A method, system, device, and medium for screening abnormal receiving devices based on TDOA positioning.

Abstract

A method, system, device, and medium for screening abnormal receiving devices based on TDOA positioning are disclosed. The method includes: solving for the intersection points of the TDOA positioning hyperbola; screening for abnormal intersection points; classifying all the screened intersection points; calculating the dispersion of the classification results; performing weighted dispersion processing; and screening for abnormal receiving devices based on the weighted results. The system, device, and medium are based on the TDOA positioning abnormal receiving device screening method to screen for abnormal receiving devices, effectively reducing the interference of abnormal TDOA values ​​on the positioning results, thereby improving the accuracy and stability of the overall positioning system.

Description

Technical Field

[0001] This invention belongs to the field of passive system positioning technology, and particularly relates to a method, system, device and medium for screening abnormal receiving devices based on TDOA positioning. Background Technology

[0002] In critical defense areas, such as airports and military bases, it is essential to detect and locate abnormal signals within these areas to ensure overall control of the electromagnetic security situation. Passive positioning technology is a technique that estimates the location of a radiation source by passively measuring its electromagnetic parameters. Compared to traditional radar and sonar positioning systems, passive positioning offers advantages such as longer positioning range, lower cost, and greater concealment. Therefore, passive positioning technology has wide applications in both civilian and military systems.

[0003] The accuracy of passive positioning is primarily affected by the quality of input parameters and the performance of the positioning parsing algorithm. In recent years, researchers both domestically and internationally have conducted extensive research on passive positioning algorithms, resulting in relatively mature algorithms. However, research on the quality of positioning parameters is scarce. In practical applications, receiving devices may be obstructed by buildings, vegetation, vehicles, or other objects, leading to poor signal quality and affecting the accuracy of positioning parameters. Secondly, the stability of the receiving device itself, such as crystal oscillator frequency drift, clock synchronization errors, and receiver performance issues, can also lead to abnormal positioning parameters. More seriously, damage to the receiving device often causes it to fail to receive signals normally, resulting in abnormal positioning parameters. Without dynamically eliminating these abnormal positioning parameters, high-precision positioning cannot be achieved. Dynamically eliminating abnormal receiving devices is a crucial step in dealing with abnormal positioning parameters. By analyzing the characteristics and causes of abnormal positioning parameters, potentially problematic receiving devices can be identified, and their resulting positioning data can be promptly eliminated, thus ensuring the accuracy and reliability of the positioning system. Therefore, identifying and handling the causes of abnormal TDOA parameters and abnormal receiving devices has become a key issue in improving positioning accuracy.

[0004] Defects and shortcomings of existing technology:

[0005] First, current positioning technologies primarily improve positioning accuracy by enhancing the performance of positioning parsing algorithms, but rarely consider the impact of abnormal positioning parameters on accuracy. Second, existing technologies mainly filter out abnormal TDOA parameters; however, in practical applications, abnormal TDOA parameters are primarily caused by malfunctions in the receiving device. If abnormal receiving devices are not filtered, the device will output a series of abnormal TDOA parameters. Summary of the Invention

[0006] In order to overcome the shortcomings of the prior art, the purpose of this invention is to provide a method, system, device and medium for screening abnormal receiving devices based on TDOA positioning. By analyzing the characteristics and causes of abnormal positioning parameters, the invention identifies receiving devices that may have problems and promptly removes the positioning data generated by them, effectively reducing the interference of abnormal TDOA values ​​on the positioning results, thereby improving the accuracy and stability of the overall positioning system.

[0007] To achieve the above objectives, the present invention adopts the following technical solution:

[0008] The method for screening abnormal receiving devices based on TDOA positioning includes the following steps:

[0009] Step 1: Solve for the intersection of the hyperbolas using TDOA;

[0010] Step 2: Filter out abnormal intersections from all the intersections obtained in Step 1;

[0011] Step 3: Classify all intersections after filtering in Step 2;

[0012] Step 4: Calculate the dispersion of the intersection point classification results from Step 3;

[0013] Step 5: Perform dispersion weighting on the calculation results of Step 4;

[0014] Step 6: Screen abnormal receiving devices based on the weighted results of Step 5.

[0015] The specific method for step one is as follows:

[0016] During TDOA positioning, N receiving devices can collect N sets of data, which will form N(N-1) / 2 TDOA values. Each TDOA value can form a positioning hyperbola about the target source location, resulting in a total of N(N-1) / 2 positioning hyperbolas. These N(N-1) / 2 positioning hyperbolas will intersect at multiple points. Before calculating the coordinates of the intersection points, it is determined whether any two positioning hyperbolas intersect. The specific steps are as follows:

[0017] 1) List the equations of any two locating hyperbolas, their equations are as follows:

[0018]

[0019] Among them, u=[x,y] T Let s be the coordinates of the signal source. i =[x i ,y i ] T Let r be the coordinates of the i-th receiving device. ijThe time difference between the signal source arriving at the i-th and j-th receiving devices is multiplied by the electromagnetic wave propagation speed; 2) For F ij and F kg Taking the first-order partial derivatives respectively, we get:

[0020]

[0021] 3) Select the centroid u of the receiving device coordinates. (0) As an initial value, at the centroid u (0) Performing a Taylor series expansion at this point, we obtain the approximate system of equations:

[0022] F(u)=F(u (0) )+F'(u (0) (uu) (0) )=0 (1.3)

[0023] Therefore, the iterative solution is obtained as follows:

[0024] u (1) =u (0) -[F'(u 0 ) T F'(u 0 )] -1 F'(u 0 ) T F(u 0 (1.4)

[0025] u (1) This is the result of the first iteration; at this point, u... (1) Using this as the initial value, repeat step 3) above iteratively a times to obtain a iteration results, u (1) u (2) 、…、u (a) Take the results of the next b (b < a) iterations and determine:

[0026]

[0027] Is it true or false? If not, it means there is no intersection; if true, then u... (a) Substituting into equation (1.1), and using the manually set thresholds a, b, ε, and β, determine F. ij <β and F kg If both <β are true, then there is an intersection point, and this value is the coordinate of the intersection point; otherwise, there is no intersection point.

[0028] Based on steps 1) to 3), determine whether any two of the N(N-1) / 2 positioning hyperbolas intersect, and if they do intersect, find the coordinates of the intersection point; traverse all positioning hyperbolas and find the coordinates of all intersection points.

[0029] The specific method for step two is as follows:

[0030] All intersection points obtained in step one that are not suitable for discreteness calculation are removed. The principle of removal is based on the magnitude of the tangent angle between the two positioning hyperbolas at the intersection point:

[0031] The slopes of the two positioning hyperbolas at their intersection are:

[0032]

[0033] Among them, [x h ,y h ] T Given the coordinates of the intersection point, the angle of the tangent is calculated as follows:

[0034]

[0035] When K is greater than 90°, let T = 180° - K; otherwise, let T = K; set a threshold ξ, the value of which is in the range of 15° to 25°, and when T < ξ, the intersection point is considered abnormal.

[0036] The specific method for step three is as follows:

[0037] After filtering in step two, all intersection points are classified. Assuming N receiving devices are deployed, resulting in M ​​intersection points, let C represent the set of these M intersection points. Let Ci represent the set of all hyperbolic intersection points formed by receiving device i. i This indicates that for set C and set C' i Perform the difference operation, i.e., C no_i =CC i Then C no_i Let C be the set of intersection points of the hyperbolas formed without the participation of receiving device i, where 1 ≤ i ≤ N; then calculate set C. no_i The number of intersection points, expressed by P. no_1 , ..., P no_i , ..., P no_N Let C represent the sets respectively. no_1 C no_i C no_N The number of intersection points is represented by P1, ..., P2. i , ..., P N Let C1, ..., C be sets respectively. i C N The number of intersection points, where P i The maximum value is P i_max =(N 3 -3N 2 +2N) / 2.

[0038] The specific method for step four is as follows:

[0039] Based on the classification of intersection points in step three, set C is... no_i The dispersion is calculated using the following formula:

[0040]

[0041] Among them, [x no_i (k),x no_i [k] is represented by set C. no_i The coordinates of the kth intersection point.

[0042] The specific method for step five is as follows:

[0043] Through P i For S no_i After weighting, the formula is as follows:

[0044]

[0045] The specific method for step six is ​​as follows:

[0046] By analyzing P i and S′ noi The method for identifying abnormal receiving devices involves two steps: First, determine P... i Size, as can be seen from the above analysis, P i The maximum value is P i_max Set threshold The value ranges from 1 / 3 to 1 / 2, when P i Less than If the i-th receiving device is faulty, then proceed to the second step; otherwise, check S′. noi To identify abnormal receiving devices, a threshold χ is set, with χ ranging from 3 to 4. When the condition χS′ is met... no_i ≤S′ no_l If 1≤l≤N and l≠i, then the i-th receiving device is determined to be faulty.

[0047] A system for screening abnormal receiving devices based on TDOA positioning includes:

[0048] The TDOA module for finding the intersection of hyperbolas is used in step one to find the intersection of hyperbolas using Newton's iteration method.

[0049] The abnormal intersection filtering module is used in step two to filter abnormal intersections by judging the tangent angle between any two positioning hyperbolas at their intersection.

[0050] The intersection classification module is used in step three to classify intersections by determining which receiving device generated them.

[0051] The discreteness calculation module is used in step four to calculate the discreteness of the classified intersection points based on the classification of intersection points in step three.

[0052] The dispersion weighting module is used in step five, through P i By weighting the dispersion, a more objective description of abnormal receiving devices can be achieved.

[0053] The abnormal receiving device filtering module is used in step six to filter abnormal receiving devices.

[0054] A device for screening abnormal receiving devices based on TDOA positioning, comprising:

[0055] Memory, used to store computer programs;

[0056] A processor is used to implement the abnormal receiving device screening method based on TDOA positioning described in steps 1 to 6 when executing the computer program.

[0057] A computer-readable storage medium storing a computer program, which, when executed by a processor, is capable of screening abnormal receiving devices based on the TDOA-based abnormal receiving device screening method described in steps 1 to 6.

[0058] Compared with the prior art, the present invention has the following advantages:

[0059] First, existing positioning technologies primarily improve positioning accuracy by enhancing the performance of positioning parsing algorithms, but rarely consider the impact of abnormal positioning parameters on accuracy. Second, existing technologies mainly filter abnormal TDOA parameters; however, in practical applications, abnormal TDOA parameters are primarily caused by malfunctions in the receiving device. If abnormal receiving devices are not filtered, they will output a series of abnormal TDOA parameters. This invention, by analyzing the characteristics and causes of abnormal positioning parameters, can identify potentially problematic receiving devices and promptly remove their positioning data, thereby ensuring the accuracy and reliability of the positioning system. Attached Figure Description

[0060] Figure 1 This is a flowchart of the abnormal receiving device screening process of the present invention.

[0061] Figure 2 This is a graph showing the intersection points of various curves when the error of the receiving device 1 of the present invention is 1000ns.

[0062] Figure 3 This is a diagram of abnormal intersection points when the error of receiving device 1 in this invention is 1100ns.

[0063] Figure 4 The coordinates of the signal source in this invention are [-200, 300]. T Intersection dispersion diagram.

[0064] Figure 5 The coordinates of the signal source in this invention are [-200, -300]. T Intersection dispersion diagram.

[0065] Figure 6 The coordinates of the signal source in this invention are [200, -300]. T Intersection dispersion diagram.

[0066] Figure 7 The coordinates of the signal source in this invention are [0,0]. T Intersection dispersion diagram. Detailed Implementation

[0067] The present invention will be further described in detail below with reference to the accompanying drawings. See the flowchart for details. Figure 1 .

[0068] N receiving devices are deployed within a certain core area, where the coordinates of the i-th receiving device are s. i =[x i ,y i ] T For any i ≤ N, there exists an anomalous signal source within the core region, with coordinates u = [x, y]. T N receiving devices can collect N sets of data. Each pair of data sets undergoes cross-correlation to generate one TDOA value, resulting in a total of... One TDOA value. According to the formula:

[0069] ||us i ||2-||us j ||2-r ij =0

[0070] It can be seen that each TDOA value can form a hyperbola about the target source location, and a total of [number] hyperbolas can be formed. A hyperbola. When a receiving device 1 malfunctions, the TDOA value generated by that device will have a significant deviation. The intersection point of the hyperbola formed by the large TDOA value with other hyperbolas will deviate from the signal source location or even be non-intersecting. The principle of screening abnormal receiving devices is to analyze the number and dispersion of intersection points to identify abnormal receiving devices. See [link to relevant documentation]. Figure 2 .

[0071] A method for screening abnormal receiving devices based on TDOA positioning, comprising:

[0072] Step 1: Solving for the intersection of the hyperbolas using TDOA:

[0073] During TDOA positioning, N receiving devices can collect N sets of data, which will form N(N-1) / 2 TDOA values. Each TDOA value can form a positioning hyperbola about the target source location, resulting in a total of N(N-1) / 2 positioning hyperbolas. These N(N-1) / 2 positioning hyperbolas will intersect at multiple points. Before calculating the coordinates of the intersection points, it is necessary to determine whether any two positioning hyperbolas intersect. The method used for this determination is Newton's iteration method. The specific steps of Newton's iteration method are as follows:

[0074] 1) List the equations of any two locating hyperbolas, their equations are as follows:

[0075]

[0076] Among them, u=[x,y] T Let s be the coordinates of the signal source. i =[x i ,y i ] T Let r be the coordinates of the i-th receiving device. ij The time difference between the signal source arriving at the i-th and j-th receiving devices is multiplied by the electromagnetic wave propagation speed; 2) For F ij and F kg Taking the first-order partial derivatives respectively, we get:

[0077]

[0078] 3) Select the centroid u of the receiving device coordinates. (0) As an initial value, at the centroid u (0) Performing a Taylor series expansion at this point, we obtain the approximate system of equations:

[0079] F(u)=F(u (0) )+F'(u (0) (uu) (0) )=0 (1.3)

[0080] Therefore, the iterative solution is obtained as follows:

[0081] u (1) =u (0) -[F'(u 0 ) T F'(u 0 )] -1 F'(u 0 ) T F(u 0 (1.4)

[0082] u (1) This is the result of the first iteration; at this point, u... (1) Using this as the initial value, repeat step 3) above iteratively a times to obtain a iteration results, u (1) u (2) 、…、u (a) Take the results of the next b (b < a) iterations and determine:

[0083]

[0084] Is it true or false? If not, it means there is no intersection; if true, then u... (a) Substitute into equation (1.1) and determine F. ij <β and F kg If both <β are true, it means there is an intersection point, and this value is the coordinate of the intersection point; otherwise, it means there is no intersection point.

[0085] Steps 1) to 3) above can determine whether any two positioning hyperbolas among N(N-1) / 2 positioning hyperbolas intersect, and if they do intersect, how to obtain the coordinates of the intersection point. This process is then repeated across all positioning hyperbolas to find the coordinates of all intersection points. Here, a, b, ε, and β are manually set threshold values.

[0086] Step 2: Filter out abnormal intersections from all intersections obtained in Step 1:

[0087] All intersection points obtained in step one that are not suitable for discreteness calculation are removed. The principle of removal is based on the magnitude of the tangent angle between the two positioning hyperbolas at the intersection point:

[0088] The slopes of the two positioning hyperbolas at their intersection are:

[0089]

[0090] Among them, [x h ,y h ] T Given the coordinates of the intersection point, the angle of the tangent is calculated as follows:

[0091]

[0092] When K is greater than 90°, let T = 180° - K; otherwise, let T = K; set a threshold ξ, the value of which ranges from 15° to 25°. When T < ξ, the intersection point is considered abnormal. See [link to relevant documentation]. Figure 3 .

[0093] Step 3: Classify all intersections after filtering in Step 2:

[0094] After filtering in step two, all intersection points are classified. Assuming N receiving devices are deployed, resulting in M ​​intersection points, let C represent the set of these M intersection points. Let Ci represent the set of all hyperbolic intersection points formed by receiving device i. i This indicates that for set C and set C' i Perform the difference operation, i.e., C no_i =CC i Then C no_i Let C be the set of intersection points of the hyperbolas formed without the participation of receiving device i, where 1 ≤ i ≤ N. Then, the set C is calculated. no_i The number of intersection points, expressed by P. no_1 , ..., P no_i , ..., P no_N Let C represent the sets respectively. no_1 C no_i C no_N The number of intersection points is represented by P1, ..., P2. i , ..., P N Let C1, ..., C be sets respectively. i C N The number of intersection points, where P i The maximum value is P i_max =(N 3 -3N 2 +2N) / 2.

[0095] Step 4: Calculate the dispersion of the intersection point classification results from Step 3.

[0096] Based on the classification of intersection points in step three, set C is... no_i The dispersion is calculated using the following formula:

[0097]

[0098] Among them, [x no_i (k),x no_i [k] is represented by set C. no_i The coordinates of the kth intersection point.

[0099] Step 5: Perform dispersion weighting on the calculation results of Step 4:

[0100] Through P i For S no_i After weighting, the formula is as follows:

[0101]

[0102] Step Six: Screening for Abnormal Receiving Devices

[0103] Identifying abnormal receiving devices involves analyzing P... iand S′ noi The judgment is made in two steps: First, judge P. i Size, as can be seen from the above analysis, P i The maximum value is P i_max Set threshold The value ranges from 1 / 3 to 1 / 2, when P i Less than If the i-th receiving device is faulty, then proceed to the second step; otherwise, check S′. noi To identify abnormal receiving devices, a threshold χ is set, with χ ranging from 3 to 4. When the condition χS′ is met... no_i ≤S′ no_l If 1≤l≤N and l≠i, then the i-th receiving device is determined to be faulty.

[0104] Simulation analysis assumes that six receiving devices are deployed within a core area with a radius of 500 meters. The coordinates of these six receiving devices are s1 = [250, 433]. T s2 = [500, 0] T s3 = [250, -433] T s4 = [-250, -433] T s5 = [-500, 0] T And s6 = [-250, 433] T Let the thresholds be a = 15, b = 5, ε = 1, β = 1, ξ = 15, and χ = 3. For ease of analysis, when the number of intersections of receiving device 1 is less than P... 1_max When / χ, let S′ no_2 S′ no_3 S′ no_4 S′ no_5 and S′ no_6 The value is 1000, and then the coordinates of the signal source u are [-200, 300]. T [-200, -300] T [200, -300] T [0,0] T Four simulations were performed respectively, and the simulation results are shown below. Figure 4 , Figure 5 , Figure 6 , Figure 7 As can be seen from the simulation diagram, as the error value of receiving device 1 increases, S′ no_2 S' no_3 S' no_4 S' no_5 S' no_6 It also increases accordingly, and S' no_1The TDOA parameter remains consistently at an extremely low level, thus indicating an abnormality in receiving device 1. Existing technologies primarily filter for abnormal TDOA parameters; however, in practical applications, abnormal TDOA parameters are mainly caused by malfunctions in the receiving device. (Based on the embodiments and...) Figure 4 , Figure 5 , Figure 6 , Figure 7 As can be seen, the present invention can effectively identify potentially problematic receiving devices after the receiving device error value exceeds 500ns, and promptly eliminate a series of positioning data generated by them.

Claims

1. A method for screening abnormal receiving devices based on TDOA positioning, characterized in that: Specifically, the following steps are included: Step 1: Solve for the intersection of the hyperbolas using TDOA; During TDOA positioning, N receiving devices can collect N sets of data, which will form N(N-1) / 2 TDOA values. Each TDOA value can form a positioning hyperbola about the target source location, resulting in a total of N(N-1) / 2 positioning hyperbolas. These N(N-1) / 2 positioning hyperbolas will form multiple intersection points. Before calculating the coordinates of the intersection points, it is determined whether any two positioning hyperbolas intersect, and if they do intersect, the coordinates of the intersection points are calculated. All positioning hyperbolas are traversed to calculate the coordinates of all intersection points. Step 2: Screen all intersection points obtained in Step 1 for abnormal intersection points; remove all intersection points obtained in Step 1 that are not suitable for discreteness calculation. The removal principle is based on the tangent angle K of the two positioning hyperbolas at the intersection point: when K is greater than 90°, let T = 180° - K; otherwise, let T = K; set a threshold ξ, the value of which ranges from 15° to 25°. When T < ξ, the intersection point is considered abnormal. Step 3: Classify all intersections after filtering in Step 2; After filtering in step two, all intersection points are classified. Assuming N receiving devices are deployed, resulting in M ​​intersection points, let C represent the set of these M intersection points. Let Ci represent the set of all hyperbolic intersection points formed by receiving device i. i This indicates that for set C and set C' i Perform the difference operation, i.e., C no_i =CC i Then C no_i Let C be the set of intersection points of the hyperbolas formed without the participation of receiving device i, where 1 ≤ i ≤ N; then calculate set C. no_i The number of intersection points, expressed by P. no_1 , ..., P no_i , ..., P no_N Let C represent sets respectively. no_1 C no_i C no_N The number of intersection points is represented by P1, ..., P. i , ..., P N Let C1, ..., C be sets respectively. i C N The number of intersection points, where P i The maximum value is P i_max =(N 3 -3N 2 +2N) / 2; Step 4: Calculate the dispersion of the intersection point classification results from Step 3; Based on the classification of intersection points in step three, set C is... no_i The dispersion is calculated using the following formula: Among them, [x no_i (k),y no_i [k] is represented by set C. no_i The coordinates of the kth intersection point; Step 5: Perform dispersion weighting on the calculation results of Step 4; Through P i For S no_i After weighting, the formula is as follows: Step Six: Screen abnormal receiving devices based on the weighted results from Step Five; By analyzing P i and S' no_i The method for identifying abnormal receiving devices involves two steps: First, determine P... i Size, as can be seen from the above analysis, P i The maximum value is P i_max Set threshold The value ranges from 1 / 3 to 1 / 2, when P i Less than If the i-th receiving device is faulty, then proceed to the second step; in the second step, check S'. no_i To identify abnormal receiving devices, a threshold χ is set, with χ ranging from 3 to 4. When the condition χS' is met... no_i ≤S' no_l If 1≤l≤N and l≠i, then the i-th receiving device is determined to be faulty.

2. The method for screening abnormal receiving devices based on TDOA positioning according to claim 1, characterized in that: The specific steps of step one are as follows: 1) List the equations of any two locating hyperbolas, their equations are as follows: Among them, u=[x,y] T Let s be the coordinates of the signal source. i =[x i ,y i ] T Let r be the coordinates of the i-th receiving device. ij The time difference between the signal source reaching the i-th and j-th receiving devices is multiplied by the electromagnetic wave propagation speed. 2) For F ij and F kg Taking the first-order partial derivatives respectively, we get: 3) Select the centroid u of the receiving device coordinates. (0) As an initial value, at the centroid u (0) Performing a Taylor series expansion at this point, we obtain the approximate system of equations: F(u)=F(u (0) )+F'(u (0) )(uu (0) )=0 Therefore, the iterative solution is obtained as follows: and (1) =and (0) -[F'(u 0 ) T In (and 0 )] -1 In (and 0 ) T F(and 0 ) u (1) This is the result of the first iteration; at this point, u... (1) Using this as the initial value, repeat step 3) above iteratively a times to obtain a iteration results, u (1) u (2) 、…、u (a) Take the results of the next b (b < a) iterations and determine: Is it true or false? If not, it means there is no intersection; if true, then u... (a) Substitute into the equation Determine F using manually set thresholds a, b, ε, and β. ij <β and F kg If both <β are true, then there is an intersection point, and this value is the coordinate of the intersection point; otherwise, there is no intersection point. Based on steps 1) to 3), determine whether any two of the N(N-1) / 2 positioning hyperbolas intersect.

3. The method for screening abnormal receiving devices based on TDOA positioning according to claim 1, characterized in that: The specific method for step two is as follows: The angle K between the tangents of the two positioning hyperbolas at their intersection is used as the criterion: the slopes of the two positioning hyperbolas at their intersection are: Among them, [x h ,y h ] T Given the coordinates of the intersection point, the angle of the tangent is calculated as follows:

4. A system based on the TDOA positioning-based abnormal receiving device screening method according to any one of claims 1 to 3, characterized in that: include: The TDOA module for finding the intersection of hyperbolas is used in step one to find the intersection of hyperbolas using Newton's iteration method. The abnormal intersection filtering module is used in step two to filter abnormal intersections by judging the tangent angle between any two positioning hyperbolas at their intersection. The intersection classification module is used in step three to classify intersections by determining which receiving device generated them. The discreteness calculation module is used in step four to calculate the discreteness of the classified intersection points based on the classification of intersection points in step three. The dispersion weighting module is used in step five, through P i Weighting the dispersion; The abnormal receiving device filtering module is used in step six to filter abnormal receiving devices.

5. A device based on the TDOA positioning-based abnormal receiving device screening method according to any one of claims 1 to 3, characterized in that: include: Memory, used to store computer programs; The processor is used to implement the abnormal receiving device screening method based on TDOA positioning described in steps one to six when executing the computer program.

6. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by the processor, it can perform abnormal receiving device screening based on the abnormal receiving device screening method based on TDOA positioning as described in any one of claims 1 to 3.

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