A method for rapid detection of low-altitude flying objects and flight safety warning

Abstract

The present invention relates to the field of low-altitude flying object technology and provides a method for rapid low-altitude flying object detection and flight safety warning, comprising: step 1: phased array radar scanning; step 2: establishing an airspace grid space-time coordinate system; step 3: scanning the airspace; step 4: positioning the airspace grid; step 5: correcting a trajectory prediction model; step 6: predicting flight trajectories; step 7: establishing a flight safety model; step 8: flight impact assessment; and step 9: providing a flight safety warning. The present invention can effectively perform rapid low-altitude flying object detection and flight safety warning.

Description

Technical Field

[0001] The present invention relates to the technical field of low-altitude flying objects, and in particular to a method for rapid detection of low-altitude flying objects and flight safety early warning. Background Art

[0002] With the increasing frequency of low-altitude flight activities, the number of low-altitude flying objects, including drones, light aircraft, and hot air balloons, has increased dramatically, and their safety issues have become increasingly prominent. Effective detection and supervision of low-altitude flying objects has become a key link in ensuring low-altitude flight safety and maintaining national and public security.

[0003] Currently, the commonly used low-altitude flying object monitoring technologies include radar detection technology, photoelectric detection technology and radio monitoring technology. All three technologies have their own advantages and disadvantages. Traditional radar detection technology can detect and track low-altitude flying objects more stably, but there are detection blind spots; photoelectric detection technology integrates optical imaging technology, which works well under good light conditions, but is not as effective in severe weather conditions; radio monitoring technology monitors by scanning the radio spectrum of the monitored object, and is completely ineffective for objects without electromagnetic signals (floating objects).

[0004] Low-altitude flying objects have the following characteristics:

[0005] Miniaturization and low detectability: Many low-altitude flying objects (especially consumer-grade drones) are small in size, have small radar cross-sectional areas, and have unclear infrared characteristics. Aircraft with stealth designs and composite materials are more difficult to detect by conventional detection methods, posing great challenges to detection technology.

[0006] Low speed and strong maneuverability: Low-altitude flying objects have a wide range of speeds, from nearly hovering drones to high-speed light aircraft, and can quickly change flight attitude and heading. This requires the detection system to have rapid target update and high-precision tracking capabilities. Existing technologies often lag when dealing with complex and maneuverable targets. Summary of the Invention

[0007] The present invention provides a method for rapid detection of low-altitude flying objects and flight safety warning, which can better perform rapid detection of low-altitude flying objects and flight safety warning.

[0008] A method for rapid detection of low-altitude flying objects and flight safety early warning according to the present invention comprises the following steps:

[0009] Step 1: Phased array radar scanning;

[0010] Step 2: Establish a spatial grid space-time coordinate system. Use phased array radar, radar network, or designated point as the reference to establish the spatial grid coordinate system. The time reference is based on Beidou satellite timing.

[0011] Step 3: Scan the airspace. The scanning strategy drives the phased array radar to scan the airspace and detect active or passive flying objects in the airspace, regardless of whether the flying objects have power or heat sources, and are not affected by weather.

[0012] Step 4: Airspace grid positioning: Based on the detection and warning airspace grid coordinate system, the time series dimension is introduced to achieve the airspace grid spatiotemporal positioning of the aircraft and form the spatiotemporal trajectory of the aircraft.

[0013] Step 5: Correction of trajectory prediction model: Establish an attitude prediction model based on the real-time attitude of the detected flying object, and correct the subsequent attitude prediction model of the flying object based on the previous continuous attitude change rate;

[0014] Step 6: Flight trajectory prediction: introduce time series variables to perform attitude integration on the aircraft to predict the trajectory of the aircraft.

[0015] Step 7: Establish a flight safety model. The flight safety model consists of two parts: the first is the flight safety model of the aircraft itself, which is built based on the aircraft's own posture and flight characteristics; the second is the airspace safety model, which is built based on the flight characteristics and trajectory of all aircraft in the airspace grid, focusing more on the mutual influence between aircraft in the airspace.

[0016] Step 8: Flight impact assessment. This includes two aspects: first, the safety impact of the airspace environment on the aircraft, which is assessed through the airspace grid safety factor; and second, the safety impact of the aircraft on other aircraft in the airspace, which is assessed through the airspace grid safety factor.

[0017] Step 9: Flight safety warning: classify flight safety risks and trigger different warning mechanisms for different risk levels to issue warning information to flying objects and airspace regulators.

[0018] Preferably, in step 1, a micro phased array radar is used to perform airspace scanning, and the phased array module controls the phase of the electromagnetic wave to perform large-scale airspace scanning through the array antenna and multiple radars are networked to reduce the problem of scanning blind spots.

[0019] Preferably, step 2 specifically includes:

[0020] (2.1) Spatial grid space-time coordinate system;

[0021] The spatial grid space-time coordinate system is a dynamic matrix with multi-dimensional dynamic granularity.

[0022]

[0023] Where: C is the spatial grid space-time coordinate, which is managed by grid precision level and time series slice; C nt is the spatial grid coordinate of the n-level grid at time phase t;

[0024] (2.2) Spatial grid dimension composition;

[0025] The airspace grid is a spatial unit. The entire regulatory airspace is dynamically divided into a series of closely connected virtual cubes without gaps. The detection, positioning and safety warning of flying objects are all carried out with the airspace grid as the smallest unit. Each airspace grid G t Contains various information:

[0026] G t =(x,y,z,l,w,t)

[0027] Where: x, y, z are the spatial positions of the grid in the entire grid matrix, defined using a right-handed coordinate system; l is the grid level at which the grid is located, with l>0; t is the state of the grid at time phase t in the space-time sequence; and w is the airspace safety factor of the grid at time phase t, which changes with the changes in the overall airspace safety environment.

[0028] Preferably, in step 3, the phased array radar realizes continuous scanning detection by controlling the periodic change of the phase of the radar wave;

[0029]

[0030] in, The amount of radar wave phase change; d is the spacing between antenna units; λ is the radar wavelength; θ is the scanning angle of the beam;

[0031] (3.1) Detection target distance;

[0032] The target distance R is calculated by measuring the time delay τ between the transmitted signal and the received signal:

[0033]

[0034] Where c is the speed of light;

[0035] (3.2) Detect target speed;

[0036] By measuring the Doppler frequency shift f of the received signal d To calculate the target velocity v:

[0037]

[0038] Where λ is the radar wavelength;

[0039] (3.3) Detection target angle;

[0040] The target angle θ is calculated by measuring the phase difference Δφ of the received signal between different antenna elements:

[0041]

[0042] Preferably, in step 4, the distance, speed and angle of the detected object measured by the radar in step 3 are mapped to the spatial grid coordinate system and stored as spatial grid spatiotemporal coordinates to provide source data for subsequent safety assessment and early warning;

[0043] (4.1) Polar coordinates are converted to rectangular coordinates;

[0044] x=r cos(φ)cos(θ)

[0045] y=r cos(φ)sin(θ)

[0046] z=r sin(φ)

[0047] Where r is the distance from the object to the origin, θ is the azimuth angle, and φ is the pitch angle;

[0048] (4.2) The spatial rectangular coordinates are mapped to the spatial grid coordinates;

[0049] Mapping the (x, y, z) coordinates in the rectangular coordinate system to the spatial grid requires quantization according to the level and range of the grid;

[0050] Grid Range:

[0051] [x min ,x max ]×(y min ,y max ]×[z min ,z max ]

[0052] The grid resolution is Δx×Δy×Δz;

[0053] Mesh Mapping:

[0054] Map (x,y,z) coordinates to grid indices (i,j,k):

[0055]

[0056] Preferably, in step 5, specifically:

[0057] The attitude of the object is estimated by combining the dynamic model of the flying object and radar measurement data based on Kalman filtering;

[0058] Posture model M:

[0059] M=(p x ,p y ,p z ,v x ,v y ,v z ,θx ,θ y ,θ z )

[0060] where p x , p y , p z is the position of the flying object, v x , v y , v z is the speed of the flying object, θ x ,θ y ,θ z is the acceleration of the flying object;

[0061] Detection model z k :

[0062] z k =H k x k +v k

[0063] Among them: H k is the observation matrix, which describes how the state is mapped to the observation value; x k is the observation quantity, a group of variables describing the state of the flying object; v k is the observation noise, assuming it is zero-mean Gaussian noise, and the covariance matrix is ​​R k ;

[0064] Posture changes:

[0065] x k =F k x k-1 +B k u k +w k

[0066] Among them: F k is the attitude transfer matrix, which describes how the attitude is transferred from time k-1 to time k; B k is the control input matrix, describing the external factors u k Effect on posture; w k is the process noise, assumed to be zero-mean Gaussian noise, and the covariance matrix is ​​Q k ;

[0067] Pose prediction:

[0068]

[0069] in: is the predicted posture at time k, is the pose estimate at time k-1.

[0070] Preferably, in step 7, specifically:

[0071] (7.1) Collision safety of flying objects themselves:

[0072] p rel =P0-P min

[0073] v rel =v0-v max

[0074] where p rel is the spatial distance difference between the flying object and its neighboring flying objects in the airspace; P0 is the current position of the flying object; P min is the position of the object closest to the current object; v rel is the spatial velocity difference between the flying object and its neighboring flying objects in the airspace; v0 is the speed of the current flying object; v max is the speed of the object with the largest speed among the neighboring objects;

[0075] (7.2) Collision conditions:

[0076] Time conditions: relative velocity direction points to each other, and collision time t collision >0;

[0077]

[0078] Where: p rel ·v rel is the dot product of relative position and relative velocity; ||v rel || is the modulus of the relative velocity;

[0079] Distance condition: distance d between flying objects min Less than the safety distance d safe :

[0080] d min =||p rel +v rel ·t collision ||

[0081] When d min <d safe , the flying objects may collide.

[0082] The beneficial effects of the present invention are as follows:

[0083] This invention can flexibly set the airspace monitoring range, quickly detect flying objects in low-altitude airspace without blind spots (unaffected by the flying object's appearance, power characteristics, electromagnetic characteristics, and weather conditions), and dynamically set the safety warning accuracy based on the needs of the airspace application scenario, improving the efficiency and accuracy of safety warnings. For low-altitude applications and airspace safety management, it can quickly detect flying objects and conduct safety assessments, while also determining their safety impact on the airspace environment and efficiently and synchronously reporting this to other flying objects in the same airspace, thus achieving high application value in the field of full-airspace safe flight and regulatory technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0084] Figure 1 Flowchart of a method for rapid detection of low-altitude flying objects and flight safety warning in an embodiment. DETAILED DESCRIPTION

[0085] In order to further understand the content of the present invention, the present invention is described in detail with reference to the accompanying drawings and embodiments. It should be understood that the embodiments are merely for explaining the present invention and are not intended to limit the present invention.

[0086] Example

[0087] like Figure 1 As shown, this embodiment provides a method for rapid detection of low-altitude flying objects and flight safety warning, which includes the following steps:

[0088] Step 1: Phased array radar scanning;

[0089] In step 1, a micro phased array radar is used to scan the airspace. The phased array module controls the phase of the electromagnetic wave to scan the airspace over a large area through the array antenna, and multiple radars are networked to reduce the problem of scanning blind spots.

[0090] Step 2: Establish an airspace grid space-time coordinate system. Use phased array radar, radar network or designated points (such as key buildings) as the benchmark to establish an airspace grid coordinate system. The time benchmark is based on Beidou satellite timing.

[0091] Step 2 specifically includes:

[0092] (2.1) Spatial grid space-time coordinate system;

[0093] The spatial grid space-time coordinate system is a dynamic matrix with multi-dimensional dynamic granularity.

[0094]

[0095] Where: C is the spatial grid space-time coordinate, which is managed by grid precision level and time series slice; C nt is the spatial grid coordinate of the n-level grid at time phase t;

[0096] (2.2) Spatial grid dimension composition;

[0097] The airspace grid is a spatial unit. The entire regulatory airspace is dynamically divided into a series of closely connected virtual cubes without gaps. The detection, positioning and safety warning of flying objects are all carried out with the airspace grid as the smallest unit. Each airspace grid G t Contains various information:

[0098] G t =(x,y,z,l,w,t)

[0099] Where: x, y, z are the spatial positions of the grid in the entire grid matrix, defined using a right-handed coordinate system; l is the grid level at which the grid is located, with l>0; t is the state of the grid at time phase t in the space-time sequence; and w is the airspace safety factor of the grid at time phase t, which changes with the changes in the overall airspace safety environment.

[0100] Step 3: Scan the airspace. Use the scanning strategy to drive the phased array radar (radar network) to scan the airspace and detect active or passive flying objects in the airspace. This is not limited to whether the flying objects have power or heat sources, and is not affected by weather.

[0101] In step 3, the phased array radar achieves continuous scanning detection by controlling the periodic change of the phase of the radar wave;

[0102]

[0103] in, The amount of radar wave phase change; d is the spacing between antenna units; λ is the radar wavelength; θ is the scanning angle of the beam;

[0104] (3.1) Detection target distance;

[0105] The target distance R is calculated by measuring the time delay τ between the transmitted signal and the received signal:

[0106]

[0107] Where c is the speed of light;

[0108] (3.2) Detect target speed;

[0109] By measuring the Doppler frequency shift f of the received signal d To calculate the target velocity v:

[0110]

[0111] Where λ is the radar wavelength;

[0112] (3.3) Detection target angle;

[0113] The target angle θ is calculated by measuring the phase difference Δφ of the received signal between different antenna elements:

[0114]

[0115] Step 4: Airspace grid positioning: Based on the detection and warning airspace grid coordinate system, the time dimension is introduced to achieve the airspace grid spatiotemporal positioning of the flying object and form the spatiotemporal trajectory of the flying object.

[0116] In step 4, the radar measures the distance, speed, and angle of the detected object in step 3, maps them to the spatial grid coordinate system, and stores them as spatial grid space-time coordinates, providing source data for subsequent safety assessment and early warning;

[0117] (4.1) Polar coordinates are converted to rectangular coordinates;

[0118] x=r cos(φ)cos(θ)

[0119] y=r cos(φ)sin(θ)

[0120] z=r sin(φ)

[0121] Where r is the distance from the object to the origin, θ is the azimuth angle, and φ is the pitch angle;

[0122] (4.2) The spatial rectangular coordinates are mapped to the spatial grid coordinates;

[0123] Mapping the (x, y, z) coordinates in the rectangular coordinate system to the spatial grid requires quantization according to the level and range of the grid;

[0124] Grid Range:

[0125] [x min ,x max ]×(y min ,y max ]×[z min ,z max ]

[0126] The grid resolution is Δx×Δy×Δz;

[0127] Mesh Mapping:

[0128] Map (x,y,z) coordinates to grid indices (i,j,k):

[0129]

[0130] Step 5: Correction of trajectory prediction model: Establish an attitude prediction model based on the real-time attitude of the detected flying object, and correct the subsequent attitude prediction model of the flying object based on the previous continuous attitude change rate.

[0131] In step 5, specifically:

[0132] The attitude of the object is estimated by combining the dynamic model of the flying object and radar measurement data based on Kalman filtering;

[0133] Posture model M:

[0134] M=(p x ,p y ,p z ,v x ,v y ,v z ,θ x ,θ y ,θ z )

[0135] where p x , p y , p z is the position of the flying object, v x , v y , v z is the speed of the flying object, θ x ,θ y ,θ z is the acceleration of the flying object;

[0136] Detection model z k :

[0137] z k =H k x k +v k

[0138] Among them: H k is the observation matrix, which describes how the state is mapped to the observation value; x k is the observation quantity, a group of variables describing the state of the flying object; v k is the observation noise, assuming it is zero-mean Gaussian noise, and the covariance matrix is ​​R k ;

[0139] Posture changes:

[0140] x k =F k x k-1 +B k u k +w k

[0141] Among them: F k is the attitude transfer matrix, which describes how the attitude is transferred from time k-1 to time k; B k is the control input matrix, describing the external factors u k Effect on posture; wk is the process noise, assumed to be zero-mean Gaussian noise, and the covariance matrix is ​​Q k .

[0142] Pose prediction:

[0143]

[0144] in: is the predicted posture at time k, is the pose estimate at time k-1.

[0145] Step 6: Flight trajectory prediction: introduce time series variables to perform attitude integration on the flying object to predict the trajectory of the flying object.

[0146] Step 7: Establish a flight safety model. The flight safety model includes two aspects: one is the flight safety model of the aircraft itself, which is built based on the aircraft's own posture and flight characteristics; the other is the airspace safety model, which is built based on the flight characteristics and trajectories of all aircraft in the airspace grid, and focuses more on the mutual influence between aircraft in the airspace.

[0147] In step 7, specifically:

[0148] (7.1) Collision safety of flying objects themselves:

[0149] p rel =P0-P min

[0150] v rel =v0-v max

[0151] where p rel is the spatial distance difference between the flying object and its neighboring flying objects in the airspace; P0 is the current position of the flying object; P min is the position of the object closest to the current object; v rel is the spatial velocity difference between the flying object and its neighboring flying objects in the airspace; v0 is the speed of the current flying object; v max is the speed of the object with the largest speed among the neighboring objects;

[0152] (7.2) Collision conditions:

[0153] Time conditions: relative velocity direction points to each other, and collision time t collision >0;

[0154]

[0155] Where: p rel ·v rel is the dot product of relative position and relative velocity; ||v rel|| is the modulus of the relative velocity;

[0156] Distance condition: distance d between flying objects min Less than the safety distance d safe :

[0157] d min =||p rel +v rel ·t collision ||

[0158] When d min <d safe , the flying objects may collide.

[0159] Step 8: Flight impact assessment. Flight impact assessment includes two aspects: one is the safety impact assessment of the airspace environment on the aircraft, which is carried out through the airspace grid safety factor; the other is the safety impact assessment of the aircraft on other aircraft in the airspace, which is carried out through the airspace grid safety factor.

[0160] After calculating the safety factors of the aircraft and airspace based on step 7, the safety situation of the aircraft itself in the airspace environment and the safety impact of the aircraft on the airspace grid unit can be obtained, and the safety factor in the airspace grid can be updated synchronously.

[0161] Step 9: Flight safety warning: classify flight safety risks and trigger different warning mechanisms for different risk levels to issue warning information to flying objects and airspace regulators.

[0162] This embodiment enables flexible setting of airspace monitoring ranges, enabling rapid detection of low-altitude flying objects without blind spots (unaffected by the object's appearance, power, and electromagnetic characteristics, or by weather). It also dynamically adjusts safety warning accuracy based on airspace application scenario requirements, improving both the efficiency and accuracy of safety warnings. Targeting low-altitude applications and airspace safety management, this system can rapidly detect flying objects and conduct safety assessments, simultaneously assessing their safety impact on the airspace environment and efficiently and synchronously reporting this information to other flying objects in the same airspace, ensuring full-airspace safety flight and regulatory technology with extremely high application value.

[0163] The above is a schematic description of the present invention and its embodiments, which is not restrictive. The drawings show only one embodiment of the present invention, and the actual structure is not limited thereto. Therefore, if a person skilled in the art is inspired by this and, without departing from the purpose of the present invention, designs a structure and embodiment similar to this technical solution without inventiveness, they shall fall within the scope of protection of the present invention.

Claims

1. A method for rapid detection of low-altitude flying objects and flight safety early warning, characterized by: The following steps are involved: Step 1: Phased array radar scanning; Step 2: Establish a spatial grid space-time coordinate system. Use phased array radar, radar network, or designated point as the reference to establish the spatial grid coordinate system. The time reference is based on Beidou satellite timing. Step 3: Scan the airspace. The scanning strategy drives the phased array radar to scan the airspace and detect active or passive flying objects in the airspace, regardless of whether the flying objects have power or heat sources, and are not affected by weather. Step 4: Airspace grid positioning: Based on the detection and warning airspace grid coordinate system, the time series dimension is introduced to achieve the airspace grid spatiotemporal positioning of the aircraft and form the spatiotemporal trajectory of the aircraft. Step 5: Correction of trajectory prediction model: Establish an attitude prediction model based on the real-time attitude of the detected flying object, and correct the subsequent attitude prediction model of the flying object based on the previous continuous attitude change rate; In step 5, specifically: The attitude of the object is estimated by combining the dynamic model of the flying object and radar measurement data based on Kalman filtering; Posture model M: M=(p x ,p y ,p z ,v x ,v y ,v z ,i x ,i y ,i z ) where p x , p y , p z is the position of the flying object, v x , v y , v z is the speed of the flying object, θ x ,θ y ,θ z is the acceleration of the flying object; Detection model z k : z k =H k x k +v k Among them: H k is the observation matrix, which describes how the state is mapped to the observation value; x k is the observation quantity, a group of variables describing the state of the flying object; v k is the observation noise; Posture changes: x k =F k x k-1 +B k u k +w k Among them: F k is the attitude transfer matrix, which describes how the attitude is transferred from time k-1 to time k; B k is the control input matrix, describing the external factors u k Effect on posture; w k is the process noise; Pose prediction: in: is the predicted posture at time k, is the pose estimate at time k-1; Step 6: Flight trajectory prediction: introduce time series variables to perform attitude integration on the aircraft to predict the trajectory of the aircraft. Step 7: Establish a flight safety model. The flight safety model consists of two parts: the first is the flight safety model of the aircraft itself, which is built based on the aircraft's own posture and flight characteristics; the second is the airspace safety model, which is built based on the flight characteristics and trajectory of all aircraft in the airspace grid, focusing more on the mutual influence between aircraft in the airspace. In step 7, specifically: (7.1) Collision safety of flying objects themselves: p rel =P0-P min v rel =v0-v max where p rel is the spatial distance difference between the flying object and its neighboring flying objects in the airspace; P0 is the current position of the flying object; P min is the position of the object closest to the current object; v rel is the spatial velocity difference between the flying object and its neighboring flying objects in the airspace; v0 is the speed of the current flying object; v max is the speed of the object with the largest speed among the neighboring objects; (7.2) Collision conditions: Time conditions: relative velocity direction points to each other, and collision time t collision >0; Where: p rel ·v rel is the dot product of relative position and relative velocity; ||v rel || is the modulus of the relative velocity; Distance condition: distance d between flying objects min Less than the safety distance d safe : d min =||p rel +v rel ·t collision || When d min <d safe , then the flying objects may collide; Step 8: Flight impact assessment. This includes two aspects: first, the safety impact of the airspace environment on the aircraft, which is assessed through the airspace grid safety factor; and second, the safety impact of the aircraft on other aircraft in the airspace, which is assessed through the airspace grid safety factor. Step 9: Flight safety warning: classify flight safety risks and trigger different warning mechanisms for different risk levels to issue warning information to flying objects and airspace regulators.

2. The method for rapid detection of low-altitude flying objects and flight safety early warning according to claim 1, characterized in that: In step 1, a micro phased array radar is used to scan the airspace. The phased array module controls the phase of the electromagnetic wave to scan the airspace over a large area through the array antenna, and multiple radars are networked to reduce the problem of scanning blind spots.

3. The method for rapid detection of low-altitude flying objects and flight safety early warning according to claim 2, characterized in that: Step 2 specifically includes: (2.1) Spatial grid space-time coordinate system; The spatial grid space-time coordinate system is a dynamic matrix with multi-dimensional dynamic granularity. Where: C is the spatial grid space-time coordinate, which is managed by grid precision level and time series slice; C nt is the spatial grid coordinate of the n-level grid at time phase t; (2.2) Spatial grid dimension composition; The airspace grid is a spatial unit. The entire regulatory airspace is dynamically divided into a series of closely connected virtual cubes without gaps. The detection, positioning and safety warning of flying objects are all carried out with the airspace grid as the smallest unit. Each airspace grid G t Contains various information: G t =(x,y,z,l,w,t) Where: x, y, z are the spatial positions of the grid in the entire grid matrix, defined using a right-handed coordinate system; l is the grid level at which the grid is located, with l>0; t is the state of the grid at time phase t in the space-time sequence; and w is the airspace safety factor of the grid at time phase t, which changes with the changes in the overall airspace safety environment.

4. The method for rapid detection of low-altitude flying objects and flight safety early warning according to claim 3, characterized in that: In step 3, the phased array radar achieves continuous scanning detection by controlling the periodic change of the phase of the radar wave; in, The amount of radar wave phase change; d is the spacing between antenna units; λ is the radar wavelength; θ is the scanning angle of the beam; (3.1) Detection target distance; The target distance R is calculated by measuring the time delay τ between the transmitted signal and the received signal: Where c is the speed of light; (3.2) Detect target speed; By measuring the Doppler frequency shift f of the received signal d To calculate the target velocity v: Where λ is the radar wavelength; (3.3) Detection target angle; The target angle θ is calculated by measuring the phase difference Δφ of the received signal between different antenna elements:

5. The method for rapid detection of low-altitude flying objects and flight safety early warning according to claim 4, characterized in that: In step 4, the radar measures the distance, speed, and angle of the detected object in step 3, maps them to the spatial grid coordinate system, and stores them as spatial grid space-time coordinates, providing source data for subsequent safety assessment and early warning; (4.1) Polar coordinates are converted to rectangular coordinates; x=r cos(φ)cos(θ) y=r cos(φ)sin(θ) z=r sin(φ) Where r is the distance from the object to the origin, θ is the azimuth angle, and φ is the pitch angle; (4.2) The spatial rectangular coordinates are mapped to the spatial grid coordinates; Mapping the (x, y, z) coordinates in the rectangular coordinate system to the spatial grid requires quantization according to the level and range of the grid; Grid Range: [x min ,x max ]×[y min ,y max ]×[z min ,z max ] The grid resolution is Δx×Δy×Δz; Mesh Mapping: Map (x,y,z) coordinates to grid indices (i,j,k):

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