A radar data processing system and method for surface target monitoring

Abstract

The present invention discloses a radar data processing system and method for surface target monitoring, and belongs to the field of radar data processing technology. The present invention includes: setting radar monitoring equipment and cameras to monitor the target coast conditions and personnel dynamics in real time; combining coastal terrain data and wave buoys to predict the change of water depth at each cross-sectional position of the target coast within a unit time; analyzing the position information of each active person within the target coast range according to the radar monitoring equipment and image recognition results, and tracking the dynamics of each active person within the target coast range; analyzing the safety risks of each active person within the current target coast range within a unit time according to the predicted change of water depth at each cross-sectional position of the target coast, combined with the personnel position information; judging whether to issue a safety warning. Rapid positioning of risk personnel is achieved, and rescue efficiency is improved; through early warning, the occurrence of coastal emergencies is effectively avoided, and the safety of coastal activities is enhanced.

Description

Technical Field

[0001] The present invention relates to the technical field of radar data processing, and in particular to a radar data processing system and method for surface target monitoring. Background Art

[0002] Radar is an electronic device that uses radio waves to detect target location, movement speed and other characteristics. It can be used to monitor targets at long distances and is suitable for detecting surface targets.

[0003] However, in the existing technology, the resolution ability of the radar system is limited, and the tracking ability in multi-target scenarios is insufficient. A single radar data may not be able to meet the needs of coastal risk management. In view of the complex and changeable coastal environment, how to combine other sensors to monitor surface targets and provide more accurate and comprehensive monitoring data is a difficult problem that needs to be solved. Summary of the invention

[0004] The purpose of the present invention is to provide a radar data processing system and method for surface target monitoring, which uses radar to intelligently monitor coastal conditions and tourist behavior, and immediately informs relevant personnel to intervene in the scene when a surface target is detected to have a safety risk, so as to solve the problems raised in the above background technology.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions: a radar data processing method for surface target monitoring, comprising the following steps:

[0006] Step 1: Set up radar monitoring equipment and cameras to monitor the target coastline conditions and personnel dynamics in real time; process the signal data collected by the radar in real time, and identify the active personnel within the target coastline based on image recognition technology;

[0007] Step 2: Combine coastal topography data and wave buoys to use computer simulation to predict the change in water depth at each cross-section of the target coast within a unit time;

[0008] Step 3: Analyze the location information of each person active in the target coastal area based on the radar monitoring equipment and image recognition results, and track the dynamics of each person active in the target coastal area;

[0009] Step 4: Based on the water depth changes at each cross-section of the target coast predicted in step 2 and combined with the personnel location information, analyze the safety risks of each active person within the current target coast within a unit time;

[0010] Step 5: Based on the analysis results in step 4, if there are safety risks to people active within the current target coastline, a safety warning will be issued to notify relevant personnel to handle the risks.

[0011] Furthermore, the step 1 specifically includes the following steps:

[0012] Step 1.1: radar monitoring equipment and cameras are set up on the land of the target coast, and the activities within the target coast are monitored by the radar monitoring equipment, and the activities within the target coast are monitored in real time by the camera; the coast refers to the area where the land and the sea meet, and the sea and the land in this area interact actively. The high tide line of the seawater changes in a complex manner when extending towards the land, and the depth of the seawater increases significantly when extending towards the sea;

[0013] The active subjects refer to the mobile targets monitored within the target coast, including active personnel, ships, animals and coastal facilities, etc.

[0014] Step 1.2: intercept the signal sent back by the radar at a set time interval, remove the noise and interference signal in the signal, use the Doppler effect to mark the moving subject, and convert the processed radar data into a two-dimensional radar image;

[0015] Extract the features related to the active subject from the intercepted signal, use the target detection algorithm to identify the extracted features, identify the active subject and its location, number each active subject and mark it in the radar image; establish an active subject set, denoted as OB={Y d |d∈[0,z]}, where Y d represents the dth active subject in the active subject set; z represents the total number of active subjects in the active subject set;

[0016] Step 1.3: Based on real-time visual monitoring by the camera, the collected images of the target coast are annotated through the YOLO model, and the position of the active person is output; the position is composed of the vertex coordinates of the upper left corner and the lower right corner of the bounding box annotated by the model, and the position of any active person is recorded as (x1, y1, x2, y2).

[0017] Furthermore, the wave buoy in step 2 is placed in the sea area near the coast and is equipped with a variety of sensors that can measure the wave height, wave direction and wave period of the waves; when using a computer to simulate and predict the change of water depth at each cross-sectional position of the target coast within a unit time, the maximum water depth at each cross-sectional position of the target coast within the next unit time is calculated according to the following formula:

[0018] ;

[0019] ;

[0020] Among them, SS ’ (k) represents the maximum water depth at the kth section of the target coast in the next unit time, SSi (k) represents the seabed depth at the kth cross-sectional position of the target coast in the i-th unit time, k=1, 2, ...s, s represents the farthest cross-sectional position of the target coast; the seabed depth represents the vertical distance from the sea level to the seabed topography, and the sea level represents the standardized mean sea level;

[0021] H represents the wave height at the farthest cross-section position in the i-th unit time of the target coast, which is obtained by wave buoy measurement; L represents the wave wavelength in the i-th unit time, g is the gravitational acceleration, and T represents the wave period of the wave, which is obtained by wave buoy recording;

[0022] α is the seafloor slope at the kth cross-section of the target coast obtained through coastal topography data;

[0023] It represents the error coefficient, which is selected by relevant personnel based on the seabed friction and sediment composition of the target coast.

[0024] Furthermore, the step 3 specifically includes the following steps:

[0025] Step 3.1: Based on the positions of the set of active subjects and active personnel, synchronize the timestamps, process the marked radar image and the labeled target coast image, align the coordinate systems of the two images through image registration, superimpose the radar image and the target coast image, mark the active subjects in the radar image covered by the bounding box of the target coast as active personnel, and generate the set of active personnel, denoted as OP={Y p |p∈[1,e]},Y p represents the pth active person in the active person set, and e represents the total number of active persons in the active person set;

[0026] Step 3.2: Based on the moving target indicator, the dynamics of each active person within the target coastline are tracked, and the motion trajectory of each active subject is output. The activity trajectory of any active person is recorded as {Yp1→Yp2→...→Yp n |p∈[1,e]}, where Yp n Indicates the position coordinates of the p-th active person in the radar image at the n-th monitoring time point;

[0027] Step 3.3: Analyze the personnel dynamics of the active personnel and generate a personnel dynamics dataset corresponding to each active person within the target coastal area, denoted as RY={Y p (j)|p∈[1,e],j∈[1,3]}; where j represents the dynamic level of the active personnel. According to the distance between the cross-sectional position of the active personnel and the farthest cross-sectional position of the target coast, the dynamic level of the active personnel is divided into three levels, specifically:

[0028] When the distance is greater than C1, the active person is determined to be at the first dynamic level;

[0029] When C2<distance≤C1, it is determined that the active person belongs to the second dynamic level;

[0030] When C2 ≥ distance, the active person is judged to belong to the third dynamic level;

[0031] Among them, C1>C2; when the distance between the cross-sectional position of the active person and the farthest cross-sectional position of the target coast is smaller, it is considered that the dynamic level of the active person is higher and the existing safety risk is higher.

[0032] Furthermore, the step 4 analyzes the safety risk value of each active person within the target coast based on the personnel dynamic data set and the water depth change at each cross-section position of the target coast predicted in step 2, and specifically calculates the safety risk value of the pth active person in the target coast according to the following formula:

[0033] ;

[0034] Among them, l k Indicates the current cross-sectional location of the active personnel, SS ’ (l k ) represents the target coast lth time in the next unit time k The maximum water depth at each cross-section position, f(j) represents the influence coefficient corresponding to the dynamic level of the active personnel, which is preset by the relevant staff; Refers to the impact factor of the wave impact on the participants, indicating the Yp of the participants n With Yp n-1 The value of the displacement between them in the x-axis direction;

[0035] When the event staff n With Yp n-1 When the displacement between is positive in the x-axis direction, , when the activity staff's Yp n With Yp n-1 When the displacement between the two is negative in the x-axis direction, ;

[0036] It should be noted that Yp n-1 represents the position coordinates of the p-th active person in the radar image at the n-1-th monitoring time point, the x-axis represents the horizontal direction in the coordinate system corresponding to the radar image, and refers to the longitudinal position of the radar scan; the x-axis direction represents the direction of the x-axis in the coordinate system corresponding to the radar image from land to sea;

[0037] When the safety risk value of any person active in the target coast exceeds the preset safety threshold, it is determined that the person is at safety risk.

[0038] According to the above steps, by processing and analyzing the radar data, the movements of people within the target coastal area can be obtained. Based on the changes in sea water in the near-coastal area, the situation of people active on the coast can be focused on. By analyzing the changes in their positions on the coast, the safety risks of people active on the coast can be analyzed to ensure the dynamic safety of people active on the coast.

[0039] A radar data processing system for surface target monitoring includes the following modules:

[0040] Radar management module, used to manage radar monitoring equipment installed on the target coast;

[0041] The personnel tracking module is used to track the activities of people within the target coastal area;

[0042] Risk analysis module, used to analyze the safety risks of people active within the target coastal area;

[0043] The coastal management module is used to manage the target coast according to the output results of the risk analysis module.

[0044] Further, the radar management module includes a radar setting unit and a radar data processing unit;

[0045] The radar setting unit is used to set up radar monitoring equipment and cameras on the land of the target coast, monitor the active subjects within the target coast range through the radar monitoring equipment, and perform real-time visual monitoring of the active subjects within the target coast range through the camera;

[0046] The radar data processing unit is used to intercept the signal sent back by the radar at a set time interval, remove noise and interference signals in the signal, use the Doppler effect to mark the active subject, and convert the processed radar data into a two-dimensional radar image; extract features related to the active subject from the intercepted signal, use the target detection algorithm to identify the extracted features, identify the active subject and the position of the active subject, and number each active subject and mark it in the radar image.

[0047] Further, the personnel tracking module includes a personnel identification unit and a personnel positioning unit;

[0048] The personnel identification unit annotates the collected images of the target coast through the YOLO model based on the real-time visual monitoring of the camera, and outputs the location of the active personnel;

[0049] The personnel positioning unit synchronizes timestamps based on the positions of the active subject set and the active personnel, processes the marked radar image and the labeled image of the target coast, aligns the coordinate systems of the two images through image registration, superimposes the radar image and the image of the target coast, and marks the active subjects in the radar image covered within the boundary box of the target coast as active personnel.

[0050] Further, the risk analysis module includes a coast prediction unit, a personnel safety analysis unit and a risk identification unit;

[0051] The coast prediction unit is used to combine the coast topography data and the wave buoy, and use computer simulation to predict the change of water depth at each cross-section position of the target coast within a unit time;

[0052] The personnel safety analysis unit is used to analyze the safety risk value of each active person within the target coast range according to the personnel dynamic data set and the water depth change of each cross-section position of the target coast predicted by the coast prediction unit;

[0053] The risk identification unit is used to issue a safety warning and notify relevant personnel to handle the risk according to the analysis result of the personnel safety analysis unit when there are safety risks of people active in the target coastal area.

[0054] Compared with the prior art, the beneficial effects achieved by the present invention are:

[0055] The present invention manages the radar monitoring equipment installed on the target coast through a radar management module, monitors the target coast conditions and personnel dynamics in real time, and the radar can work under all-weather conditions to ensure the reliability and coverage of monitoring; combined with image recognition technology, it can more accurately identify active personnel and distinguish different types of targets, reducing the false alarm rate.

[0056] The present invention tracks the behavior of people active in the target coastline through a people tracking module; through the combined use of radar and camera, the position and trajectory of people active on the coast can be tracked in real time, providing detailed dynamic information.

[0057] The present invention analyzes the safety risks of people active in the target coastal area through a risk analysis module; uses computer simulation to predict water depth changes, and can evaluate potential risk areas in advance; combines the water depth change prediction and personnel dynamic information at each cross-sectional location of the coast, and can effectively evaluate the safety risks of active personnel and reduce the possibility of accidents.

[0058] The present invention manages the target coast according to the output results of the risk analysis module through the coast management module; when the risk analysis module finds that there are safety risks for active personnel, it provides accurate location information and immediately notifies relevant staff to intervene, thereby improving rescue efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0060] Figure 1 It is a structural schematic diagram of a radar data processing system for surface target monitoring according to the present invention;

[0061] Figure 2 The present invention is a flow chart of a radar data processing method for surface target monitoring. DETAILED DESCRIPTION

[0062] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0063] See also Figure 1 In the first embodiment, a radar data processing system for surface target monitoring is provided, comprising the following modules:

[0064] A radar management module is used to manage the radar monitoring equipment set up on the target coast; it includes a radar setting unit and a radar data processing unit;

[0065] The radar setting unit is used to set up radar monitoring equipment and cameras on the land of the target coast, monitor the active subjects within the target coast range through the radar monitoring equipment, and perform real-time visual monitoring of the active subjects within the target coast range through the camera;

[0066] The radar data processing unit is used to intercept the signal sent back by the radar at a set time interval, remove noise and interference signals in the signal, use the Doppler effect to mark the active subject, and convert the processed radar data into a two-dimensional radar image; extract the features related to the active subject from the intercepted signal, use the target detection algorithm to identify the extracted features, identify the active subject and the position of the active subject, and number each active subject and mark it in the radar image.

[0067] The personnel tracking module is used to track the activities of people within the target coastal area; it includes a personnel identification unit and a personnel positioning unit;

[0068] The personnel identification unit uses the YOLO model to annotate the collected images of the target coast based on real-time visual monitoring by the camera and output the location of the active personnel;

[0069] The personnel positioning unit synchronizes the timestamp based on the positions of the active subject set and the active personnel, processes the marked radar image and the annotated image of the target coast, aligns the coordinate systems of the two images through image registration, superimposes the radar image and the image of the target coast, and marks the active subjects in the radar image covered by the boundary box of the target coast as active personnel.

[0070] The risk analysis module is used to analyze the safety risks of people in the target coastal area; it includes a coastal prediction unit, a personnel safety analysis unit and a risk identification unit;

[0071] The coastal prediction unit is used to combine coastal topographic data and wave buoys, and use computer simulation to predict the change of water depth at each cross-section of the target coast within a unit time;

[0072] The personnel safety analysis unit is used to analyze the safety risk value of each active person within the target coast based on the personnel dynamic data set and the water depth change of each cross-section position of the target coast predicted by the coast prediction unit;

[0073] The risk identification unit is used to issue a safety warning and notify relevant personnel to handle the risk based on the analysis results of the personnel safety analysis unit when there are safety risks to the active personnel within the target coastal area.

[0074] The coastal management module is used to manage the target coast according to the output results of the risk analysis module.

[0075] See also Figure 2 In the second embodiment, a radar data processing method for surface target monitoring is provided, comprising the following steps:

[0076] Step 1: Set up radar monitoring equipment and cameras to monitor the target coastline conditions and personnel dynamics in real time; process the signal data collected by the radar in real time, and identify the active personnel within the target coastline based on image recognition technology;

[0077] Step 1.1: radar monitoring equipment and cameras are set up on the land of the target coast, and the activities within the target coast are monitored by the radar monitoring equipment, and the activities within the target coast are monitored in real time by the camera; the coast refers to the area where the land and the sea meet, and the sea and the land in this area interact actively. The high tide line of the seawater changes in a complex manner when extending towards the land, and the depth of the seawater increases significantly when extending towards the sea;

[0078] The radar equipment is configured with a moving target indicator (MTI) to filter out static background and track the movement of people within the target coastal area to improve the accuracy and efficiency of radar monitoring.

[0079] The active subjects refer to the mobile targets monitored within the target coast, including active personnel, ships, animals and coastal facilities, etc.

[0080] In one implementation, radar monitoring equipment and cameras are installed on lighthouses or towers that can cover the target monitoring area, ensuring that the radar's scanning range covers the range of activities of people on the coast; radar equipment with high resolution and long-distance monitoring capabilities is selected to ensure that the radar system can work in a variety of weather conditions, including rainy days, foggy days, and at night. Combining the long-range detection capability of the radar and the visual monitoring of the camera, a more comprehensive understanding of the dynamics of people on the target coast can be achieved.

[0081] Step 1.2: intercept the signal sent back by the radar at a set time interval, remove the noise and interference signal in the signal, use the Doppler effect to mark the moving subject, and convert the processed radar data into a two-dimensional radar image;

[0082] Extract the features related to the active subject from the intercepted signal, use the target detection algorithm to identify the extracted features, identify the active subject and its location, number each active subject and mark it in the radar image; establish an active subject set, denoted as OB={Y d |d∈[0,z]}, where Y d represents the dth active subject in the active subject set; z represents the total number of active subjects in the active subject set;

[0083] Preferably, the target detection algorithm may be a convolutional neural network;

[0084] Step 1.3: Based on real-time visual monitoring by the camera, the collected images of the target coast are annotated through the YOLO model, and the position of the active person is output; the position is composed of the vertex coordinates of the upper left corner and the lower right corner of the bounding box annotated by the model, and the position of any active person is recorded as (x1, y1, x2, y2).

[0085] Step 2: Combine coastal topography data and wave buoys to use computer simulation to predict the change in water depth at each cross-section of the target coast within a unit time;

[0086] Specifically, the maximum water depth at each cross-section of the target coast in the next unit time is calculated according to the following formula:

[0087] ;

[0088] ;

[0089] Among them, SS ’ (k) represents the maximum water depth at the kth section of the target coast in the next unit time, SS i (k) represents the seabed depth at the kth cross-sectional position of the target coast in the ith unit time, k=1, 2, ...s, s represents the farthest cross-sectional position of the target coast; the seabed depth represents the vertical distance from the sea level to the seabed topography, and the sea level represents the standardized mean sea level, which can be the geodetic sea level or the theoretical lowest tide level;

[0090] H represents the wave height at the farthest cross-section position in the i-th unit time of the target coast, which is obtained by measuring the wave buoy; L represents the wave length in the i-th unit time, and g is the gravitational acceleration, g=9.81m / s 2 ; T represents the wave period of the ocean wave, which is obtained through wave buoy records;

[0091] α is the seafloor slope at the kth cross-section of the target coast obtained through coastal topography data;

[0092] represents the error coefficient, which is selected by relevant personnel based on the seabed friction and sediment composition of the target coast;

[0093] Step 3: Analyze the location information of each person active in the target coastal area based on the radar monitoring equipment and image recognition results, and track the dynamics of each person active in the target coastal area;

[0094] Step 3.1: Based on the positions of the set of active subjects and active personnel, synchronize the timestamps, process the marked radar image and the labeled target coast image, align the coordinate systems of the two images through image registration, superimpose the radar image and the target coast image, mark the active subjects in the radar image covered by the bounding box of the target coast as active personnel, and generate the set of active personnel, denoted as OP={Y p |p∈[1,e]},Y p represents the pth active person in the active person set, and e represents the total number of active persons in the active person set;

[0095] Step 3.2: Based on the moving target indicator, the dynamics of each active person within the target coastline are tracked, and the motion trajectory of each active subject is output. The activity trajectory of any active person is recorded as {Yp1→Yp2→...→Yp n |p∈[1,e]}, where Yp n Indicates the position coordinates of the p-th active person in the radar image at the n-th monitoring time point;

[0096] Step 3.3: Analyze the personnel dynamics of the active personnel and generate a personnel dynamics dataset corresponding to each active person within the target coastal area, denoted as RY={Y p (j)|p∈[1,e],j∈[1,3]}; where j represents the dynamic level of the active personnel. According to the distance between the cross-sectional position of the active personnel and the farthest cross-sectional position of the target coast, the dynamic level of the active personnel is divided into three levels, specifically:

[0097] When the distance is greater than C1, the active person is determined to be at the first dynamic level;

[0098] When C2<distance≤C1, it is determined that the active person belongs to the second dynamic level;

[0099] When C2 ≥ distance, the active person is judged to belong to the third dynamic level;

[0100] Among them, C1>C2; when the distance between the cross-sectional position of the active person and the farthest cross-sectional position of the target coast is smaller, it is considered that the dynamic level of the active person is higher and the safety risk is higher;

[0101] Step 4: Based on the water depth changes at each cross-section of the target coast predicted in step 2 and combined with the personnel location information, analyze the safety risks of each active person within the current target coast within a unit time;

[0102] Specifically, the safety risk value of the pth active person in the target coast is calculated according to the following formula:

[0103] ;

[0104] Among them, l k Indicates the current cross-sectional location of the active personnel, SS ’ (l k ) represents the target coast lth time in the next unit time k The maximum water depth at each cross-section position, f(j) represents the influence coefficient corresponding to the dynamic level of the active personnel, which is preset by the relevant staff; Refers to the impact factor of the wave impact on the participants, indicating the Yp of the participants n With Yp n-1 The value of the displacement between them in the x-axis direction;

[0105] When the event staff n With Yp n-1 When the displacement between is positive in the x-axis direction, , when the activity staff's Yp n With Yp n-1 When the displacement between the two is negative in the x-axis direction, ;

[0106] It should be noted that Yp n-1 represents the position coordinates of the p-th active person in the radar image at the n-1-th monitoring time point, the x-axis represents the horizontal direction in the coordinate system corresponding to the radar image, and refers to the longitudinal position of the radar scan; the x-axis direction represents the direction of the x-axis in the coordinate system corresponding to the radar image from land to sea;

[0107] When the safety risk value of any person active in the target coast exceeds the preset safety threshold, it is determined that the person is at safety risk.

[0108] According to the above steps, by processing and analyzing the radar data, the movements of people within the target coastal area can be obtained. Based on the changes in sea water in the near-coastal area, the situation of people active on the coast can be focused on. By analyzing the changes in their positions on the coast, the safety risks of people active on the coast can be analyzed to prevent safety risks to people active on the coast.

[0109] Exemplarily, when the dynamic level of the pth active person belongs to the first dynamic level, and the impact factor of the wave impact on the active person is positive, the safety risk value of the pth active person is:

[0110] ;

[0111] The safety risk value of the pth active person does not exceed the preset safety threshold, and it is determined that there is no safety risk for the active person.

[0112] Step 5: Based on the analysis results in step 4, if there are safety risks to people active within the current target coastline, a safety warning will be issued to notify relevant personnel to handle the risks.

[0113] Establish an emergency response mechanism. Once the radar detects abnormal movements or potential dangers, issue immediate warning information through radio to guide tourists to evacuate quickly.

[0114] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0115] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A radar data processing method for surface target monitoring, characterized in that: The following steps are involved: Step 1: Set up radar monitoring equipment and cameras to monitor the target coast conditions and personnel dynamics in real time; Process the signal data collected by the radar in real time, and identify the people active within the target coast based on image recognition technology; Step 2: Combine coastal topography data and wave buoys to use computer simulation to predict the change in water depth at each cross-section of the target coast within a unit time; Step 3: Analyze the location information of each person active in the target coastal area based on the radar monitoring equipment and image recognition results, and track the dynamics of each person active in the target coastal area; Step 4: Based on the water depth changes at each cross-section of the target coast predicted in step 2 and combined with the personnel location information, analyze the safety risks of each active person within the current target coast within a unit time; Step 5: Based on the analysis results in step 4, if there are safety risks to personnel within the current target coastline, a safety warning is issued to notify relevant personnel to handle the risk; When using a computer to simulate and predict the change in water depth at each cross-sectional location of the target coast within a unit time in step 2, the maximum water depth at each cross-sectional location of the target coast within the next unit time is calculated according to the following formula: ； ； Among them, SS ’ (k) represents the maximum water depth at the kth section of the target coast in the next unit time, SS i (k) represents the seabed depth at the kth cross-section position of the target coast in the i-th unit time, k = 1, 2, ... s, s represents the farthest cross-section position of the target coast; H represents the wave height at the farthest cross-section position in the i-th unit time of the target coast, which is obtained by wave buoy measurement; L represents the wave wavelength in the i-th unit time, g is the gravitational acceleration, and T represents the wave period of the wave, which is obtained by wave buoy recording; α is the seafloor slope at the kth cross-section of the target coast obtained through coastal topography data; Represents the error coefficient.

2. A radar data processing method for surface target monitoring according to claim 1, characterized in that: The step 1 specifically comprises the following steps: Step 1.1: Set up radar monitoring equipment and cameras on the land of the target coast, monitor the activities of the subjects within the target coast through the radar monitoring equipment, and conduct real-time visual monitoring of the subjects within the target coast through the camera; Step 1.2: intercept the signal sent back by the radar at a set time interval, use the Doppler effect to mark the moving subject, and convert the processed radar data into a two-dimensional radar image; Extract the features related to the active subject from the intercepted signal, use the target detection algorithm to identify the extracted features, identify the active subject and its location, number each active subject and mark it in the radar image; establish an active subject set, denoted as OB={Y d |d∈[0,z]}, where Y d represents the dth active subject in the active subject set; z represents the total number of active subjects in the active subject set; Step 1.3: Based on real-time visual monitoring by the camera, the YOLO model is used to annotate the collected images of the target coast and output the location of the active personnel.

3. The radar data processing method for surface target monitoring according to claim 1, characterized in that: The step 3 specifically comprises the following steps: Step 3.1: Based on the positions of the set of active subjects and active personnel, synchronize the timestamps, process the marked radar image and the labeled target coast image, align the coordinate systems of the two images through image registration, superimpose the radar image and the target coast image, mark the active subjects in the radar image covered by the bounding box of the target coast as active personnel, and generate the set of active personnel, denoted as OP={Y p |p∈[1,e]},Y p represents the pth active person in the active person set, and e represents the total number of active persons in the active person set; Step 3.2: Based on the moving target indicator, the dynamics of each active person within the target coastline are tracked, and the motion trajectory of each active subject is output. The activity trajectory of any active person is recorded as {Yp1→Yp2→...→Yp n |p∈[1,e]}, where Yp n Indicates the position coordinates of the p-th active person in the radar image at the n-th monitoring time point; Step 3.3: Analyze the personnel dynamics of the active personnel and generate a personnel dynamics dataset corresponding to each active person within the target coastal area, denoted as RY={Y p (j)|p∈[1,e],j∈[1,3]}; where j represents the dynamic level of the active person.

4. The radar data processing method for surface target monitoring according to claim 1, characterized in that: The step 4 analyzes the safety risk value of each active person within the target coast based on the personnel dynamic data set and the water depth change at each cross-section position of the target coast predicted in step 2, and specifically calculates the safety risk value of the pth active person in the target coast according to the following formula: ； Among them, l k Indicates the current cross-sectional location of the active personnel, SS ’ (l k ) represents the target coast lth time in the next unit time k The maximum water depth at each cross-section position, f(j) represents the influence coefficient corresponding to the dynamic level of the active personnel, which is preset by the relevant staff; Refers to the impact factor of the wave impact on the participants, indicating the Yp of the participants n With Yp n-1 The value of the displacement between them in the x-axis direction; When the event staff n With Yp n-1 When the displacement between is positive in the x-axis direction, , when the activity staff's Yp n With Yp n-1 When the displacement between the two is negative in the x-axis direction, ; When the safety risk value of any person active in the target coast exceeds the preset safety threshold, it is determined that the person is at safety risk.

5. A radar data processing system for surface target monitoring, characterized in that: Includes the following modules: Radar management module, used to manage radar monitoring equipment installed on the target coast; The personnel tracking module is used to track the activities of people within the target coastal area; Risk analysis module, used to analyze the safety risks of people active within the target coastal area; The coastal management module is used to manage the target coast according to the output results of the risk analysis module; The risk analysis module includes a coast prediction unit, a personnel safety analysis unit and a risk identification unit; The coast prediction unit is used to combine the coast topography data and the wave buoy, and use computer simulation to predict the change of water depth at each cross-section position of the target coast within a unit time: The maximum water depth at each cross-section of the target coast in the next unit time is calculated according to the following formula: ； ； Among them, SS ’ (k) represents the maximum water depth at the kth section of the target coast in the next unit time, SS i (k) represents the seabed depth at the kth cross-section position of the target coast in the i-th unit time, k = 1, 2, ... s, s represents the farthest cross-section position of the target coast; H represents the wave height at the farthest cross-section position in the i-th unit time of the target coast, which is obtained by wave buoy measurement; L represents the wave wavelength in the i-th unit time, g is the gravitational acceleration, and T represents the wave period of the wave, which is obtained by wave buoy recording; α is the seafloor slope at the kth cross-section of the target coast obtained through coastal topography data; represents the error coefficient; The personnel safety analysis unit is used to analyze the safety risk value of each active person within the target coast range according to the personnel dynamic data set and the water depth change of each cross-section position of the target coast predicted by the coast prediction unit; The risk identification unit is used to issue a safety warning and notify relevant personnel to handle the risk according to the analysis result of the personnel safety analysis unit when there are safety risks of people active in the target coastal area.

6. A radar data processing system for surface target monitoring according to claim 5, characterized in that: The radar management module includes a radar setting unit and a radar data processing unit; The radar setting unit is used to set up radar monitoring equipment and cameras on the land of the target coast, monitor the active subjects within the target coast range through the radar monitoring equipment, and perform real-time visual monitoring of the active subjects within the target coast range through the camera; The radar data processing unit is used to intercept the signal sent back by the radar at a set time interval, remove noise and interference signals in the signal, use the Doppler effect to mark the active subject, and convert the processed radar data into a two-dimensional radar image; extract features related to the active subject from the intercepted signal, use the target detection algorithm to identify the extracted features, identify the active subject and the position of the active subject, and number each active subject and mark it in the radar image.

7. A radar data processing system for surface target monitoring according to claim 5, characterized in that: The personnel tracking module includes a personnel identification unit and a personnel positioning unit; The personnel identification unit annotates the collected images of the target coast through the YOLO model based on the real-time visual monitoring of the camera, and outputs the location of the active personnel; The personnel positioning unit synchronizes timestamps based on the positions of the active subject set and the active personnel, processes the marked radar image and the labeled image of the target coast, aligns the coordinate systems of the two images through image registration, superimposes the radar image and the image of the target coast, and marks the active subjects in the radar image covered within the boundary box of the target coast as active personnel.

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