic fence event triggering for members of object set S0, uses location information P1_modify to monitor electronic fence event triggering for members of object set S1, and uses location information P2_estimate to monitor electronic fence event triggering for members of object set S1.

[0065] This application also provides an electronic fence management method based on the above system, including the following steps:

[0066] Step 1: The electronic fence location calculation module calculates the measurement deviation of each tracked object based on the measurement values ​​of the tracked objects reported by each access point, and divides the tracked objects into a reliable object set S0, a secondary reliable object set S1, and an unreliable object set S2 based on the measurement deviation. It also estimates the location information set P0 corresponding to each member of the reliable object set S0 and the initial location information set P1 corresponding to each member of the secondary reliable object set S1.

[0067] Step 2: The electronic fence position self-calibration module uses the position information P0 of each object in S0 as prior information to calibrate the position information of each member in S1, and obtains the calibrated position information P1_modify of the members in S1. Then, using the position information P0 and P1_modify of each object in S0 and S1 as prior information, the position information of each member in S2 is estimated to obtain P2_estimate.

[0068] Step 3: The electronic fence event triggering module uses location information P0 to monitor electronic fence event triggering for members of object set S0, uses location information P1_modify to monitor electronic fence event triggering for members of object set S1, and uses location information P2_estimate to monitor electronic fence event triggering for members of object set S2.

[0069] In step 1, the measured value is the time difference of arrival. The specific method for the electronic fence location calculation module to divide the reliable object set S0, the secondary reliable object set S1, and the unreliable object set S2, and to estimate the location information set P0 corresponding to each member of the reliable object set S0 and the initial location information set P1 corresponding to each member of the secondary reliable object set S1 is as follows:

[0070] Based on the formulas (1) to (9), the W value and the (x, y, z) value are calculated, and then the following processing is performed:

[0071] If the number of arrival time difference measurements of a UE is less than 4 or the W value calculated by equation (9) is less than 0, then the deviation of the UE is infinite and the UE is assigned to the unreliable object set S2. At this time, the UE has no initial position coordinates.

[0072] If the W value calculated by equation (9) is equal to 0, then the deviation of the UE is 0, the UE is assigned to the reliable object set S0, and the user's location coordinates (x, y, z) are calculated according to equation (6). The user's location coordinates are unique and are put into the location information set P0.

[0073] If there are two values calculated according to Equation (8), then two initial position coordinates (x_pos0, y_pos0, z_pos0) and (x_pos1, y_pos1, z_pos1) of the UE are obtained according to Equation (6). Then, calculate the distance between these two coordinates, Distance_pos0_to_pos1 =

[0074] ,

[0075] If Distance_pos0_to_pos1 < threshold1, then the deviation of the UE is 0, the UE is classified into the reliable object set S0, and the unique position coordinate of the UE is calculated according to ((x_pos0, y_pos0, z_pos0) + (x_pos1, y_pos1, z_pos1)) / 2 and put into the position information set P0;

[0076] If Distance_pos0_to_pos1 ≥ threshold1, then the deviation of the UE is threshold1, it is classified into the "sub - reliable object set S1", and (x_pos0, y_pos0, z_pos0) and (x_pos1, y_pos1, z_pos1) are used as the two initial position coordinates of the UE and put into the initial position information set P1;

[0077] In step 1, in Equations (1) to (9), is the master station coordinate, is the coordinate of slave station i, where i takes values of 1, 2, 3, is the distance difference between the distance from the object to be tracked to the master station and the distance from the object to be tracked to slave station i;

[0078] (1)

[0079] (2)

[0080] (3)

[0081] (4)

[0082] (5)

[0083] (6)

[0084] (7)

[0085] (8)

[0086] (9).

[0087] In step 2, the position calibration module uses the position information P0 of each object in S0 as prior information, and then calibrates the position information of each member in S1. The specific method is as follows:

[0088] Step 2.1A: Clear P1_modify;

[0089] Step 2.2A: Determine whether S1 is empty. If yes, proceed to step 2.7A. If no, obtain a member K1 from S1 and delete the member from S1.

[0090] Step 2.3A: Obtain the two initial position information of member K, P0_K1 and P1_K1;

[0091] Step 2.4A: Select member K2 from S0 that is closest to P0_K, and select member K3 that is closest to P1_K;

[0092] Step 2.5A: Trigger base station scheduling members K1 and K2, K1 and K3 to perform sidelink measurements, and obtain the path loss measurement results of K1 and K2, K1 and K3 from the base station: Measure_1_to_2, Measure_2_to_1, Measure_1_to_3, Measure_3_to_1;

[0093] Step 2.6A, if

[0094] (Measure_1_to_2+Measure_2_to_1)>(Measure_1_to_3+Measure_3_to_1),

[0095] If the position of member K1 is corrected to P1_K1, then the position of member K1 is corrected to P0_K1, and K1 and its position information are written to P1_modify. Then, the process jumps to step 2.2A.

[0096] Step 2.7A: Output P1_modify.

[0097] In step 2, the position calibration module uses the position information P0 and P1_modify of each object in S0 and S1 as prior information to estimate the position information of each member in S2 to obtain P2_estimate. The specific steps are as follows:

[0098] Step 2.1B: Clear P2_estimate, merge P0 and P1_modify information into P_combine. Each member includes the terminal ID and its unique location coordinates. Divide the area to be monitored into F grids according to the preset grid size. Each grid has unique coordinates and number.

[0099] Step 2.2B: Determine whether S2 is empty. If it is, proceed to step 2.7B. If not, obtain a member K1 from S2 and delete the member from S2.

[0100] Step 2.3B: Obtain the access point AP_i where member K1 resides, where i takes values ​​of 0, ..., I-1, and I is the number of access points where K1 resides;

[0101] Step 2.4B: Trigger the base station to schedule Terminal_i_j and K1, which are stationed under AP_i and belong to P_combine, to perform sidelink measurements. Obtain the path loss measurement results Measure_i_j_to_K1 and Measure_K1_to_i_j from the base station. Measure_i_j_to_K1 is the path loss measurement value from terminal j stationed under AP_i to member K1, and Measure_K1_to_i_j is the path loss measurement value from K1 to terminal j stationed under AP_i.

[0102] Step 2.5B: Select the P terminals with the smallest value of (Measure_i_j_to_K1 + Measure_K1_to_i_j) from i and j, and define the terminals. The value of p can be 0, ..., P-1;

[0103] Step 2.6B: Select the cell from the F cells that satisfies the terminal condition. With the origin of the coordinate system,

[0104] (Measure_) _to_K1+Measure_K1_to_ ) / 2

[0105] For cells with path loss, the center coordinates of the cell are used as member K1 relative to the terminal. Candidate location coordinate set The The number of grids is defined as Then, the estimated position coordinates Axis_K1 of terminal K1 are calculated according to the following formula:

[0106] tmp = +inf; +inf represents positive infinity.

[0107] for ( =0; < -1; ++)(10)

[0108] {

[0109] for ( =1; < -1; ++)

[0110] { ......

[0111] for ( =1; < -1; ++)

[0112] {

[0113] if ( <tmp)

[0114] {

[0115] tmp = ,

[0116] ,

[0117] }

[0118] }

[0119] }

[0120] }

[0121] Axis_K1 =

[0122] distance(A,B) calculates the distance between coordinates A and coordinates B. To calculate the average of P 3D coordinates, the formula means: from each candidate location coordinate set... Each cell is selected to form a combination containing P cells. The cumulative value of the center coordinate distance between each pair of cells in each combination is calculated. The combination with the smallest cumulative value is selected. The mean coordinate of the P cells in the corresponding combination is calculated as the position coordinate Axis_K1 of member K1. Member K1 and its estimated coordinate Axis_K1 are written into P2_estimate, and then the process jumps to step 2.2B.

[0123] Step 2.7B: Output P2_estimate.

[0124] In step 3, the fence event triggering monitoring includes, but is not limited to, the location being located within the target area and the location remaining within the target area for a time greater than a threshold T.

[0125] The following specific embodiments describe a detailed implementation of an electronic fence management device:

[0126] Example: Figure 3 As shown, this embodiment includes a 15-story building (without underground activity space). Four access points are deployed on each floor. Taking the first floor as an example: the four access points are access point 0, access point 1, access point 2, and access point 3. Access point 0 is the main station, and access points 1, 2, and 3 are secondary stations. The location coordinates of the main station are... The coordinates of access points 1, 2, and 3 of the secondary station are (80, 80, 5), (80, 0, 5), and (0, 0, 5), respectively. The monitored area on each floor is divided into 64 grids (i.e., the F value mentioned in steps 2.1B and 2.6B is 64), numbered sequentially as 0, 1, ..., 62, 63. The grid numbers corresponding to the electronic fence area are 18, 19, 20, 21, 26, 27, 28, 29, 34, 35, 36, and 37. At a certain moment, there are a total of 8 terminals residing in the monitored area, namely UE0, UE1, UE2, UE3, UE4, UE5, UE6, and UE7. Among them, UE7 (not on the first floor) is classified into the reliable object set S0 at that moment after deviation calculation, with coordinates (35, 75, 79.5). The electronic fence management process for other UEs is described below:

[0127] As shown in the diagram, due to the obstruction of building 2, the signal path between UE0 and access point 2, and between UE3 and access point 2, is not direct. Ultimately, UE0's signal reaches access point 2 after reflection from building 1, and UE3's signal reaches access point 2 after reflection from building 3. This means that the arrival time between UE0 and access point 2 is inaccurate because it is not a direct path, directly causing UE0 to fail to locate. Similarly, the arrival time between UE3 and access point 2 is also inaccurate due to the non-direct path, directly causing UE3 to fail to locate. (If existing technical solutions are used, more access points would be deployed to increase the number of measurement nodes and avoid the impact of non-line-of-sight transmission, ensuring the number of nodes for line-of-sight transmission, which would significantly increase costs). This situation directly leads to a large number of false alarms in the application of the electronic fence system. The high failure rate and low detection rate make it difficult to perform fence monitoring tasks effectively. This invention aims to solve this problem. The specific approach is as follows: By measuring the deviation, the monitored objects are divided into sets of objects with different reliability levels (i.e., reliable object set S0, sub-reliable object set S1, and unreliable object set S2). Then, through iteration, using the location information of the reliable object set as prior information, the location information of the unreliable object set is self-calibrated (i.e., the reliable object set S0 is used to calibrate the sub-reliable object set S1, and the reliable object set S0 and the calibrated sub-reliable object set S1 are used to calibrate the unreliable object set S2). This achieves mutual calibration between objects in the electronic fence system, thereby improving the accuracy of electronic fence monitoring. This invention effectively improves the accuracy of electronic fence monitoring without increasing the hardware facilities of the electronic fence. The specific implementation process is described below:

[0128] At a certain point in time, the measurement values ​​of the objects to be tracked reported by each access point on the first floor are detailed in Table 2. Then, the electronic fence location calculation module calculates the distance from the object to be tracked to the secondary station i minus the distance from the object to the main station. The calculation results are detailed in Table 3. Then, the calculations for the four access nodes are performed according to equation (1). This yields i = 0, 1, 2, 3. The values ​​are 6449, 12825, 6425, and 25 respectively. Then, the values ​​of the seven UEs are calculated according to equation (2). The values ​​are given, where i is 1, 2, or 3. The calculation results are detailed in Table 1. Then, matrix A is calculated according to equation (3) to obtain...

[0129]

[0130] Next, according to equation (4), the matrix C of the 7 UEs is calculated, as detailed in Table 1;

[0131] Next, according to equation (5), the matrix D of the 7 UEs is calculated, as detailed in Table 1;

[0132] Next, according to formula (6), calculate a1, a2, a3, b1, b2, and b3 for the seven UEs. See Table 1 for details.

[0133] Next, according to equation (7), calculate Q1, Q2, and Q3 for the seven UEs, as detailed in Table 1;

[0134] Next, according to equation (8), calculate the 7 UEs. See Table 1 for details;

[0135] Next, according to equation (9), the W values ​​of the seven UEs are calculated, as detailed in Table 1;

[0136] Next, according to equation (6), calculate the position coordinates (x, y, z) of the 7 UEs.

[0137] After completing the above operations from equation (1) to equation (9), we can obtain the W value and (x, y, z) value of each of the 7 UEs (see Table 1 for details). In this embodiment, there is no activity space on the underground floor in the monitoring location. Therefore, in Table 1, the coordinates with negative z coordinates of UE4, UE5, and UE6 are directly discarded. That is to say, UE4, UE5, and UE6 also have only one coordinate. Then, based on the operation in step 1, the reliability level is divided and the initial position is calculated. The specific method is as follows:

[0138] Referring to the data in Table 1, the two coordinates of UE2 are as follows:

[0139] P0_K1=(65.0002, 75.0004, 1.4959),

[0140] If P1_K1 = (64.9282, 74.8092, 4.8512), then the distance between the two coordinates is...

[0141] =3.3615. Since this value is less than the threshold 1 (3.5 in this embodiment, but the specific value is determined by the positioning accuracy requirement, and is generally half of the positioning accuracy requirement), the deviation of the UE is determined to be 0, and the coordinates of UE2 are adjusted to ((65.0002, 75.0004, 1.4959) + (64.9282, 74.8092, 4.8512)) / 2 = (64.9642, 74.9048, 3.1736). In addition, after removing invalid coordinates, UE4, UE5, and UE6 each have only one coordinate, so these three UEs also belong to the reliable set S0. In addition, it has been assumed that UE7 belongs to S0 at this time, and the coordinates of UE7 are (35, 75, 79.5). Therefore, the members of the reliable object set S0 are: UE2, UE4, UE5, UE6, and UE7.

[0142] For UE1, the distance between its two location coordinates can be calculated using the aforementioned method to be 78.2462, which is greater than the threshold 1. Therefore, the deviation of this UE is threshold 1, and it is assigned to the sub-reliable object set S1. This UE includes two initial location coordinates, namely (32.4070, 80.6601, 78.1173) and (34.9999, 65.0001, 1.4981).

[0143] Since there is no solution for UE0 and UE3, they are directly assigned to the unreliable object set S2.

[0144] Next, following the methods in steps 2.1A to 2.7A, the position of the S1 member is calibrated using the prior position information of the S0 member. That is, the position coordinates of UE1 are calibrated using the S0 member information. First, from the S0 members, the UE closest to the candidate coordinate 1 (34.9999, 65.0001, 1.4981) of UE1 is selected. Since the distances of UE2, UE4, UE5, UE6, and UE7 to this coordinate are 31.6033, 36.4007, 40.0001, 42.7201, and 78.6403, respectively. Therefore, UE2 is closest to this coordinate; next, from the S0 members, the UE closest to candidate coordinate 2 (32.4070, 80.6601, 78.1173) of UE1 is selected. Since the distances of UE2, UE4, UE5, UE6, and UE7 to this coordinate are 81.9125, 89.1221, 94.7355, 95.5131, and 6.3775 respectively, UE7 is closest to this coordinate; next, the base station schedules members UE1 and UE2, and UE1 and UE7 to perform sidelink measurements, and obtains the path loss measurement results of UE1 and UE2, and UE1 and UE7 from the base station: Measure_UE1_to_UE2=6, Measure_UE2_to_UE1=7, Measure_UE1_to_UE7=16, Measure_UE7_to_UE1=13; then according to the judgment criterion in step 2.6A, since

[0145] (Measure_UE1_to_UE2+Measure_UE2_to_UE1) = 6+7 = 13

[0146] <(Measure_UE1_to_UE7+Measure_UE7_to_UE1) = 16+13 = 29,

[0147] Therefore, the coordinates of UE1 are determined to be (34.9999, 65.0001, 1.4981), and the position calibration of the sub-reliable object set S1 is now complete.

[0148] Next, following the methods in steps 2.1B to 2.7B, using the position information P0 and P1_modify of each object in S0 and S1 as prior information, the position information of each member in S2 is estimated to obtain P2_estimate. First, P0 and P1_modify are merged into P_combine. It can be seen that P_combine includes members: UE1, UE2, UE4, UE5, UE6, and UE7. The unreliable object set S2 includes two members: UE0 and UE3. Therefore, one unreliable object is first retrieved. Let's say UE0 is retrieved first. Then, the access points where UE0 resides are obtained as access point 0, access point 1, access point 2, and access point 3, i.e., I is set to 4 in step 2.3B. Next, the base station is triggered to schedule Terminal_i_j, which resides under access points 0, 1, 2, and 3 and belongs to P_combine, to perform sidelink measurements with UE0. In this implementation, all terminals in P_combine are under the access points where UE0 resides. Therefore, the base station is directly triggered to schedule UE1, UE2, UE4, UE5, UE6, and UE7 to perform sidelink measurements with UE0. The measurements are then taken to obtain Measure_UE1_to_UE0, Measure_UE2_to_UE0, Measure_UE4_to_UE0, Measure_UE5_to_UE0, Measure_UE6_to_UE0, Measure_UE7_to_UE0, Measure_UE0_to_UE1, Measure_UE0_to_UE2, Measure_UE0_to_UE4, Measure_UE0_to_UE5, Measure_UE0_to_UE6, and Measure_UE0_to_UE7. Next, from the following six sets of data, the three sets with the smallest values ​​are selected:

[0149] (Measure_UE1_to_UE0+Measure_UE0_to_UE1),

[0150] (Measure_UE2_to_UE0+Measure_UE0_to_UE2),

[0151] (Measure_UE4_to_UE0+Measure_UE0_to_UE4),

[0152] (Measure_UE5_to_UE0+Measure_UE0_to_UE5),

[0153] (Measure_UE6_to_UE0+Measure_UE0_to_UE6),

[0154] (Measure_UE7_to_UE0+Measure_UE0_to_UE7)

[0155] refer to Figure 4 The schematic representation of the nearest neighbor relationship shows that the smallest value selected in this embodiment is (Measure_UE1_to_UE0+Measure_UE0_to_UE1).

[0156] (Measure_UE2_to_UE0+Measure_UE0_to_UE2),

[0157] (Measure_UE4_to_UE0+Measure_UE0_to_UE4),

[0158] Therefore, UE1, UE2, and UE4 are considered to be the components in step 2.5B. The value of p is 0, 1, or 2, that is... Corresponding to UE1, Corresponding to UE2, Corresponding to UE4. For example... Figure 4 As shown, this invention will use UE1, UE2, and UE4 to estimate the position of UE0. Then, according to step 2.6B, with UE1 as the center and (Measure_UE1_to_UE0+Measure_UE0_to_UE1) / 2 path loss as a reference, the location is found. Figure 4 In this embodiment, the cells that satisfy the path loss relationship are: cells 1, 2, 3, 4, 5, 13, 21, 29, 37, 36, 35, 34, 33, 25, 17, and 9. This cell set is defined as GroupUE1. Then, with UE2 as the center and the path loss of (Measure_UE2_to_UE0 + Measure_UE0_to_UE2) / 2 as a reference, the following is found: Figure 4 In this embodiment, the cells that satisfy the path loss relationship are cells 5, 13, 21, 22, and 23. This cell set is defined as GroupUE2. Then, with UE4 as the center and the path loss of (Measure_UE4_to_UE0 + Measure_UE0_to_UE4) / 2 as a reference, the following cells are identified: Figure 4In this embodiment, the cells that satisfy the path loss relationship are cells 7, 6, 5, 4, 12, 20, 28, 36, 37, 38, and 39. This cell set is defined as GroupUE4. Then, according to the calculation logic of equation (10), cells are selected from GroupUE1, GroupUE2, and GroupUE4.

[0159] ,

[0160] and through

[0161] Axis_K1 =

[0162] The estimated coordinates of UE0 are calculated. The estimation results in this embodiment are as follows: Figure 4 As shown, the estimated coordinates of UE0 are grid 5. Using the same method, the estimated coordinates of UE3 are grid 21.

[0163] Finally, the electronic fence event triggering module determines that UE1 and UE3 are inside the fence, and therefore triggers an alarm event.

[0164] As can be seen from the above embodiments, this invention divides the objects to be monitored into sets of objects with different reliability levels (i.e., reliable object set S0, sub-reliable object set S1, and unreliable object set S2) by measuring the deviation. Then, through iteration, using the location information of the objects in the reliable object set as prior information, it performs self-calibration on the location information of the objects in the unreliable object set (i.e., using the reliable object set S0 to calibrate the sub-reliable object set S1, and using the reliable object set S0 and the calibrated sub-reliable object set S1 to calibrate the unreliable object set S2). This achieves mutual calibration between objects in the electronic fence system to improve the accuracy of electronic fence monitoring. Using the method of this invention, the accuracy of electronic fence monitoring can be effectively improved without increasing the hardware facilities of the electronic fence.

[0165] Table 27 UE arrival time difference measurements

[0166]

[0167] Table 37 shows the conversion results of arrival distance difference for each UE.

[0168]

[0169] Table 47 UEs Value calculation results

[0170]

[0171] Table 17 shows the calculation results for UE C / D / a / b / AA / BB / CC.

[0172]

[0173] The above are merely preferred embodiments of this application and are not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

[0174] While the specific embodiments of this application have been described above in conjunction with the accompanying drawings, this is not intended to limit the scope of protection of this application. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art without creative effort based on the technical solutions of this application are still within the scope of protection of this application.

Claims

1. A method for managing electronic fences, characterized in that, The electronic fence management system, which consists of an electronic fence location calculation module, an electronic fence location self-calibration module, and an electronic fence event triggering module, includes the following steps: Step 1: The electronic fence location calculation module calculates the measurement deviation of each tracked object based on the measurement values ​​of the tracked objects reported by each access point, and divides the tracked objects into a reliable object set S0, a secondary reliable object set S1, and an unreliable object set S2 based on the measurement deviation. It also estimates the location information set P0 corresponding to each member of the reliable object set S0 and the initial location information set P1 corresponding to each member of the secondary reliable object set S1. Step 2: The electronic fence position self-calibration module uses the position information P0 of each object in S0 as prior information to calibrate the position information of each member in S1, and obtains the calibrated position information P1_modify of the members in S1. Then, using the position information P0 and P1_modify of each object in S0 and S1 as prior information, the position information of each member in S2 is estimated to obtain P2_estimate. Step 3: The electronic fence event triggering module uses location information P0 to monitor electronic fence event triggering for members of object set S0, uses location information P1_modify to monitor electronic fence event triggering for members of object set S1, and uses location information P2_estimate to monitor electronic fence event triggering for members of object set S2. In step 2, the position calibration module uses the position information P0 of each object in S0 as prior information, and then calibrates the position information of each member in S1. The specific method is as follows: Step 2.1A: Clear P1_modify; Step 2.2A: Determine whether S1 is empty. If yes, proceed to step 2.7A. If no, obtain a member K1 from S1 and delete the member from S1. Step 2.3A: Obtain the two initial position information of member K, P0_K1 and P1_K1; Step 2.4A: Select member K2 from S0 that is closest to P0_K, and select member K3 that is closest to P1_K; Step 2.5A: Trigger base station scheduling members K1 and K2, K1 and K3 to perform sidelink measurements, and obtain the path loss measurement results of K1 and K2, K1 and K3 from the base station: Measure_1_to_2, Measure_2_to_1, Measure_1_to_3, Measure_3_to_1; Step 2.6A, if (Measure_1_to_2+Measure_2_to_1)>(Measure_1_to_3+Measure_3_to_1), If the position of member K1 is corrected to P1_K1, then the position of member K1 is corrected to P0_K1, and K1 and its position information are written to P1_modify. Then, the process jumps to step 2.2A. Step 2.7A: Output P1_modify; In step 2, the position calibration module uses the position information P0 and P1_modify of each object in S0 and S1 as prior information to estimate the position information of each member in S2 to obtain P2_estimate. The specific steps are as follows: Step 2.1B: Clear P2_estimate, merge P0 and P1_modify information into P_combine, each member includes the terminal ID and its unique location coordinates, and divide the area to be monitored into F grids according to the preset grid size, each grid having unique coordinates and number; Step 2.2B: Determine whether S2 is empty. If it is, proceed to step 2.7B. If not, obtain a member K1 from S2 and delete the member from S2. Step 2.3B: Obtain the access point AP_i where member K1 resides, where i takes values ​​of 0, ..., I-1, and I is the number of access points where K1 resides; Step 2.4B: Trigger the base station to schedule Terminal_i_j and K1, which are stationed under AP_i and belong to P_combine, to perform sidelink measurements. Obtain the path loss measurement results Measure_i_j_to_K1 and Measure_K1_to_i_j from the base station. Measure_i_j_to_K1 is the path loss measurement value from terminal j stationed under AP_i to member K1, and Measure_K1_to_i_j is the path loss measurement value from K1 to terminal j stationed under AP_i. Step 2.5B: Select the P terminals with the smallest value of (Measure_i_j_to_K1 + Measure_K1_to_i_j) from i and j, and define the terminals. The value of p can be 0, ..., P-1; Step 2.6B: Select the cell from the F cells that satisfies the terminal condition. With the origin of the coordinate system, (Measure_ _to_K1+Measure_K1_to_ ) / 2 For cells with path loss, the center coordinates of the cell are used as member K1 relative to the terminal. Candidate location coordinate set The The number of grids is defined as From each candidate location coordinate set Each cell is selected to form a combination containing P cells. The cumulative value of the center coordinate distance between each pair of cells in each combination is calculated. The combination with the smallest cumulative value is selected. The mean coordinate of the P cells in the corresponding combination is calculated as the position coordinate Axis_K1 of member K1. Member K1 and its estimated coordinate Axis_K1 are written into P2_estimate, and then the process jumps to step 2.2B. Step 2.7B: Output P2_estimate.

2. The electronic fence management method according to claim 1, characterized in that: In step 1, the measured value is the time difference of arrival. The specific method for the electronic fence location calculation module to divide the reliable object set S0, the secondary reliable object set S1, and the unreliable object set S2, and to estimate the location information set P0 corresponding to each member of the reliable object set S0 and the initial location information set P1 corresponding to each member of the secondary reliable object set S1 is as follows: Based on the formulas (1) to (9), the W value and the (x, y, z) value are calculated, and then the following processing is performed: If the number of arrival time difference measurements of a UE is less than 4 or the W value calculated by equation (9) is less than 0, then the deviation of the UE is infinite and the UE is assigned to the unreliable object set S2. At this time, the UE has no initial position coordinates. If the W value calculated by equation (9) is equal to 0, then the deviation of the UE is 0, the UE is assigned to the reliable object set S0, and the user's location coordinates (x, y, z) are calculated according to equation (6). The user's location coordinates are unique and are put into the location information set P0. If two values ​​are obtained according to equation (8), then the two initial position coordinates (x_pos0, y_pos0, z_pos0) and (x_pos1, y_pos1, z_pos1) of the UE are obtained according to equation (6). Then, the distance between these two coordinates, Distance_pos0_to_pos1, is calculated. ， If Distance_pos0_to_pos1 < threshold1, the deviation of this UE is 0, this UE is classified into the reliable object set S0, and the unique position coordinate of this UE is calculated according to ((x_pos0, y_pos0, z_pos0) + (x_pos1, y_pos1, z_pos1)) / 2 and put into the position information set P0; If Distance_pos0_to_pos1 ≥ threshold1, the deviation of this UE is threshold1, it is classified into the "sub - reliable object set S1", and (x_pos0, y_pos0, z_pos0) and (x_pos1, y_pos1, z_pos1) are used as the two initial position coordinates of this UE and put into the initial position information set P1; In step 1, in equations (1) to (9), Main station coordinates Here are the coordinates of the secondary station i, where i takes values ​​of 1, 2, or 3. The distance difference is the distance from the object to be tracked to the main station minus the distance from the object to be tracked to the secondary station i. (1) (2) (3) （4） （5） （6） (7) (8) （9）。 3. An electronic fence management method according to claim 1, wherein: In the step 3, the fence event trigger monitoring includes but is not limited to that the located position is within the target area and the time that the located position continuously stays within the target area is greater than the threshold T.

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