A method and device for quickly positioning a mobile terminal involved in a crime scene

Abstract

This invention discloses a method and device for rapid location of mobile terminals involved in crimes, specifically relating to the field of wireless signal positioning technology. It involves setting sampling points at the crime scene to acquire wireless signal strength, direction of arrival, and sampling coordinates; performing peak extraction and directional clustering to generate candidate location points; performing micro-displacement re-measurement around the candidate location points; determining the boundary orientation of obstructions based on the peak migration trajectory of the re-measured signal strength; distinguishing between leakage and reflection candidate points by registering the directional changes of the candidate location points with the boundary orientation of the obstructions; determining the terminal entity candidate region based on the asymmetric attenuation characteristics of the wireless signal strength at leakage candidate points; and combining this with consistency verification between the terminal entity candidate region and the reflection candidate points, thereby achieving rapid and accurate location of the mobile terminal involved in the crime. This invention effectively improves the accuracy and efficiency of locating mobile terminals involved in crimes.

Description

Technical Field

[0001] This invention relates to the field of wireless signal positioning technology, and more specifically, to a method and device for rapid positioning of mobile terminals involved in a crime scene. Background Technology

[0002] Current methods for rapid mobile terminal location at crime scenes primarily rely on the peak strength of wireless signals or the direction of signal arrival detected at the scene to determine the specific location of the mobile terminal involved. However, in practical applications, the complex spatial environment of crime scenes, especially the presence of numerous metal-structured furniture, equipment, vehicles, or building components, makes the wireless signals emitted by mobile terminals highly susceptible to environmental interference and alteration during propagation. This environmental interference manifests primarily as wireless signals potentially propagating through spatial gaps, openings, or reflective surfaces, causing the detected peak signal strength or signal direction to not directly correspond to the actual location of the terminal, resulting in location deviations or even misjudgments. Summary of the Invention

[0003] In order to overcome the above-mentioned defects of the prior art, embodiments of the present invention provide a method and device for rapid location of mobile terminals involved in a crime scene to solve the problems mentioned in the background art.

[0004] To achieve the above objectives, the present invention provides the following technical solution:

[0005] A method for rapid location of mobile terminals involved in a crime scene, comprising the following steps:

[0006] S1. Set up multiple sampling points at the crime scene and use directional receiving equipment to collect the wireless signal strength, direction of arrival, and sampling coordinates of the mobile terminal involved in the case at the sampling points to obtain a signal sampling sequence;

[0007] S2. Extract peak values ​​and cluster arrival directions from the signal sampling sequence to generate candidate location points;

[0008] S3. Perform micro-displacement re-measurement around the candidate positioning point along the intersection direction, extract edge leakage features based on the peak migration trajectory and local fluctuation period of the re-measurement signal intensity, and determine the corresponding occlusion boundary direction based on the peak migration trajectory.

[0009] S4. Register the arrival direction change sequence corresponding to the candidate positioning point with the boundary direction of the occluder, and screen out the leakage candidate points that slide along the boundary and the reflection candidate points that deflect away from the boundary.

[0010] S5. Re-measure the leakage candidate points along the boundary of the shield and on both sides of the normal direction, and determine the terminal entity candidate area in reverse according to the asymmetric attenuation order on both sides of the normal direction.

[0011] S6. Perform consistency verification between the candidate areas of the terminal entity and the candidate points of reflection, and output the positioning result of the mobile terminal involved in the case.

[0012] In a preferred embodiment, S1 specifically refers to:

[0013] The sampling path is determined based on the spatial boundaries and the distribution of obstructions at the crime scene, and sampling points are set at intervals along the sampling path;

[0014] A directional receiving device is used to perform directional scanning at each sampling point to record the wireless signal strength and corresponding direction of arrival under different scanning directions;

[0015] The wireless signal strengths continuously collected at the same sampling point are sorted by time, and stable signal segments are generated after removing abrupt signals.

[0016] By associating stable signal segments with the sampling coordinates corresponding to the sampling points, a signal sampling sequence containing the correspondence between wireless signal strength, direction of arrival, and sampling coordinates is generated.

[0017] In a preferred embodiment, S2 specifically refers to:

[0018] Local intensity peaks are extracted based on the relationship of wireless signal intensity changes in the signal sampling sequence, and peak distribution trajectories are formed based on the sampling coordinates corresponding to the local intensity peaks.

[0019] The arrival directions corresponding to the peak distribution trajectory are merged into directional proximity segments to generate continuous directional segments.

[0020] Isolated peaks are filtered out based on the consistency of wireless signal strength changes within a continuous directional segment.

[0021] Intersection analysis is performed on the remaining peak distribution trajectory to extract the intersection area of ​​continuous segments in multiple directions, and the sampling coordinates corresponding to the intersection area are determined as candidate positioning points.

[0022] In a preferred embodiment, S3 specifically refers to:

[0023] Continuous retests are performed around the candidate location points along intersecting movement directions, and the trajectory of wireless signal strength changes and corresponding retest coordinates are recorded during the retest process;

[0024] The peak position migration trajectory is formed based on the offset relationship of the peak position in the trajectory of wireless signal strength change;

[0025] Periodic analysis of the wireless signal strength fluctuation intervals corresponding to the peak migration trajectory is performed to extract the local fluctuation period;

[0026] Identify edge leakage features based on the corresponding changes between peak migration trajectories and local fluctuation cycles;

[0027] The direction of the corresponding shading body boundary is determined based on the extension direction of the peak migration trajectory.

[0028] In a preferred embodiment, S4 specifically refers to:

[0029] Extract the arrival direction change sequence of candidate positioning points during continuous remeasurement, and establish the change correlation between the arrival direction change sequence and the corresponding remeasurement coordinates;

[0030] Based on the boundary orientation of the obstructing object, the arrival direction change sequence is registered with the boundary orientation to form a boundary fitting trajectory;

[0031] A continuous analysis of the directional offset amplitude in the boundary fitting trajectory is performed to identify the leakage propagation trajectory of continuous sliding along the boundary of the shield.

[0032] A turning point analysis is performed on the directional abrupt region that deviates from the boundary of the shading body, the corresponding reflection propagation trajectory is extracted, and the reflection candidate point is determined based on the remeasured coordinates corresponding to the reflection propagation trajectory.

[0033] In a preferred embodiment, S5 specifically refers to:

[0034] Re-measurement was carried out along the boundary of the shielding body corresponding to the leakage propagation trajectory and in the direction perpendicular to the boundary of the shielding body. The relationship between the change of wireless signal strength and the corresponding re-measurement coordinates during the re-measurement process was recorded.

[0035] Analyze the differences in wireless signal strength attenuation in the direction perpendicular to the boundary of the obstruction to determine the asymmetric attenuation sequence of wireless signal strength;

[0036] The direction of wireless signal propagation is determined based on the slower side of the asymmetric attenuation sequence of wireless signal strength, and the candidate region of the terminal entity is determined based on the retest coordinate range corresponding to the direction of propagation.

[0037] In a preferred embodiment, S6 specifically refers to:

[0038] A retest is performed within the candidate area of ​​the terminal entity to obtain the correspondence between the wireless signal strength distribution of the candidate area and the retest coordinates.

[0039] Analyze the spatial continuity of wireless signal strength distribution between candidate reflection points and candidate terminal entity regions to identify the locations where the wireless signal strength distribution is interrupted;

[0040] The actual boundary of the candidate area for the terminal entity is delineated based on the location of the interruption in the wireless signal strength distribution, and the location result of the mobile terminal in question is determined based on the actual boundary.

[0041] On the other hand, the present invention provides a device for rapid location of a mobile terminal involved in a crime scene, comprising: a processor, a memory, and a program or instructions stored in the memory and executable on the processor. When the program or instructions are executed by the processor, a method for rapid location of a mobile terminal involved in a crime scene is implemented.

[0042] The technical effects and advantages of the present invention, a method and device for rapid location of mobile terminals involved in a crime scene:

[0043] By setting up multiple sampling points at the crime scene and collecting wireless signal strength, direction of arrival, and sampling coordinates, a signal sampling sequence corresponding to the spatial location of the scene can be formed. Candidate positioning points are generated by peak extraction and direction of arrival clustering, reducing direct dependence on a single signal strength peak. By performing micro-displacement re-measurement around the candidate positioning points and extracting edge leakage features by combining peak migration trajectory and local fluctuation period, abnormal propagation locations caused by environmental factors such as gaps and openings can be identified. By registering the direction of arrival change sequence with the boundary orientation of the obstruction, leakage candidate points sliding along the boundary and reflection candidate points deflected away from the boundary can be distinguished. By re-measuring both sides of the leakage candidate points in the normal direction and determining the candidate area of ​​the terminal entity based on the asymmetric attenuation order, the positioning judgment can be shifted from the position of the signal pseudo-peak to the possible area of ​​the terminal entity. By outputting the positioning results of the mobile terminal involved in the case through consistency verification, the accuracy and reliability of rapid positioning of the mobile terminal involved in the case in the complex environment of the crime scene can be improved. Attached Figure Description

[0044] Figure 1 This is a schematic diagram of a method for rapid location of a mobile terminal involved in a crime scene according to the present invention. Detailed Implementation

[0045] 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 of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0046] Example 1

[0047] Figure 1 This invention provides a method for rapid location of a mobile terminal involved in a crime scene, comprising the following steps:

[0048] S1. Set up multiple sampling points at the crime scene and use directional receiving equipment to collect the wireless signal strength, direction of arrival, and sampling coordinates of the mobile terminal involved in the case at the sampling points to obtain a signal sampling sequence;

[0049] S2. Extract peak values ​​and cluster arrival directions from the signal sampling sequence to generate candidate location points;

[0050] S3. Perform micro-displacement re-measurement around the candidate positioning point along the intersection direction, extract edge leakage features based on the peak migration trajectory and local fluctuation period of the re-measurement signal intensity, and determine the corresponding occlusion boundary direction based on the peak migration trajectory.

[0051] S4. Register the arrival direction change sequence corresponding to the candidate positioning point with the boundary direction of the occluder, and screen out the leakage candidate points that slide along the boundary and the reflection candidate points that deflect away from the boundary.

[0052] S5. Re-measure the leakage candidate points along the boundary of the shield and on both sides of the normal direction, and determine the terminal entity candidate area in reverse according to the asymmetric attenuation order on both sides of the normal direction.

[0053] S6. Perform consistency verification between the candidate areas of the terminal entity and the candidate points of reflection, and output the positioning result of the mobile terminal involved in the case.

[0054] S1. Multiple sampling points are set up at the crime scene. A directional receiving device is used to collect the wireless signal strength, direction of arrival, and sampling coordinates of the mobile terminal involved in the case at each sampling point, resulting in a signal sampling sequence, including:

[0055] The sampling path is determined based on the spatial boundaries and the distribution of obstructions at the crime scene, and sampling points are set at intervals along the sampling path;

[0056] Specifically, by using a ranging tool to measure the actual spatial range of the crime scene, the spatial boundaries of the crime scene are determined, including but not limited to the length, width, and height of the crime scene and their distribution locations. Within the spatial boundaries of the crime scene, objects that may reflect, refract, shield, or otherwise interfere with the wireless signals emitted by the mobile terminal involved in the case are identified and marked, i.e., obstructions, including but not limited to metal cabinets, walls, columns, furniture, electrical equipment, and vehicles. Based on the specific spatial distribution locations, physical dimensions, and geometric shapes of the marked obstructions within the crime scene, a spatial layout diagram of the crime scene is drawn.

[0057] In the spatial layout diagram, locations close to both the spatial boundary and the distribution of obstructions are selected as the primary basis for path setting, ensuring that the planned sampling paths can cover areas within the crime scene where wireless signal interference exists as much as possible. Specifically, linear, polygonal, or grid-like paths can be used based on the geometric distribution characteristics of the obstructions. For example, in scenarios where obstructions are arranged linearly, a linear sampling path parallel to the linear direction of the obstructions is used; in scenarios where obstructions exist in a dispersed state, a grid-like or polygonal sampling path is used.

[0058] Based on the spatial length of the sampling path, the total length of the sampling path is evenly divided into several sub-intervals, and a sampling point is set at the boundary of each sub-interval. The division method is determined according to the frequency range, propagation characteristics, and expected positioning accuracy requirements of the wireless signal. For example, for common wireless signal frequency ranges of mobile terminals involved in cases (such as, but not limited to, the 900MHz to 2.4GHz band), a uniform interval of about 1 to 2 meters is used; in scenarios with a large crime scene space or high expected positioning accuracy requirements, the interval between sampling points is shortened to between 0.5 meters and 1 meter to ensure that sufficiently dense wireless signal information is obtained.

[0059] A directional receiving device is used to perform directional scanning at each sampling point to record the wireless signal strength and corresponding direction of arrival under different scanning directions;

[0060] Specifically, at each sampling point, a directional receiving device equipped with a directional antenna is used to progressively rotate and scan along a horizontal plane centered on the sampling point to acquire signals. The directional receiving device rotates along the horizontal plane in fixed-angle increments, for example, scanning once every 10 degrees, gradually achieving 360-degree omnidirectional signal coverage. In each angular direction, the directional receiving device acquires the strength value of the wireless signal in that direction and records the direction of arrival of the wireless signal. The direction of arrival is determined by precisely calibrating the pointing angle of the directional antenna and associating the pointing angle with geographical coordinates, thereby accurately recording the wireless signal strength and direction of arrival in each direction.

[0061] The wireless signal strengths continuously collected at the same sampling point are sorted by time, and stable signal segments are generated after removing abrupt signals.

[0062] Specifically, a series of wireless signal strength measurements are acquired through multiple continuous scans in each direction, forming a wireless signal strength sequence that varies over time. This sequence is then sorted in ascending order according to the acquisition time to obtain time-series-based wireless signal strength measurements. Abrupt signal removal is then performed on these time-series-based measurements using either the moving window variance method or the moving mean difference method. This involves calculating the local statistics (e.g., window variance or mean difference) between each measurement and its neighboring measurements in the signal strength sequence. When a measurement's local statistics relative to its preceding and following values ​​exceed a preset threshold, the corresponding measurement is identified as an abrupt signal and removed. The preset threshold range is determined by setting a reasonable statistical threshold based on historical data of the acquired wireless signal strength and the ambient noise level. For example, a range of 1 to 3 times the standard deviation of historical signal strength variation can be used as the preset threshold range.

[0063] The signal strength measurement after removing abrupt signals constitutes a stable signal segment, which represents the true and stable wireless signal strength distribution characteristics of the same sampling point in a specific direction.

[0064] By associating stable signal segments with the sampling coordinates corresponding to sampling points, a signal sampling sequence containing the correspondence between wireless signal strength, direction of arrival, and sampling coordinates is generated.

[0065] Specifically, the stable signal segments are associated with the sampling coordinates corresponding to the sampling points. For each stable signal segment, the spatial coordinate information of the corresponding sampling point is recorded and retained. The spatial coordinate information of the sampling point is obtained through on-site measurement. The coordinate information includes, but is not limited to, three-dimensional coordinates using a spatial rectangular coordinate system or a geographic coordinate system. For example, the spatial position of the sampling point is represented by spatial rectangular coordinates (X, Y, Z) accurate to the centimeter level, thereby calibrating the spatial position information of each sampling point.

[0066] After the above processing, a signal sampling sequence containing the correspondence between wireless signal strength, direction of arrival, and sampling coordinates is finally generated. The signal sampling sequence uses the sampling point coordinates as an index to record the stable wireless signal strength and direction of arrival of the wireless signal measured in each direction at each sampling point.

[0067] S2. Perform peak extraction and direction-of-arrival clustering on the signal sampling sequence to generate candidate location points, including:

[0068] Local intensity peaks are extracted based on the relationship of wireless signal intensity changes in the signal sampling sequence, and peak distribution trajectories are formed based on the sampling coordinates corresponding to the local intensity peaks.

[0069] Specifically, wireless signal strength data in all directions for each sampling point are extracted from the signal sampling sequence. Based on the continuity of spatial sampling coordinates, a two-dimensional spatial intensity distribution relationship is constructed with the sampling coordinates as the horizontal axis and wireless signal strength as the vertical axis. In this two-dimensional spatial intensity distribution relationship, local extremum analysis is used to compare the wireless signal strength at each sampling point with that of adjacent sampling points. When the wireless signal strength at a certain sampling point is higher than that of adjacent sampling points and also higher than a preset threshold multiple of the average wireless signal strength of adjacent sampling points, the wireless signal strength at the corresponding location of that sampling point is identified as a local intensity peak. The preset threshold multiple is determined as follows: based on statistical analysis of the measurement data of wireless signal strength at actual crime scenes, the standard deviation of the wireless signal strength in the adjacent area of ​​the sampling point is calculated, and then twice the standard deviation is used as the threshold multiple to distinguish the difference between the local intensity peak and the surrounding background signal.

[0070] The spatial sampling coordinates corresponding to each local intensity peak are sequentially connected to form a trajectory line based on the continuous spatial positions of the sampling coordinates, i.e., the peak distribution trajectory. The connection principle is as follows: for two adjacent local intensity peaks, the spatial coordinate distance between them is calculated. When the spatial coordinate distance is lower than a preset spatial distance threshold, it is determined that the two local intensity peaks belong to the same trajectory segment in spatial distribution, and they are sequentially connected to form a continuous trajectory segment. The spatial distance threshold is determined as follows: based on the propagation characteristics of the wireless signal and the sampling point interval distance, 1.2 times the sampling point interval distance is taken as the spatial distance threshold.

[0071] The arrival directions corresponding to the peak distribution trajectory are merged into directional proximity segments to generate continuous directional segments.

[0072] Specifically, for the arrival direction of the wireless signal corresponding to each local intensity peak in the peak distribution trajectory, the angle value is used as the direction measurement standard, and a direction proximity merging algorithm is used to process the direction angle value. The direction proximity merging algorithm is implemented as follows: all arrival direction angle values ​​are arranged in ascending order, and the angle difference between adjacent angle values ​​is compared one by one. When the difference between two angle values ​​is less than a preset angle threshold, the two angle values ​​are merged into the same continuous segment in the same direction, until all direction angle values ​​are merged into several continuous segments in the same direction. The preset angle threshold is determined as follows: based on the angle step accuracy of the signal collected by the directional receiving device and the directional characteristics of the wireless signal propagation, an angle threshold between 1.5 times the angle step value is selected as the angle threshold. For example, if the directional receiving device uses a 10-degree step, the angle threshold is set to 15 degrees.

[0073] Isolated peaks are filtered out based on the consistency of wireless signal strength changes within a continuous directional segment.

[0074] Specifically, for each continuous segment in a direction, the wireless signal strength of all local intensity peaks within the segment is extracted, and the trend of wireless signal strength variation within the segment is calculated. For example, linear or polynomial fitting methods are used to fit the changes in wireless signal strength within the continuous segment. When the wireless signal strength corresponding to a local intensity peak deviates from the fitted curve, i.e., the fitting residual value exceeds a preset residual threshold, the corresponding local intensity peak is identified as an isolated peak and filtered out. The preset residual threshold is determined by analyzing the standard deviation of the signal strength fitting residual based on historical statistical data of wireless signal strength measurements, and using 2.5 times the standard deviation as the residual threshold.

[0075] Intersection analysis is performed on the remaining peak distribution trajectory to extract the intersection area of ​​continuous segments in multiple directions, and the sampling coordinates corresponding to the intersection area are determined as candidate positioning points;

[0076] Specifically, the peak distribution trajectories of continuous segments in each direction are plotted on the same spatial layout coordinate system. The spatial positional relationships between the trajectories of continuous segments in different directions are compared. If a spatial intersection is found between the peak distribution trajectories of two or more continuous segments in the spatial layout coordinate system (i.e., the spatial coordinates of the intersection areas overlap or are close to each other), then the intersection area is marked as the intersection area of ​​the continuous segments. The criterion for determining the spatial intersection location is: when the shortest distance between the peak distribution trajectories of two continuous segments in two directions is less than or equal to the spatial distance intersection threshold, it is considered an intersection area. The spatial distance intersection threshold is determined in the same way as the spatial distance threshold, for example, set to 1.2 times the sampling point interval distance.

[0077] For each intersection area, calculate the centroid or average coordinate value of all sampled coordinate positions, that is, use the geometric center point of multiple sampled coordinates within the intersection area as the spatial coordinate position of the candidate positioning point.

[0078] S3. Perform micro-displacement re-measurement around the candidate positioning point along the intersection direction. Extract edge leakage features based on the peak migration trajectory and local fluctuation period of the re-measured signal intensity, and determine the corresponding occlusion boundary orientation based on the peak migration trajectory, including:

[0079] Continuous retests are performed around the candidate location points along intersecting movement directions, and the trajectory of wireless signal strength changes and corresponding retest coordinates are recorded during the retest process;

[0080] Specifically, based on the spatial coordinates of the candidate positioning point, at least two intersecting straight-line paths are planned with the candidate positioning point as the spatial center, and spatial movement is performed along these intersecting straight-line paths. Specifically, the planned straight-line paths should be perpendicular or approximately perpendicular to each other; for example, one straight-line path in the horizontal direction and one straight-line path in the vertical direction are planned, ensuring that the two paths intersect at the candidate positioning point. Simultaneously, on each straight-line path, starting from the candidate positioning point, continuous movement is performed at a fixed spatial step size, and wireless signal strength is measured. The fixed spatial step size is determined by setting it to between one-quarter and one-half of the wavelength based on the wavelength and propagation characteristics of the wireless signal. For example, for wireless signals with frequencies in the range of 900MHz to 2.4GHz, the fixed spatial step size is set to approximately 0.1 meters to 0.3 meters.

[0081] During each step of spatial movement, the same directional receiving device is used to measure the wireless signal strength. The antenna of the directional receiving device is always pointed towards the candidate positioning point. The measured value of the wireless signal strength at each movement position and the corresponding spatial remeasurement coordinates are recorded. By sequentially associating the wireless signal strength measurements recorded during the continuous remeasurement process with the corresponding spatial remeasurement coordinates, a trajectory of the wireless signal strength change during the continuous remeasurement process is formed.

[0082] The peak position migration trajectory is formed based on the offset relationship of the peak position in the trajectory of wireless signal strength change;

[0083] Specifically, the wireless signal strength variation trajectory during continuous retesting is analyzed point by point. Local extremum analysis is used to identify and extract multiple wireless signal strength peaks and their corresponding spatial retesting coordinates along each retesting path, referred to as peak positions. Based on the spatial coordinate relationship of multiple peak positions on each straight path, the spatial offset of the peak position is calculated, i.e., the spatial distance from the starting point to the ending point. The continuous spatial variation relationship of each peak position along the retesting path is recorded, and the peak positions are connected in order of spatial coordinates to form a complete peak position migration trajectory.

[0084] Periodic analysis of the wireless signal strength fluctuation intervals corresponding to the peak migration trajectory is performed to extract the local fluctuation period;

[0085] Specifically, for each peak migration trajectory, the spatial distance between two adjacent wireless signal strength peaks in the trajectory is extracted, and this spatial distance is defined as the wireless signal strength fluctuation interval. Fourier spectrum analysis or autocorrelation analysis is performed on all wireless signal strength fluctuation intervals to identify the spatial periodic distribution characteristics within the fluctuation intervals. Periodic analysis methods include, but are not limited to: performing a discrete Fourier transform on the fluctuation interval sequence to identify the spatial periodic component with the largest spectral amplitude from the spectrum, which is then determined as the local fluctuation period. For example, if Fourier spectrum analysis reveals a peak at a spatial distance of 0.5 meters in the fluctuation interval spectrum, then the local fluctuation period is 0.5 meters.

[0086] Identify edge leakage features based on the corresponding changes between peak migration trajectories and local fluctuation cycles;

[0087] Specifically, through analysis of the propagation characteristics of wireless signals, edge leakage is characterized by a regular, periodic change in the peak position of the peak migration trajectory in the direction of spatial movement. Specifically, the spatial coordinates of each peak position are sequentially marked on the peak migration trajectory, and the spatial position is divided into periods based on the local fluctuation period. The changing trend of the peak wireless signal strength within each period is compared. When the value and position of the peak wireless signal strength within a certain spatial period exhibit stable and repetitive regular fluctuations, it is identified as an edge leakage feature. The judgment criteria are: if the spatial distance difference between the peak positions of wireless signal strength within two or more consecutive spatial period periods is less than a spatial distance threshold and the numerical difference of the peak wireless signal strength is less than a wireless signal strength threshold, then an edge leakage feature is determined to exist. The spatial distance threshold and the wireless signal strength threshold are determined as follows: the spatial distance threshold is set to within 10% of the local fluctuation period, and the wireless signal strength threshold is set to within 5% of the maximum measured wireless signal strength. For example, when the maximum wireless signal strength is -50dBm, the wireless signal strength threshold is set to within 2.5dBm.

[0088] The direction of the corresponding shading body boundary is determined based on the extension direction of the peak migration trajectory.

[0089] Specifically, using the candidate location points as a benchmark, the actual spatial location of the peak migration trajectory is marked on the spatial layout diagram, and the overall extension direction of the trajectory is considered as the main reference direction for the boundary orientation of the obstruction. Combining the spatial layout characteristics of the obstructions on site, by comparing the distribution and extension direction of the obstruction boundaries in the spatial layout diagram, the obstruction boundary closest to or consistent with the overall extension direction of the peak migration trajectory is determined as the boundary orientation of the obstruction. The direction comparison method is as follows: calculate the spatial vector angle of the peak migration trajectory extension direction, then calculate the spatial vector angle of the obstruction boundary separately, and compare the obstruction boundary vector angle with the peak migration trajectory extension direction vector angle one by one. When the difference between the obstruction boundary vector angle and the peak migration trajectory extension direction vector angle is less than the angle matching threshold, the obstruction boundary is determined to be the corresponding boundary orientation of the obstruction. The angle matching threshold is determined by setting it between 5 and 10 degrees based on the actual site conditions.

[0090] S4. Register the arrival direction change sequence corresponding to the candidate positioning point with the boundary orientation of the occlusion body, and screen out leakage candidate points that slide along the boundary and reflection candidate points that deflect away from the boundary, including:

[0091] Extract the arrival direction change sequence of candidate positioning points during continuous remeasurement, and establish the change correlation between the arrival direction change sequence and the corresponding remeasurement coordinates;

[0092] Specifically, the arrival direction of the wireless signal is extracted from the wireless signal strength change trajectory recorded during continuous retesting. For each spatial retesting coordinate, the arrival direction of the wireless signal is recorded as an angle, which is accurately measured and calculated by the directional antenna of the directional receiving device. According to the actual order of spatial coordinate movement during continuous retesting, the arrival direction angles of the wireless signals corresponding to each spatial retesting coordinate are arranged sequentially to form a complete sequence of arrival direction changes. The arrival direction change sequence and the spatial retesting coordinates are then marked with a data correspondence to generate a data association between the spatial retesting coordinates and the arrival direction of the wireless signal, that is, the change association between the arrival direction change sequence and the corresponding retesting coordinates.

[0093] Based on the boundary orientation of the obstructing object, the arrival direction change sequence is registered with the boundary orientation to form a boundary fitting trajectory;

[0094] Specifically, starting from the direction of the obstruction's boundary, and using the direction of the obstruction's boundary as the reference direction, the direction vector angle of the obstruction's boundary is calculated. Each direction angle in the arrival direction change sequence is registered with the direction vector angle of the obstruction's boundary. For example, a direction angle difference analysis method is used, which calculates the difference between each arrival direction angle and the direction vector angle of the obstruction's boundary. Whether the difference is lower than a preset boundary direction registration threshold determines whether the arrival direction of the wireless signal is in a boundary-fitting state. The boundary direction registration threshold is determined by setting it between 5 and 8 degrees based on the spatial measurement accuracy of the wireless signal propagation direction and the geometric characteristics of the obstruction's boundary. All spatial remeasured coordinates successfully registered with the obstruction's boundary are extracted, and these spatial remeasured coordinates are connected in a continuous sequence according to the actual spatial coordinates to form a boundary-fitting trajectory.

[0095] A continuous analysis of the directional offset amplitude in the boundary fitting trajectory is performed to identify the leakage propagation trajectory of continuous sliding along the boundary of the shield.

[0096] Specifically, in the generated boundary fitting trajectory, the angular change difference of the arrival direction of the wireless signal corresponding to adjacent remeasured coordinates is extracted and defined as the directional offset amplitude. A continuity analysis is performed on the directional offset amplitudes corresponding to multiple consecutive adjacent spatial remeasured coordinate positions. For example, a sliding window variance analysis method is used, which calculates the variance of all directional offset amplitudes within a predetermined window length in the boundary fitting trajectory. The window length is determined based on the actual wireless signal strength measurement sampling frequency and spatial step size; for example, the window length is set to 3 to 5 consecutive spatial remeasured coordinate positions. When the variance of the directional offset amplitude within the window is less than a preset continuity threshold, it is determined that the directional offset amplitude of the spatial remeasured coordinate segment corresponding to the window has good continuity, conforming to the propagation characteristics of continuous sliding along the boundary of the obstruction. The continuity threshold is determined based on the statistical analysis of the accuracy of actual on-site wireless signal direction measurement, using 0.7 times the historical measurement standard deviation of the directional offset amplitude as the continuity threshold. Connecting the spatial remeasured coordinate segments that meet the continuity analysis criteria forms a complete leakage propagation trajectory, representing the continuous sliding path of the wireless signal along the boundary of the obstruction.

[0097] A turning point analysis is performed on the directional abrupt region that deviates from the boundary of the shading body, the corresponding reflection propagation trajectory is extracted, and the reflection candidate point is determined based on the remeasured coordinates corresponding to the reflection propagation trajectory.

[0098] Specifically, in the boundary alignment trajectory, spatial remeasured coordinate positions where the directional offset exceeds the boundary directional registration threshold are identified and defined as directional change regions. For each directional change region, the wireless signal strength corresponding to all remeasured coordinate positions within the directional change region is extracted, and the trend of wireless signal strength variation is analyzed. For example, the wireless signal strength gradient analysis method is used, that is, the gradient of the wireless signal strength at each spatial remeasured coordinate position relative to the adjacent spatial positions is calculated one by one. If there is a position in the directional change region where the wireless signal strength gradient is higher than the surrounding background area and the gradient direction changes, this position is determined to be the turning point of the wireless signal. The turning point is connected with the adjacent spatial remeasured coordinates to form the reflection propagation trajectory. The spatial remeasured coordinates corresponding to the position with the highest wireless signal strength and the most significant wireless signal gradient in the reflection propagation trajectory are extracted and defined as reflection candidate points.

[0099] The method for determining the wireless signal strength gradient threshold is as follows: the standard deviation of the wireless signal strength change gradient is obtained by statistical analysis of actual wireless signal measurement data, and 2.5 times the standard deviation is used as the wireless signal strength gradient threshold. By setting the wireless signal gradient threshold, it is ensured that the turning analysis can accurately identify the actual spatial location of the reflection in the region of sudden change in wireless signal direction, and effectively eliminate random fluctuation interference in the wireless signal propagation process, thereby improving the spatial location accuracy of the reflection candidate point.

[0100] S5. Re-measure the leak candidate points along the boundary of the shielding body and on both sides of the normal direction, and determine the terminal entity candidate region in reverse according to the asymmetric attenuation order on both sides of the normal direction, including:

[0101] Re-measurement was carried out along the boundary of the shielding body corresponding to the leakage propagation trajectory and in the direction perpendicular to the boundary of the shielding body. The relationship between the change of wireless signal strength and the corresponding re-measurement coordinates during the re-measurement process was recorded.

[0102] Specifically, using the leakage propagation trajectory as a reference, several straight retest paths are planned along the direction of the shield boundary and perpendicular to the direction of the shield boundary. The straight retest paths along the direction of the shield boundary extend along the spatial distribution of the edge leakage propagation trajectory; the straight retest paths perpendicular to the direction of the shield boundary intersect the spatial distribution of the edge leakage propagation trajectory perpendicularly. Specifically, the spatial length of each straight retest path is consistent with the sampling point interval, for example, set to 1 to 2 meters. The spatial step size of the retest path is set according to the spatial attenuation characteristics of the wireless signal; for example, for wireless signals with frequencies from 900MHz to 2.4GHz, the spatial step size is set between 0.1 meters and 0.3 meters.

[0103] On each straight retest path, the same directional receiving device was used to conduct retests at spatial step intervals. The wireless signal strength measurement value and the corresponding spatial coordinate information were recorded at each spatial retest coordinate. At the same time, the antenna of the directional receiving device was always pointed in the direction of the leakage propagation trajectory during the retest process to ensure that the measured wireless signal strength measurement value accurately reflects the wireless signal propagation characteristics in the direction of the leakage propagation trajectory.

[0104] Analyze the differences in wireless signal strength attenuation in the direction perpendicular to the boundary of the obstruction to determine the asymmetric attenuation sequence of wireless signal strength;

[0105] Specifically, for each straight retest path perpendicular to the boundary of the shield, the wireless signal strength measured at all spatial retest coordinate positions along the straight retest path is extracted. For each straight retest path, taking the location of the leakage propagation trajectory as the starting point of attenuation analysis, attenuation curves of wireless signal strength as a function of spatial retest coordinate positions are plotted in both the inward and outward directions of the shield. The attenuation gradient of the wireless signal strength attenuation curve in the inward and outward directions of the shield is calculated. The specific calculation method is as follows: the difference in wireless signal strength between adjacent spatial retest coordinate positions is divided by the corresponding spatial step size to obtain the wireless signal strength attenuation gradient. By comparing the difference in wireless signal strength attenuation gradient in the inward and outward directions of the shield, the directions of gentler and more severe wireless signal strength attenuation are determined, thus forming an asymmetric attenuation sequence of wireless signal strength.

[0106] The direction of wireless signal propagation is determined based on the gentler side of the asymmetric attenuation sequence of wireless signal strength, and the candidate region of the terminal entity is determined based on the retest coordinate range corresponding to the direction of propagation.

[0107] Specifically, starting from the asymmetric attenuation sequence of wireless signal strength, the spatial remeasurement coordinate direction on the side with gentler attenuation is determined as the actual source direction of wireless signal propagation. The remeasurement spatial range is expanded along the source direction of wireless signal propagation, and wireless signal strength remeasurement continues until a continuous spatial attenuation trend is observed or the wireless signal strength drops below a preset minimum value. At this point, all measured spatial remeasurement coordinate positions are defined as the actual remeasurement range along the source direction of wireless signal propagation. The preset minimum value of wireless signal strength is determined as follows: based on historical statistical analysis of actual wireless signal measurement data, the minimum historical standard deviation of the wireless signal strength measurement value is taken as a reference standard. The minimum value of wireless signal strength is set as a multiple of the maximum value of wireless signal strength and the historical standard deviation of wireless signal strength, for example, set as the maximum value of wireless signal strength minus three times the historical standard deviation of wireless signal strength.

[0108] Based on the measured wireless signal strength values ​​and spatial coordinate positions within the actual remeasurement range along the direction of wireless signal propagation, spatial coordinate clustering analysis is performed, for example, using the K-means spatial clustering algorithm. The wireless signal strength value is used as the weighting factor for spatial clustering analysis, and initial spatial coordinate cluster centers are formed based on the spatial remeasurement coordinate positions with higher wireless signal strength. The spatial positions and spatial ranges of the cluster centers are continuously updated iteratively until the difference in the Euclidean distance between all spatial remeasurement coordinate positions and their corresponding cluster centers is less than a preset spatial clustering convergence threshold. The spatial clustering convergence threshold is determined by setting it to within 10% of the sampling point interval distance, for example, within 0.1 meters, based on the on-site positioning accuracy requirements and wireless signal propagation characteristics. After the clustering analysis converges, the final clustered region is defined as the candidate region for terminal entities.

[0109] S6. Perform consistency verification between the candidate areas of the terminal entity and the candidate points of reflection, and output the positioning results of the mobile terminal involved in the case, including:

[0110] A retest is performed within the candidate area of ​​the terminal entity to obtain the correspondence between the wireless signal strength distribution of the candidate area and the retest coordinates.

[0111] Specifically, spatial retesting is planned and implemented within the spatial range of the candidate area for terminal entities. The retesting path is set as follows: taking the centroid of the candidate area as a reference point, a grid-like retesting path centered on the centroid is adopted. The grid size of the grid-like retesting path is determined according to the spatial attenuation characteristics of wireless signals and the actual measurement accuracy requirements on site. For example, for wireless signals with a frequency range of 900MHz to 2.4GHz, the grid size is set between 0.2 meters and 0.5 meters. At each grid node, the same directional receiving device is used to measure the wireless signal strength. The wireless signal strength measured at each grid node is associated with and recorded one-to-one with the corresponding spatial retesting coordinates, thereby forming the correspondence between the distribution of wireless signal strength and the retesting coordinates within the candidate area for terminal entities.

[0112] Analyze the spatial continuity of wireless signal strength distribution between candidate reflection points and candidate terminal entity regions to identify the locations where the wireless signal strength distribution is interrupted;

[0113] Specifically, starting from the spatial location of the reflection candidate point, spatial wireless signal strength is measured along a straight line towards the terminal entity candidate area to obtain the wireless signal strength along the spatial connection path between the reflection candidate point and the terminal entity candidate area. The wireless signal strength along the spatial connection path is then jointly analyzed with the wireless signal strength within the terminal entity candidate area. For example, a spatial wireless signal strength continuity trend analysis method can be used, which involves comparing the differences in wireless signal strength at adjacent remeasured coordinate positions to determine the continuous variation characteristics of wireless signal strength in space. When the wireless signal strength at multiple consecutive remeasured coordinate positions remains relatively stable and the variation amplitude is lower than a preset continuity stability threshold, the wireless signal strength distribution is considered to have good spatial continuity. When the wireless signal strength shows a significant decrease or attenuation trend in the spatial remeasured coordinates exceeding the preset continuity stability threshold, the corresponding position is determined as a wireless signal strength distribution interruption position. The preset continuity stability threshold is determined by analyzing the historical standard deviation of wireless signal strength measurements and setting it to 2.5 times the historical standard deviation.

[0114] The actual boundary of the candidate area for the terminal entity is delineated based on the location of the interruption in the wireless signal strength distribution, and the location result of the mobile terminal in question is determined based on the actual boundary.

[0115] Specifically, spatial boundaries are marked at locations where wireless signal strength distribution is interrupted. Using a spatial coordinate marking method, the spatial remeasurement coordinates corresponding to the locations where wireless signal strength is interrupted are recorded point by point to form the actual boundary of the candidate area for the terminal entity. The candidate area for the terminal entity is defined based on the actual boundary. The definition method includes, but is not limited to, the wireless signal strength comparison method between spatial points inside and outside the boundary. That is, wireless signal strength is remeasured along the actual boundary inward and outward directions respectively, and the spatial distribution characteristics of wireless signal strength in the inward direction are compared with those in the outward direction. If the overall wireless signal strength inside the boundary is significantly higher than that outside, then the inner side of the boundary is confirmed as the actual spatial range of the candidate area for the terminal entity.

[0116] The location point is calculated by using the wireless signal strength measurements of all remeasured coordinate positions within the actual boundary of the candidate area of ​​the terminal entity. Specifically, the calculation method is the wireless signal strength spatial centroid positioning method, which involves weighting and averaging the spatial positions based on the wireless signal strength to calculate the weighted spatial centroid coordinates of the overall wireless signal strength distribution, which is then used as the final location result for the mobile terminal in question. The formula for calculating the spatial centroid coordinates of the wireless signal strength is as follows:

[0117] X_c = Σ(W_i × X_i) / ΣW_i;

[0118] Y_c=Σ(W_i×Y_i) / ΣW_i;

[0119] Z_c = Σ(W_i × Z_i) / ΣW_i;

[0120] Where X_c, Y_c, and Z_c represent the three-dimensional coordinates of the spatial centroid of the wireless signal strength, in meters; X_i, Y_i, and Z_i represent the coordinates of the i-th spatial remeasurement coordinate position inside the actual boundary, in meters; W_i represents the weighting coefficient of the wireless signal strength measured at the i-th spatial remeasurement coordinate position. The weighting is calculated based on the difference between the measured wireless signal strength at the corresponding spatial remeasurement coordinate position and the maximum value of the measured wireless signal strength in the area. For example, the maximum value of the wireless signal strength is set to W_i=1, and the weight is calculated by decreasing the weight value by 0.05 for every 1dBm decrease in wireless signal strength, thus obtaining the weighting coefficient W_i for each spatial position.

[0121] The actual spatial coordinates of the mobile terminal in question were ultimately determined using a spatial centroid positioning calculation method. For example, if the maximum wireless signal strength was -45dBm and the second maximum was -46dBm, the weight coefficient W_i corresponding to the spatial remeasured coordinates at the maximum wireless signal strength was 1, and the weight coefficient W_i corresponding to the spatial remeasured coordinates at the second maximum wireless signal strength was 0.95, and so on, for all weight coefficients. The spatial positioning results of the mobile terminal in question were then recorded and compared with the actual coordinates in the on-site spatial layout diagram to determine the true spatial location of the mobile terminal within the crime scene.

[0122] Example 2

[0123] A device for rapid location of a mobile terminal involved in a crime scene includes: a processor, a memory, and a program or instructions stored in the memory and executable on the processor. When the program or instructions are executed by the processor, a method for rapid location of a mobile terminal involved in a crime scene is implemented.

[0124] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more sets of available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. The semiconductor medium can be a solid-state drive.

[0125] Those skilled in the art will recognize that the modules and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0126] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and modules described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0127] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or modules may be electrical, mechanical, or other forms.

[0128] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical modules; they may be located in one place or distributed across multiple network modules. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0129] In addition, the functional modules in the various embodiments of this application can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module.

[0130] If the aforementioned functions are implemented as software functional modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0131] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0132] In conclusion, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for rapid location of a mobile terminal involved in a crime scene, characterized in that, Includes the following steps: S1. Set up multiple sampling points at the crime scene and use directional receiving equipment to collect the wireless signal strength, direction of arrival, and sampling coordinates of the mobile terminal involved in the case at the sampling points to obtain a signal sampling sequence; S2. Extract peak values ​​and cluster arrival directions from the signal sampling sequence to generate candidate location points; S3. Perform micro-displacement re-measurement around the candidate positioning point along the intersection direction, extract edge leakage features based on the peak migration trajectory and local fluctuation period of the re-measurement signal intensity, and determine the corresponding occlusion boundary direction based on the peak migration trajectory. S4. Register the arrival direction change sequence corresponding to the candidate positioning point with the boundary direction of the occluder, and screen out the leakage candidate points that slide along the boundary and the reflection candidate points that deflect away from the boundary. S5. Re-measure the leakage candidate points along the boundary of the shield and on both sides of the normal direction, and determine the terminal entity candidate area in reverse according to the asymmetric attenuation order on both sides of the normal direction. S6. Perform consistency verification between the candidate areas of the terminal entity and the candidate points of reflection, and output the positioning result of the mobile terminal involved in the case.

2. The method for rapid location of a mobile terminal involved in a crime scene according to claim 1, characterized in that, S1, specifically: The sampling path is determined based on the spatial boundaries and the distribution of obstructions at the crime scene, and sampling points are set at intervals along the sampling path; A directional receiving device is used to perform directional scanning at each sampling point to record the wireless signal strength and corresponding direction of arrival under different scanning directions; The wireless signal strengths continuously collected at the same sampling point are sorted by time, and stable signal segments are generated after removing abrupt signals. By associating stable signal segments with the sampling coordinates corresponding to the sampling points, a signal sampling sequence containing the correspondence between wireless signal strength, direction of arrival, and sampling coordinates is generated.

3. A method for rapid location of a mobile terminal involved in a crime scene according to claim 2, characterized in that, S2, specifically: Local intensity peaks are extracted based on the relationship of wireless signal intensity changes in the signal sampling sequence, and peak distribution trajectories are formed based on the sampling coordinates corresponding to the local intensity peaks. The arrival directions corresponding to the peak distribution trajectory are merged into directional proximity segments to generate continuous directional segments. Isolated peaks are filtered out based on the consistency of wireless signal strength changes within a continuous directional segment. Intersection analysis is performed on the remaining peak distribution trajectory to extract the intersection area of ​​continuous segments in multiple directions, and the sampling coordinates corresponding to the intersection area are determined as candidate positioning points.

4. A method for rapid location of a mobile terminal involved in a crime scene according to claim 3, characterized in that, S3, specifically: Continuous retests are performed around the candidate location points along intersecting movement directions, and the trajectory of wireless signal strength changes and corresponding retest coordinates are recorded during the retest process; The peak position migration trajectory is formed based on the offset relationship of the peak position in the trajectory of wireless signal strength change; Periodic analysis of the wireless signal strength fluctuation intervals corresponding to the peak migration trajectory is performed to extract the local fluctuation period; Identify edge leakage features based on the corresponding changes between peak migration trajectories and local fluctuation cycles; The direction of the corresponding shading body boundary is determined based on the extension direction of the peak migration trajectory.

5. A method for rapid location of a mobile terminal involved in a crime scene according to claim 4, characterized in that, S4, specifically: Extract the arrival direction change sequence of candidate positioning points during continuous remeasurement, and establish the change correlation between the arrival direction change sequence and the corresponding remeasurement coordinates; Based on the boundary orientation of the obstructing object, the arrival direction change sequence is registered with the boundary orientation to form a boundary fitting trajectory; A continuous analysis of the directional offset amplitude in the boundary fitting trajectory is performed to identify the leakage propagation trajectory of continuous sliding along the boundary of the shield. A turning point analysis is performed on the directional abrupt region that deviates from the boundary of the shading body, the corresponding reflection propagation trajectory is extracted, and the reflection candidate point is determined based on the remeasured coordinates corresponding to the reflection propagation trajectory.

6. A method for rapid location of a mobile terminal involved in a crime scene according to claim 5, characterized in that, S5, specifically: Re-measurement was carried out along the boundary of the shielding body corresponding to the leakage propagation trajectory and in the direction perpendicular to the boundary of the shielding body. The relationship between the change of wireless signal strength and the corresponding re-measurement coordinates during the re-measurement process was recorded. Analyze the differences in wireless signal strength attenuation in the direction perpendicular to the boundary of the obstruction to determine the asymmetric attenuation sequence of wireless signal strength; The direction of wireless signal propagation is determined based on the slower side of the asymmetric attenuation sequence of wireless signal strength, and the candidate region of the terminal entity is determined based on the retest coordinate range corresponding to the direction of propagation.

7. A method for rapid location of a mobile terminal involved in a crime scene according to claim 6, characterized in that, S6, specifically: A retest is performed within the candidate area of ​​the terminal entity to obtain the correspondence between the wireless signal strength distribution of the candidate area and the retest coordinates. Analyze the spatial continuity of wireless signal strength distribution between candidate reflection points and candidate terminal entity regions to identify the locations where the wireless signal strength distribution is interrupted; The actual boundary of the candidate area for the terminal entity is delineated based on the location of the interruption in the wireless signal strength distribution, and the location result of the mobile terminal in question is determined based on the actual boundary.

8. A rapid location device for mobile terminals involved in a crime scene, characterized in that, include: A processor, a memory, and a program or instructions stored in the memory and executable on the processor, wherein when the program or instructions are executed by the processor, they implement a method for rapid location of a mobile terminal involved in a crime scene as described in any one of claims 1-7.

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