Method for mapping a radar monitoring area, radar monitoring method and system, device

Abstract

The application discloses a radar monitoring area drawing method, a radar monitoring method, a radar monitoring system, an electronic device and a computer readable storage medium, wherein the radar monitoring area drawing method comprises: performing rasterization processing on a radar tracking area to obtain a raster map; acquiring a motion trajectory of a target object in the radar tracking area; and determining a boundary of a radar monitoring area in the raster map based on the motion trajectory. Through the above manner, the accuracy and the drawing efficiency of the radar monitoring area drawing can be effectively improved.

Description

Technical Field

[0001] This application relates to the field of radar monitoring technology, and in particular to a method for drawing a radar monitoring area, a radar monitoring method, a radar monitoring system, an electronic device, and a computer-readable storage medium. Background Technology

[0002] Video surveillance equipment primarily uses visible light cameras, but these cameras cannot operate at night. While infrared cameras can compensate for this limitation, this undoubtedly increases cost and operational complexity. Furthermore, optical sensors are affected by weather conditions; in foggy or snowy weather, monitoring performance is unsatisfactory. Millimeter-wave radar-based area surveillance technology has become a major research focus in recent years. Millimeter-wave radar actively emits electromagnetic waves and receives signals of the same frequency. It has a very high detection probability for moving objects or objects with a large radar cross-section (RCS), but a lower detection probability (not zero) for stationary objects. Millimeter-wave radar can operate 24 hours a day and is less affected by weather. Therefore, there is currently a strong market demand for millimeter-wave radar-based surveillance products.

[0003] To achieve automated video surveillance in hazardous areas such as seaside resorts, a comprehensive radar monitoring system with no blind spots can be deployed in these areas. Once the area closes, the radar system activates, and if a pedestrian appears within the hazardous area, an alarm is triggered immediately (lights are activated, a warning is sounded, and photographic evidence is taken). However, radar monitoring areas often require manual mapping, which is time-consuming and labor-intensive. Furthermore, due to the unpredictable accuracy of manual operation, large deviations can easily lead to false alarms and missed alarms, resulting in irreparable losses. Summary of the Invention

[0004] To address the aforementioned problems, this invention provides a method for drawing a radar monitoring area, a radar monitoring method, a radar monitoring system, an electronic device, and a computer-readable storage medium, thereby resolving the issues present in the prior art.

[0005] One technical solution adopted in this invention is: a method for drawing a radar monitoring area, the method comprising: rasterizing the radar tracking area to obtain a raster image; obtaining the motion trajectory of target five within the radar tracking area; and determining the boundary of the radar monitoring area based on the motion trajectory in the previous image.

[0006] The step of determining the boundary of the radar monitoring area in the grid image based on the motion trajectory includes: discretizing the motion trajectory to obtain multiple clustered regions of the grid image; performing dilation processing on the multiple clustered regions to obtain the grid region of the radar monitoring area in the grid image; and determining the boundary of the radar monitoring area from the grid region.

[0007] Before performing dilation processing on multiple clustered regions, the process also includes removing interfering regions from the multiple clustered regions using a clustering algorithm.

[0008] The process of expanding multiple clustered regions separately includes the following steps for each clustered region: obtaining the first centroid of the current clustered region and the second centroid of the merged region of other clustered regions; setting the expansion direction of the current clustered region to point from the first centroid to the second centroid; and expanding the current clustered region according to the expansion direction.

[0009] The process of determining the boundary of the radar monitoring area from the grid region includes: connecting the grid cells located at the edge of the grid region sequentially to obtain the initial boundary of the radar monitoring area; and smoothing the initial boundary to obtain the final boundary of the radar monitoring area.

[0010] The drawing method also includes: determining whether there are any anomalies in the boundary of the radar monitoring area; if there are anomalies, then correcting or redrawing the boundary of the radar monitoring area.

[0011] The process of determining whether there are anomalies at the boundary of the radar monitoring area includes: calculating the confidence level of each grid cell in the grid area to obtain a confidence map; extracting a first region from the confidence map where the probability of a target appearing is greater than a first probability threshold and a second region where the probability of a target appearing is less than a second probability threshold; calculating a first theoretical number of targets appearing in the first region and a second theoretical number of targets appearing in the second region; wherein the first probability threshold is greater than or equal to the second probability threshold; obtaining a first actual number of targets appearing in the first region and a second actual number of targets appearing in the second region; establishing a detection function based on the first theoretical number, the second theoretical number, the first actual number, and the second actual number, and using the detection function to calculate the anomaly value of the grid area; if the anomaly value exceeds the first threshold or is less than the second threshold, it is determined that there are anomalies at the boundary of the radar monitoring area.

[0012] Another technical solution adopted by the present invention is: a radar monitoring method, comprising: obtaining a radar monitoring area based on the motion trajectory during a non-prevention period using the above-mentioned drawing method; and generating an alarm message in response to the appearance of a target object in the radar monitoring area during a prevention period.

[0013] Another technical solution adopted by the present invention is: a radar monitoring system, comprising: a radar for generating millimeter waves; a drawing device connected to the radar for rasterizing the radar tracking area to obtain a raster map, and also for acquiring the motion trajectory of a target object within the radar tracking area, and for determining the boundary of the radar monitoring area based on the motion trajectory in the raster map; and an alarm device connected to the radar for generating an alarm message when a target object appears in the radar monitoring area during the prevention period.

[0014] Another technical solution adopted by the present invention is: an electronic device, including a processor and a memory, wherein the memory stores program instructions, and the processor is used to execute the program instructions to implement the above-mentioned radar monitoring area drawing method and / or the above-mentioned radar monitoring method.

[0015] Another technical solution adopted by the present invention is: a computer-readable storage medium storing program instructions, which, when executed by a processor, can implement the above-mentioned radar monitoring area drawing method and / or the above-mentioned radar monitoring method.

[0016] The beneficial effects of this invention are as follows: This application proposes a method for drawing a radar monitoring area. The method includes: rasterizing the radar area to obtain a raster image; acquiring the motion trajectory of a target object within the radar tracking area; and determining the boundary of the radar monitoring area based on the motion trajectory in the raster image. This method enables automatic drawing of the radar monitoring area, eliminating the need for excessive manual operation. While maintaining drawing efficiency, it significantly reduces manual labor, thereby effectively saving drawing costs. Furthermore, using the motion trajectory of the target object to determine the radar monitoring area ensures higher accuracy and better reflects the actual situation. Attached Figure Description

[0017] Figure 1 This is a flowchart illustrating the first embodiment of the radar monitoring area drawing method of this application;

[0018] Figure 2 This is the grid of the radar monitoring area in this application. Figure 1 A schematic diagram of the embodiment;

[0019] Figure 3 yes Figure 1 A detailed flowchart of step S300 in the embodiment;

[0020] Figure 4 yes Figure 2 A schematic diagram of the discretized motion trajectory in the image;

[0021] Figure 5 yes Figure 4 A schematic diagram of the structure of the mid-clustered regions after interference removal processing;

[0022] Figure 6 yes Figure 5 A schematic diagram of the clustered regions after dilation processing;

[0023] Figure 7 yes Figure 3 A detailed flowchart of step S320 in the embodiment;

[0024] Figure 8 yes Figure 2 A schematic diagram of the initial boundary of the radar monitoring area;

[0025] Figure 9 yes Figure 8 A schematic diagram of the structure of the radar monitoring area after boundary smoothing;

[0026] Figure 10 This is a flowchart illustrating the second embodiment of the radar monitoring area drawing method of this application;

[0027] Figure 11 yes Figure 10 A detailed flowchart of step S105;

[0028] Figure 12 This is a schematic diagram of a specific process of the radar monitoring method of this application;

[0029] Figure 13 This is a schematic diagram of the structure of an embodiment of the radar monitoring system of this application;

[0030] Figure 14 This is a schematic diagram of the structure of an embodiment of the electronic device of this application;

[0031] Figure 15 This is a schematic diagram of the structure of an embodiment of the computer-readable storage medium of this application. Detailed Implementation

[0032] This application discloses a method for drawing a radar monitoring area, which determines and draws the boundary of the radar monitoring area based on the movement trajectory of a target object. The method involves two ports: one is a drawing port for drawing the radar monitoring area, specifically a system or processor with drawing capabilities; the other port is a radar device with monitoring capabilities, such as a millimeter-wave radar. Specifically, this radar monitoring area drawing method can be applied to locations such as farms, seaside resorts, and grasslands.

[0033] Specifically, drawing a radar monitoring area involves drawing a closed area within the radar tracking area (the radar tracking area is the entire range that the radar can monitor). When a target appears within this closed area during the prevention period, an alarm is triggered.

[0034] For radar monitoring systems, a closed area is merely a geometric shape, posing no technical challenge. The difficulty lies in mapping this closed area to a specific sensitive region within the chosen application scenario. This mapping of the closed area to the sensitive region is the key challenge in radar monitoring area design.

[0035] When a target is within the radar tracking area, it will be detected by the radar. The movement trajectories of multiple targets or a single target within the radar tracking area at different times will be monitored by the radar and recorded by the mapping unit. By rationally utilizing these target trajectories, the mapping unit can statistically obtain the target area, i.e., the target's activity area. This activity area can serve as the corresponding radar monitoring area or a preliminary model of the radar monitoring area. Modifications can be made based on this model, significantly reducing the workload of mapping the radar monitoring area. The radar monitoring area is defined as the area where target activity is permitted during non-defense periods but not during defense periods.

[0036] The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0037] This application proposes a first embodiment of a method for drawing radar monitoring areas, such as... Figure 1 As shown, Figure 1 This is a flowchart illustrating the first embodiment of the radar monitoring area drawing method of this application. In this embodiment, the drawing entity is the drawing terminal, and the drawing method includes the following steps:

[0038] Step S100: Rasterize the radar tracking area to obtain a raster image.

[0039] like Figure 2 As shown, Figure 2 The grid of the radar monitoring range of this application. Figure 1 A schematic diagram of the embodiment. The radar tracking area refers to the entire monitoring range that the radar can monitor, i.e. Figure 2 The image shows a fan-shaped area (not labeled), where the radar monitoring area is included within the radar tracking area. The radar tracking area and the trajectory of the monitored target within the radar monitoring area are also included. Figure 2 Information such as short lines within the central sector area is transmitted to the rendering end in real time. The rendering end rasterizes the radar tracking area to obtain a raster image containing the radar tracking area, which is used to prepare for subsequent steps. The smallest unit of the raster image is a single grid cell, such as... Figure 2 As shown, the coordinates of each grid cell in the grid image are (i, j), where i represents the i-th column and j represents the j-th row. The rendering end calculates the trajectory of the target object acquired by the radar based on the grid image, effectively reducing the complexity of the computational processing.

[0040] Step S200: Obtain the trajectory of the target object within the radar tracking area.

[0041] During a non-defense period, the radar continuously detects the movement trajectories of all targets moving within its monitoring area at a certain monitoring frequency, and transmits these trajectories to the plotting terminal, where they are recorded in a grid image. Figure 2 As shown, the chaotic trajectory lines within the fan-shaped radar tracking area represent the movement trajectory of each target detected by the radar during the non-defense period.

[0042] For example, in a seaside resort scenario, the area where tourists are allowed free movement during non-prevention activities is the area that the radar needs to monitor during the prevention period—that is, the radar monitoring area. In other words, during non-prevention activities, tourists can move freely within the radar monitoring area. During the prevention period, if the radar detects a tourist appearing within the radar monitoring area, it will sound an alarm to prevent tourists from entering the radar monitoring area and causing irreparable consequences. During the prevention period, the radar monitors in real time and collects the activity trajectories of all tourists within the radar monitoring area, transmitting these trajectories to a rendering terminal, which records these trajectories on a raster map.

[0043] Step S300: Determine the boundary of the radar monitoring area in the grid map based on the motion trajectory.

[0044] Based on the above steps, after the rendering end obtains the motion trajectory of each target object, since the motion trajectory of each target object is irregular, it is difficult to determine the activity area of ​​the target object simply by observing the motion trajectory of each target object. Therefore, in this step, the rendering end determines the specific grid in the grid map where the motion trajectory of each target object is located. The area composed of these grids is the activity area of ​​all targets, which is also the prototype of the radar monitoring area. The rendering end further processes this prototype of the radar monitoring area with an algorithm to determine the boundary of the radar monitoring area. In particular, by controlling the size of the grid in the grid map within a certain range, a more accurate prototype of the radar monitoring area can be obtained. Compared with directly determining the radar monitoring area based on the motion trajectory of the target object, this method can reduce the amount of computation and the difficulty of rendering, thereby improving the rendering efficiency of the radar monitoring area.

[0045] Unlike existing technologies, this application proposes a method for drawing radar monitoring areas. This method includes: rasterizing the radar tracking area to obtain a raster image; acquiring the motion trajectory of a target object within the radar tracking area; and determining the boundary of the radar monitoring area based on the motion trajectory in the raster image. This method enables automatic drawing of radar monitoring areas, eliminating the need for excessive manual operation. While maintaining drawing efficiency, it significantly reduces manual labor, thereby effectively saving drawing costs. Furthermore, using the target object's motion trajectory to determine the radar monitoring area ensures higher accuracy and a more realistic representation of the actual situation.

[0046] Optionally, such as Figure 3 As shown, Figure 3 yes Figure 1 A detailed flowchart of step S300 in this embodiment is shown. This embodiment can be achieved through, as follows: Figure 3 The method described in this embodiment implements step S300, and includes steps S310 to S340.

[0047] Step S310: Discretize the motion trajectory to obtain multiple clustered regions of the raster image.

[0048] The trajectory of a target is formed by connecting the positions of the target at different points in time. The trajectory needs to be discretized to obtain the positions the target has passed through. When the drawing end determines the monitoring area, it only needs to know the specific positions the target has passed through, that is, it only needs to know which grids on the grid map the target has passed through to obtain the basic shape of the radar monitoring area.

[0049] Specifically, in combination Figure 2 and Figure 4 analyze, Figure 4 yes Figure 2 The diagram shows the structure of the discretized motion trajectory. After discretizing the motion trajectory, the drawing end only records the grids that the target object has reached, i.e., passed through, and marks these grids on the grid map. For example, the number of target objects appearing in each grid is marked with different identifiers, which can be grayscale values ​​or probability values, etc. The larger the number of target objects that have appeared, the larger the grayscale value or probability value of the corresponding grid. For example, the first grid is identified by identifier 111, the second grid by identifier 112, the third grid by identifier 113, and the fourth grid by identifier 114. This identifier can represent the number of target objects that appear. The grids without labels are connected to form multiple clustered regions, such as... Figure 4 The diagram shows the first cluster region 110, the second cluster region 120, the third cluster region 130, the fourth cluster region 140, and the fifth cluster region 150. These cluster regions are the areas where the target object frequently gathers.

[0050] Compared to the original complex motion trajectory, the rendering end can more accurately determine the activity area of ​​the target object by clustering regions, and thus determine the radar monitoring area based on this activity area.

[0051] Step S320: Use a clustering algorithm to remove interfering regions from multiple clustering regions.

[0052] Targets monitored by radar may be small animals or other unidentified interfering objects. The movement trajectories of these objects are characterized by small or relatively isolated activity areas. Therefore, in this step, a clustering algorithm is used to remove clusters with smaller areas. For example, [the algorithm is then applied to these clusters]. Figure 4 The second cluster region 120 and the third cluster region 130 are removed, while the first cluster region 110, the fourth cluster region 140, and the fifth cluster region 150 are retained, as follows: Figure 5 As shown, Figure 5 yes Figure 4 A schematic diagram of the structure of the clustered regions after interference removal processing.

[0053] Step S330: Perform dilation processing on multiple clustered regions to obtain the grid region 200 of the radar monitoring area in the grid diagram.

[0054] The aforementioned retained cluster regions are then subjected to expansion processing.

[0055] like Figure 5 and Figure 6 As shown, Figure 6 yes Figure 5 The diagram shows the structure of the clustered regions after dilation. After removing interference regions in step S320, the raster image retains the first clustered region 110, the fourth clustered region 140, and the fifth clustered region 150. The rendering end uses a dilation algorithm to directionally dilate these three clustered regions along their corresponding dilation directions, thereby obtaining the structure shown below. Figure 6 The grid area 200 shown can serve as a prototype for the radar monitoring area.

[0056] Optionally, such as Figure 7 As shown, Figure 7 yes Figure 3 A detailed flowchart of step S320 in the embodiment is shown. For the dilation process of each cluster region, the following can be used: Figure 7 The method shown is implemented by steps S331 to S333.

[0057] Step S331: Obtain the first centroid of the current cluster region and the second centroid of the merged region of other cluster regions.

[0058] Step S332: Set the expansion direction of the current cluster region to point from the first centroid to the second centroid.

[0059] Step S333: Perform expansion processing on the current clustered region according to the expansion direction.

[0060] The expansion direction of the first cluster region 110 is the first direction X1, the expansion direction of the fourth cluster region 140 is the second direction X2, and the expansion direction of the fifth cluster region 150 is the third direction X3.

[0061] For example, to obtain the first direction X1, firstly, obtain the first centroid of the first cluster region 110, and then obtain the common centroid of the merged fourth cluster region 140 and fifth cluster region 150, which is the second centroid of the merged region of other cluster regions. Here, the first centroid refers to a point that makes all trajectory points in the first cluster region 110 uniformly symmetrical. In other words, the first centroid is similar to the center of gravity of an "object" (here, "object" refers to an object with mass and a solid form), all trajectory points in the first cluster region 110 are similar to the mass of the "object," and the first cluster region 110 is similar to the body of the "object." Similarly, the definition of the second centroid is similar to that of the first centroid; please refer to the above for details.

[0062] The orientation of the first direction X1 is from the first centroid to the second centroid, and the first direction X1 is the expansion direction of the first cluster region 110. The rendering end uses an expansion algorithm to expand the first cluster region 110 according to the first direction X1.

[0063] Specifically, the drawing end obtains the second direction X2 and the third direction X3 in the above manner, and uses the first direction X1, the second direction X2 and the third direction X3 as the expansion directions of the first cluster region 110, the fourth cluster region 140 and the fifth cluster region 150 respectively, and performs expansion processing on the above three cluster regions to obtain the grid region 200.

[0064] Step S340: Determine the boundary of the radar monitoring area from the grid area 200.

[0065] Specifically, such as Figure 8 and Figure 9 As shown, Figure 8 yes Figure 2 A schematic diagram of the initial boundary of the radar monitoring area; Figure 9 yes Figure 8A schematic diagram of the structure of the radar monitoring area after boundary smoothing. The drawing end connects the grid cells located at the edges of the grid area 200 sequentially to obtain the initial boundary 210 of the radar monitoring area. Since the initial boundary 210 does not conform to the boundary of the radar monitoring area in the real environment, the boundary characteristics of the radar monitoring area in the real environment are as follows: 1) no frequent broken line fluctuations; 2) no sharp protrusions; 3) the existence of curves with small curvature, which can be regarded as straight lines. Based on the above three points, the drawing end uses a boundary smoothing algorithm to eliminate abrupt protrusions, making the initial boundary 210 smoother.

[0066] Specifically, the drawing end uses a smoothing algorithm to eliminate inflection points less than or equal to 90° in the initial boundary 210, thereby achieving smooth processing of the initial boundary 210 and obtaining the boundary 220 of the radar monitoring area.

[0067] This application further proposes another embodiment of a method for drawing a radar monitoring area, such as... Figure 10 As shown, Figure 10 This is a flowchart illustrating a second embodiment of the radar monitoring area drawing method of this application. The drawing method of this embodiment includes the following steps:

[0068] Step S101: Rasterize the radar tracking area to obtain a raster image.

[0069] For detailed implementation methods, please refer to the above embodiments.

[0070] Step S102: Obtain the trajectory of the target object within the radar tracking area.

[0071] For detailed implementation methods, please refer to the above embodiments.

[0072] Step S103: Determine the boundary of the radar monitoring area in the grid map based on the motion trajectory.

[0073] For detailed implementation methods, please refer to the above embodiments.

[0074] Step S104: Determine whether there are any anomalies at the boundary of the radar monitoring area.

[0075] In real-world applications, the monitored area is often affected by environmental factors, leading to discrepancies. For example, at seaside resorts, the actual area permitted for tourist activity changes due to tidal fluctuations. This permitted area is the radar monitoring zone. This zone may shift due to tidal changes, or parts may fall outside the radar's range. Consequently, the radar may not be able to detect tourist activity during non-prevention periods, resulting in significant discrepancies between the radar monitoring area plotted by the final imager and the actual situation over a given time period.

[0076] Therefore, when drawing radar monitoring areas, the drawing terminal needs to perform real-time diagnostics on the drawn radar monitoring areas to ensure their accuracy and usability. This ensures that the drawn radar monitoring areas meet the needs of the actual application scenario. If the real-time diagnostics reveals a large deviation in the monitoring area, it indicates that the radar monitoring area previously drawn by the drawing terminal does not conform to the current situation. In this case, the operator should readjust the radar's monitoring range based on the actual environment, causing the radar to re-monitor the target and transmit the new motion trajectory to the drawing terminal, which then redraws the radar monitoring area based on the new motion trajectory.

[0077] Step S105: If an anomaly is found, the boundary of the radar monitoring area shall be corrected or redrawn.

[0078] Specifically, such as Figure 11 As shown, Figure 11 yes Figure 10 A detailed flowchart of step S105 is shown below. Step S105 is specifically implemented through method steps S111-S116, as follows:

[0079] Step S111: Calculate the confidence level of each cell in the grid region to obtain a confidence map.

[0080] The rendering end calculates the confidence level of each grid cell in grid region 200 to obtain a confidence map, thereby determining whether the rendered radar monitoring area matches the actual situation. Specifically, the grid cells corresponding to grid region 200 have multiple sources (it is worth noting that after the directed expansion of each clustering region mentioned above, each grid cell in grid region 200 contains the same number of targets): 1) formed by the aggregation of original radar measurement points; 2) from directed expansion; 3) caused by boundary smoothing. In terms of confidence, the three factors are ranked from largest to smallest. Therefore, the confidence level of each grid cell in grid region 200 is not the same, with grid cells closer to the boundary 220 having relatively lower confidence levels. Therefore, the confidence level of each grid cell in grid region 200 can be calculated based on the above three factors for adjustment as needed. The calculation formula is as follows:

[0081]

[0082] Where i represents the i-th column in the raster image, and j represents the j-th row in the raster image. The confidence level f of the raster cell in the i-th column and the j-th row within the raster region 200 is calculated using formula (1). (i,j) Then the confidence level f (i,j)Normalize to [0, 1] to obtain the probability P of the target object appearing in the grid. Here, a, b, and c are all constants, where a represents the measurement number weight, b represents the inflation weight, and c represents the smoothing weight. Indicates the number of measurements, i.e. This represents the number of targets within the grid region 200 that are located in the i-th column and the j-th row. This represents the minimum number of expansions, i.e. This indicates the number of times the grid cell in column i and row j within grid region 200 expands along the expansion direction in step S330. Represents the smooth number, i.e. This indicates the number of times the inflection point of the grid cell located in the i-th column and j-th row within the grid region 200 is smoothed in step S340.

[0083] The confidence level f of each grid cell within the grid area 200 can be obtained using formula (1). (i,j) , with confidence level f (i,j) After normalization, the probability P of a target appearing within a grid can be obtained, thus yielding a confidence map. This confidence map can be used to determine the reliability of the radar monitoring area currently drawn by the rendering end, allowing for adjustments to the radar monitoring area. For example, if the probability P of a target appearing in each grid cell containing boundary 220 is less than a certain threshold (this threshold was obtained from long-term actual testing and will not be elaborated upon here), it indicates that boundary 220 will not appear within these grid cells. Therefore, boundary 220 is incorrectly drawn, meaning the radar monitoring area is incorrectly drawn or needs modification.

[0084] Step S112: Extract the first region in the confidence graph where the probability P1 of the target object is greater than the first probability threshold and the second region where the probability P2 of the target object is less than the second probability threshold; wherein, the first probability threshold is greater than or equal to the second probability threshold.

[0085] Extract the first region in the confidence map where the first probability P1 of the target object is greater than the first probability threshold and the second region where the second probability P2 of the target object is less than the second probability threshold; based on the first probability P1, calculate the first theoretical number N1 of the target object appearing in the first region, and based on the second probability P2, calculate the second theoretical number N2 of the target object appearing in the second region; wherein, the first probability threshold is greater than or equal to the second probability threshold.

[0086] Step S113: Calculate the first theoretical number N1 of the target object appearing in the first region, and calculate the second theoretical number N2 of the target object appearing in the second region.

[0087] Step S114: Obtain the first actual quantity of the target object appearing in the first area and the second actual quantity of the target object appearing in the second area.

[0088] Step S115: Establish a detection function based on the first theoretical quantity N1, the second theoretical quantity N2, the first actual quantity, and the second actual quantity, and use the detection function to calculate the outlier value β of the grid region 200.

[0089] Step S116: If the abnormal value exceeds the first threshold or is less than the second threshold, it is determined that there is an abnormality at the boundary 220 of the radar monitoring area.

[0090] The steps S112-S116 above will be described in a unified manner. Specifically, the drawing end calculates the confidence level f for each grid cell in the grid area 200 (i.e., the prototype of the radar monitoring area) drawn in each time period through step S111. (i,j) This allows for the acquisition of a confidence map. Further, the probability P of a target object appearing within each grid cell of the grid region 200 is obtained from the confidence map. Specifically, the rendering end calculates the probability P1 of the region with the highest target object appearance probability in the grid region 200 (i.e., the first region where the target object appearance probability P1 is greater than a first probability threshold) and the probability P2 of the region with the lowest target object appearance probability in the grid region 200 (i.e., the second region where the target object appearance probability P2 is less than a second probability threshold). For example, in practical applications such as seaside resorts, the first region is an area with low tourist density, typically the boundary of the permitted tourist activity area, i.e., the boundary 220 of the radar monitoring area, while the second region is the area with the highest tourist density, typically the middle area of ​​the permitted tourist activity area. After rendering the radar monitoring area, the rendering end collects and statistically analyzes the number of targets in the first and second regions in real time, selecting a period as a cycle, such as 24 hours, and calculates the average value of the first actual number of targets within that cycle. The average of the second actual quantity Furthermore, assuming that the number of targets appearing in the monitored area within one cycle is N0, the formulas for calculating the first theoretical number N1 and the second theoretical number N2 are as follows:

[0091] N1=P1·N0 (2)

[0092] N2=P2·N0 (3)

[0093] After obtaining the number of targets N1 and N2 appearing in the first and second areas of each monitored area during this period using the above formulas (2) and (3), and combining this with the average of the first actual number of targets... The average of the second actual quantity Establish a detection function and calculate the outlier β. The detection function for outlier β is as follows:

[0094]

[0095] Specifically, if the outlier β is abnormally large (greater than the first threshold) or abnormally small (less than the second threshold), it indicates that the monitored area drawn during that time period does not reflect the actual situation. In this case, the operator should readjust the radar's monitoring range based on the actual environment (i.e., readjust the radar tracking area so that the target's movable range during non-prevention periods falls within the radar's tracking area). This allows the radar to re-monitor the target's movement trajectory and transmit the new trajectory to the drawing end, which then redraws the radar monitored area based on the new trajectory. The first and second thresholds for the outlier β were obtained through long-term experimental testing and will not be elaborated here.

[0096] In summary, unlike existing technologies, this application proposes a method for drawing radar monitoring areas. This method includes: rasterizing the radar tracking area to obtain a raster map; acquiring the motion trajectory of a target object within the radar tracking area; and determining the boundary of the radar monitoring area based on the motion trajectory in the raster map. This method enables automatic drawing of radar monitoring areas, eliminating the need for excessive manual operation. While maintaining drawing efficiency, it significantly reduces manual labor, thereby effectively saving drawing costs. Furthermore, using the target object's motion trajectory to determine the radar monitoring area ensures higher accuracy and better reflects reality. Simultaneously, the drawing end performs confidence calculations on the drawn radar monitoring area to obtain a confidence map. The drawing end uses the confidence map to calculate the theoretical number of targets appearing in the two extreme regions of the radar monitoring area, namely the first and second regions, and continuously records the actual number of targets appearing in each extreme region. Based on the average of the theoretical number of targets appearing in the two extreme regions and the actual number over a period of time, an outlier detection function β is established. The drawing end can maintain the radar monitoring area in real time by detecting the abnormal value β, thereby ensuring the real-time performance of the radar monitoring area. In other words, the above method can effectively ensure that the radar monitoring area drawn by the drawing end conforms to the actual situation.

[0097] This application proposes a radar monitoring method, such as Figure 12 As shown, Figure 12 This is a schematic diagram illustrating a specific process of the radar monitoring method described in this application. The specific steps of this method are as follows:

[0098] Step S400: Obtain the radar monitoring area based on the movement trajectory during the non-prevention period.

[0099] Step S500: Obtain the radar monitoring area using the above drawing method.

[0100] Step S600: In response to the appearance of the target object in the radar monitoring area during the prevention period, an alarm message is generated.

[0101] The steps S400-S600 are explained uniformly. Based on the monitoring area drawn in the above steps, the radar will monitor the specific situation within the monitoring area in real time during the prevention period. If a target object is detected during the prevention period, the radar will generate an alarm message to remind staff to take appropriate preventive measures. For example, in a seaside bathing beach application area, the drawing terminal will draw the monitoring area through the above steps during the beach's operating hours. During the beach's non-operating hours, the radar will conduct real-time monitoring of the monitoring area to prevent tourists or other organisms from entering the beach during non-operating hours, thus avoiding accidents.

[0102] This application proposes a radar monitoring system, such as Figure 13 As shown, Figure 13 This is a schematic diagram of an embodiment of the radar monitoring system of this application. The radar monitoring system 10 includes: a radar 11, a drawing device 12, and an alarm device 13.

[0103] Among them, radar 11 is a millimeter-wave radar that can generate millimeter waves, or it can be other radars with high precision that can achieve the specific functions in the above-mentioned step of drawing the radar monitoring area.

[0104] In this application, the drawing end is a drawing device 12 capable of performing the aforementioned function of drawing the radar monitoring area. Specifically, the drawing device 12 is an electronic device with certain data processing capabilities. Specifically, the drawing device 12 is signal-connected to the radar 11 and is used to receive information from the radar 11 and draw the radar monitoring area. It is used to perform rasterization processing on the radar tracking area to obtain a raster image 200, and also to acquire the motion trajectory of the target object within the radar monitoring area. Furthermore, it is used to determine the boundary 220 of the radar monitoring area in the raster image 200 based on the motion trajectory.

[0105] The alarm device 13 is connected to the radar 11 and is used to generate an alarm message when a target appears in the radar monitoring area during the protection period.

[0106] This application further proposes an electronic device, please refer to... Figure 14 , Figure 14 This is a schematic diagram of the structure of an embodiment of the electronic device of this application. The electronic device 20 includes a processor 21 and a memory 22 connected to the processor 21. The memory 22 stores program instructions. The processor 21 executes the program instructions stored in the memory 22 to perform the steps in the above-described method embodiments.

[0107] Processor 21 can also be referred to as CPU (Central Processing Unit). Processor 21 may be an integrated circuit chip with signal processing capabilities. Processor 21 can also be a general-purpose processor, digital signal processor (DSP), application-specific integrated circuit (ASIC), field-programmable gate array (FPGA), or other programmable logic device, discrete gate or transistor logic device, or discrete hardware component. A general-purpose processor can be a microprocessor or any conventional processor.

[0108] The memory 22 is used to store the program instructions required for the processor 21 to run.

[0109] The processor 21 is also used to execute program instructions stored in the memory 22 to implement the above drawing method.

[0110] This application further proposes a computer-readable storage medium. See also... Figure 15 , Figure 15 This is a schematic diagram of the structure of an embodiment of the computer-readable storage medium of this application.

[0111] The computer-readable storage medium 30 of this application embodiment stores program instructions 31, which are executed to implement the above-described drawing method.

[0112] Specifically, program instructions 31 can be formed into a program file and stored in the aforementioned storage medium in the form of a software product, so that an electronic device (which may be a personal computer, server, or network device, etc.) or processor can execute all or part of the steps of the methods of 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, or terminal devices such as computers, servers, mobile phones, and tablets.

[0113] In this embodiment, the computer-readable storage medium 30 may be, but is not limited to, a USB flash drive, SD card, PD optical drive, portable hard drive, large-capacity floppy drive, flash memory, multimedia memory card, server, etc.

[0114] In one embodiment, a computer program product or computer program is provided, the computer program product or computer program including computer instructions stored in a computer-readable storage medium. A processor of an electronic device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, causing the electronic device to perform the steps in the above-described method embodiments.

[0115] Furthermore, if the aforementioned functions are implemented as software functions and sold or used as independent products, they can be stored in a mobile terminal-readable storage medium. That is, this application also provides a storage device storing program instructions that can be executed to implement the methods of the above embodiments. This storage device can be, for example, a USB flash drive, an optical disc, or a server. In other words, this application can be embodied in the form of a software product, which includes several instructions to cause a smart terminal to execute all or part of the steps of the methods described in the various embodiments.

[0116] The above description is merely an embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent structural or procedural transformations made based on the content of the present invention specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of the present invention.

[0117] If the technical solution of this application involves personal information, the product using this technical solution has clearly informed the user of the personal information processing rules and obtained the user's voluntary consent before processing the personal information. If the technical solution of this application involves sensitive personal information, the product using this technical solution has obtained the user's separate consent before processing the sensitive personal information, and also meets the requirement of "express consent". For example, at personal information collection devices such as cameras, clear and prominent signs are set up to inform users that they have entered the scope of personal information collection and that personal information will be collected. If an individual voluntarily enters the collection scope, it is deemed that they have agreed to the collection of their personal information; or on the personal information processing device, with clear signs / information informing users of the personal information processing rules, authorization is obtained from the individual through pop-up information or by asking the individual to upload their personal information; wherein, the personal information processing rules may include information such as the personal information processor, the purpose of personal information processing, the processing method, and the types of personal information processed.

Claims

1. A method for drawing a radar monitoring area, characterized in that, include: The radar tracking area is rasterized to obtain a raster image; Acquire the trajectory of the target object within the radar tracking area; Determining the boundary of the radar monitoring area in the grid image based on the motion trajectory includes: discretizing the motion trajectory to obtain multiple clustered regions of the grid image; performing directional expansion on the multiple clustered regions along their corresponding expansion directions to obtain grid regions of the radar monitoring area in the grid image; and determining the boundary of the radar monitoring area from the grid regions. Determining whether the boundary of the radar monitoring area is abnormal includes: calculating the confidence level of each grid cell in the grid area to obtain a confidence level map; extracting a first region in the confidence level map where the probability of the target object appearing is greater than a first probability threshold and a second region where the probability of the target object appearing is less than a second probability threshold; calculating a first theoretical number of the target object appearing in the first region and a second theoretical number of the target object appearing in the second region; wherein the first probability threshold is greater than or equal to the second probability threshold; obtaining a first actual number of the target object appearing in the first region and a second actual number of the target object appearing in the second region; establishing a detection function based on the first theoretical number, the second theoretical number, the first actual number, and the second actual number, and using the detection function to calculate the outlier value of the grid area; if the outlier value exceeds the first threshold or is less than the second threshold, then it is determined that the boundary of the radar monitoring area is abnormal. If any anomalies are found, the boundaries of the radar monitoring area will be corrected or redrawn.

2. The drawing method according to claim 1, characterized in that, Before performing dilation on the plurality of clustered regions respectively, the method further includes: Clustering algorithms are used to remove interfering regions from the multiple clustered regions.

3. The drawing method according to claim 1, characterized in that, The directional expansion of the plurality of clustered regions along their respective expansion directions includes the following steps performed for each of the clustered regions: Obtain the first centroid of the current cluster region and the second centroid of the merged region of the other cluster regions; The expansion direction of the current clustering region is set to point from the first centroid to the second centroid; The current clustered region is expanded according to the expansion direction.

4. The drawing method according to claim 1, characterized in that, Determining the boundary of the radar monitoring area from the grid area includes: By connecting the grid cells located at the edges of the grid region sequentially, the initial boundary of the radar monitoring area is obtained; The initial boundary is smoothed to obtain the boundary of the radar monitoring area.

5. A radar monitoring method, characterized in that, include: Based on the movement trajectory during the non-prevention period, the radar monitoring area is obtained using the drawing method described in any one of claims 1 to 4; If the target object appears in the radar monitoring area during the prevention period, an alarm message will be generated.

6. A radar monitoring system, characterized in that, include: Radar, used to generate millimeter waves; A drawing device, connected to the radar, is used to rasterize the radar tracking area to obtain a raster image. It is also used to acquire the motion trajectory of a target object within the radar tracking area and to determine the boundary of the radar monitoring area in the raster image based on the motion trajectory. The device includes: discretizing the motion trajectory to obtain multiple clustered regions of the raster image; performing directional expansion on each of the multiple clustered regions along a corresponding expansion direction to obtain a raster region of the radar monitoring area in the raster image; and determining the boundary of the radar monitoring area from the raster region. The drawing device is further used to determine whether there is an anomaly at the boundary of the radar monitoring area; if an anomaly exists, the boundary of the radar monitoring area is corrected or redrawn; wherein, determining whether there is an anomaly at the boundary of the radar monitoring area includes: calculating the confidence level of each grid cell of the grid area to obtain a confidence level map; extracting a first region in the confidence level map where the probability of the target object appearing is greater than a first probability threshold and a second region where the probability of the target object appearing is less than a second probability threshold; calculating a first theoretical number of the target object appearing in the first region and a second theoretical number of the target object appearing in the second region; wherein, the first probability threshold is greater than or equal to the second probability threshold; obtaining a first actual number of the target object appearing in the first region and a second actual number of the target object appearing in the second region; establishing a detection function based on the first theoretical number, the second theoretical number, the first actual number, and the second actual number, and using the detection function to calculate the anomaly value of the grid area; if the anomaly value exceeds the first threshold or is less than the second threshold, it is determined that there is an anomaly at the boundary of the radar monitoring area; An alarm device, connected to the radar, is used to generate an alarm message when a target appears in the radar's monitored area during the protection period.

7. An electronic device, characterized in that, It includes a processor and a memory, wherein the memory stores program instructions, and the processor is used to execute the program instructions to implement the radar monitoring area drawing method as described in any one of claims 1-4 and / or the radar monitoring method as described in claim 5.

8. A computer-readable storage medium, characterized in that, The system stores program instructions that, when executed by a processor, can implement the radar monitoring area drawing method as described in any one of claims 1-4 and / or the radar monitoring method as described in claim 5.

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