Low-altitude flyer rapid detection and flight safety early warning method

Abstract

The invention relates to the technical field of low-altitude flyers, and provides a low-altitude flyer rapid detection and flight safety early warning method, which comprises the following steps: step 1, phased array radar scanning; step 2, establishing an airspace grid space-time coordinate system; step 3, scanning an airspace; step 4, spatial domain grid positioning; 5, correcting the trace prediction model; step 6, flight trace prediction; 7, establishing a flight safety model; step 8, flight influence evaluation; and 9, carrying out flight safety early warning. According to the invention, low-altitude flyer rapid detection and flight safety early warning can be well carried out.

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 warning. Background Art

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

[0003] Currently, the commonly used low-altitude flying object monitoring mainly includes radar detection technology, optoelectronic detection technology and radio monitoring technology. Each of the three technologies has its own advantages and disadvantages. The traditional radar detection technology can detect and track low-altitude flying objects relatively stably, but there are detection blind spots; the optoelectronic detection technology integrates optical imaging technology and has excellent effects under good lighting conditions, but has poor effects in bad weather environments; the radio monitoring technology monitors by scanning the radio spectrum of the monitored object, and is completely ineffective for objects without electromagnetic signals (such as floating objects).

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

[0005] Miniaturization and low detectability: Many low-altitude flying objects (especially consumer drones) are small in size, have a small radar cross-section, and have no obvious infrared characteristics. Flying objects using stealth design and composite materials are more difficult to be detected by conventional detection means, posing great challenges to detection technology.

[0006] Low speed and strong maneuverability: The speed range of low-altitude flying objects is wide, from almost hovering drones to high-speed flying light aircraft, and they can quickly change flight postures and headings, which requires the detection system to have the ability of rapid target update and high-precision tracking. Existing technologies often have a lag when dealing with complex maneuvering targets. Summary of the Invention

[0007] The content of the present invention is to provide 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] According to a method for rapid detection of low-altitude flying objects and flight safety warning of the present invention, it includes the following steps:

[0009] Step 1, phased array radar scanning;

[0010] Step 2, establish an airspace grid spatio-temporal coordinate system, establish an airspace grid coordinate system with a phased array radar, a radar network or a specified point as a reference, and use the Beidou satellite time service as the time reference;

[0011] Step 3: Scan the airspace. Drive the phased array radar to perform airspace scanning through a scanning strategy to detect active or passive flying objects in the airspace, regardless of whether the flying object has power or heat source, and is not affected by weather;

[0012] Step 4: Airspace grid positioning. Introduce a time series dimension based on the detection and early warning airspace grid coordinate system to achieve the spatio-temporal positioning of flying objects in the airspace grid and form the spatio-temporal trajectory of flying objects;

[0013] Step 5: Trace prediction model correction. According to the real-time attitude of the detected flying object, establish an attitude prediction model, and correct the subsequent attitude prediction model of the flying object by the previous continuous attitude change rate;

[0014] Step 6: Flight trace prediction. Introduce a time series variable to perform attitude integration on the flying object to achieve the prediction of the flight trace of the flying object;

[0015] Step 7: Establish a flight safety model. The flight safety model includes two aspects: one is the flight safety model of the flying object itself, which is constructed based on the attitude and flight characteristics of the flying object itself; the other is the airspace safety model, which is constructed based on the flight characteristics and traces of all flying objects in the airspace grid, and pays more attention to the mutual influence between flying objects in the airspace;

[0016] Step 8: Flight impact assessment. The flight impact assessment includes two aspects: one is the assessment of the safety impact of the airspace environment on the flying object, which is carried out through the airspace grid safety factor; the other is the assessment of the safety impact of the flying object on other flying objects in the airspace, which is carried out through the airspace grid safety factor;

[0017] Step 9: Flight safety early warning. Classify the flight safety risks, and trigger different early warning mechanisms for different risk levels to send early warning information to the flying object and airspace supervision personnel.

[0018] Preferably, in step 1, a micro phased array radar is used for airspace scanning. The phase control module controls the phase of the electromagnetic wave to perform large-range airspace scanning through the planar array antenna and multi-radar networking to reduce the problem of scanning blind areas.

[0019] Preferably, in step 2, it specifically includes:

[0020] (2.1) Airspace grid spatio-temporal coordinate system;

[0021] The airspace grid spatio-temporal coordinate system is a multi-dimensional dynamic granularity dynamic matrix,

[0022]

[0023] where: C is the airspace grid spatio-temporal coordinate, which is managed by the grid accuracy level and time series slice; C nt is the airspace grid coordinate of the nth-level grid at the tth phase;

[0024] (2.2) Airspace grid dimension composition;

[0025] The airspace grid is a spatial unit. The entire supervised airspace is dynamically divided into a series of closely connected virtual cubes without gaps. The detection and positioning of flying objects and safety warnings are all carried out with the airspace grid as the smallest unit. Each airspace grid G t contains multiple pieces of 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 where the grid is located, l>0; t is the state of the grid at the t-th phase in the space-time sequence; w is the airspace safety factor of the grid at the t-th phase, which changes with the change of the entire 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] where, is the phase change amount of the radar wave; d is the spacing between antenna elements; 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) Detection target speed;

[0036] The target speed v is calculated by measuring the Doppler frequency shift f of the received signal d :

[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 between the received signals of different antenna elements:

[0041]

[0042] Preferably, in step 4, the distance, speed, and angle of the detection object measured by the radar in step 3 are normalized into the airspace grid coordinate system and stored as the airspace grid spatio-temporal coordinates to provide source data for subsequent safety assessment and early warning.

[0043] (4.1) Convert polar coordinates to spatial rectangular coordinates.

[0044] x = rcos(φ)cos(θ)

[0045] y = r cos(φ)sin(θ)

[0046] z = rsin(φ)

[0047] where r is the distance from the object to the origin, θ is the azimuth angle, and φ is the elevation angle.

[0048] (4.2) Normalize the spatial rectangular coordinates into the airspace grid coordinates.

[0049] To normalize the (x, y, z) coordinates in the rectangular coordinate system into the airspace grid, quantization needs to be performed 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] Grid normalization:

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

[0055]

[0056] Preferably, in step 5, specifically:

[0057] Adopt a method based on Kalman filtering combined with the dynamic model of the flying object and radar measurement data to estimate the attitude of the object.

[0058] Attitude model M:

[0059] M = (p x , p y , p z , v x , v x , v y , v​z , θ x , 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 velocity 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] where: H k is the observation matrix, describing how the state is mapped to the observations; x k is the observable quantity, a set of variables describing the state of the flying object; v k is the observation noise, assumed to be zero-mean Gaussian noise with covariance matrix R k ;

[0064] Attitude change:

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

[0066] where: F k is the attitude transition matrix, describing how the attitude transfers from time k - 1 to time k; B k is the control input matrix, describing the influence of the external factor u k on the attitude; w k is the process noise, assumed to be zero-mean Gaussian noise with covariance matrix Q k ;

[0067] Attitude prediction:

[0068]

[0069] where: is the predicted attitude at time k, is the attitude estimate at time k - 1.

[0070] Preferably, in step 7, specifically:

[0071] (7.1) Collision safety of the flying object itself:

[0072] p rel = P 0 - P min

[0073] v rel = v 0 - v max

[0074] where p rel is the spatial distance difference between the flying object and its neighboring flying objects in the airspace; P 0 is the position of the current flying object; P min is the position of the flying object closest to the current flying object; v rel is the spatial velocity difference between the flying object and its neighboring flying objects in the airspace; v 0 is the velocity of the current flying object; v max is the velocity of the flying object with the maximum velocity among the neighboring flying objects;

[0075] (7.2) Collision conditions:

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

[0077]

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

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

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

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

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

[0083] The present invention can flexibly set the airspace monitoring range, quickly detect flying objects in the low-altitude airspace without blind spots (not affected by the appearance characteristics, power characteristics, and electromagnetic characteristics of flying objects, and not affected by weather), and can dynamically set the safety warning accuracy according to the requirements of airspace application scenarios, improving the safety warning efficiency and accuracy. In the field of low-altitude applications and airspace safety management, it can quickly detect flying objects and conduct safety assessments, and at the same time determine their safety impacts on the airspace environment, and efficiently synchronize them to other flying objects in the same airspace, which has extremely high application value in the field of all-airspace safe flight and supervision technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0084] Figure 1 It is a flowchart of a method for quickly detecting low-altitude flying objects and flight safety warning in an embodiment. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0085] To further understand the content of the present invention, the present invention will be described in detail with reference to the drawings and embodiments. It should be understood that the embodiments are only for explaining the present invention and not for limiting it.

[0086] Embodiment

[0087] As Figure 1 shown, the present embodiment provides a method for quickly detecting 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 for airspace scanning, and the phase control module controls the phase of electromagnetic waves to perform large-range airspace scanning through the planar array antenna and multi-radar networking to reduce the problem of scanning blind spots.

[0090] Step 2, establish an airspace grid spatio-temporal coordinate system, and establish an airspace grid coordinate system based on the phased array radar, radar networking or a specified point (such as a key building), and the time reference is based on the Beidou satellite time service.

[0091] In Step 2, it specifically includes:

[0092] (2.1) Airspace grid spatio-temporal coordinate system;

[0093] The airspace grid spatio-temporal coordinate system is a dynamic matrix with multi-dimensional dynamic granularity,

[0094]

[0095] where: C is the airspace grid spatio-temporal coordinate, which is managed according to the grid accuracy level and time series slice; C nt is the airspace grid coordinate of the nth-level grid at the tth phase;

[0096] (2.2) Composition of airspace grid dimensions;

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

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

[0099] where: x, y, and 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 where the grid is located, l>0; t is the state of the grid at the t-th phase in the space-time sequence; w is the airspace safety factor of the grid at the t-th phase, which changes with the change of the entire airspace safety environment.

[0100] Step 3: Scan the airspace. Drive the phased array radar (radar network) to scan the airspace through a scanning strategy to detect active or passive flying objects in the airspace, regardless of whether the flying object has power or heat source, and is not affected by weather.

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

[0102]

[0103] where is the change amount of the radar wave phase; d is the spacing between antenna elements; λ is the radar wavelength; θ is the scanning angle of the beam;

[0104] (3.1) Detect the target distance;

[0105] Calculate the target distance R 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 the target speed;

[0109] Calculate the target speed v by measuring the Doppler frequency shift f of the received signal d :

[0110]

[0111] where λ is the radar wavelength;

[0112] (3.3) Detect the target angle;

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

[0114]

[0115] Step 4, airspace grid positioning: Based on the airspace grid coordinate system for detection and early warning, introduce the time series dimension to achieve the spatio-temporal positioning of the airspace grid of the flying object, and form the spatio-temporal trajectory of the flying object.

[0116] In Step 4, in Step 3, the radar measures the distance, speed, and angle of the detected object, normalizes them into the airspace grid coordinate system, stores them as the spatio-temporal coordinates of the airspace grid, and provides source data for subsequent safety assessment and early warning;

[0117] (4.1) Convert polar coordinates to spatial rectangular coordinates;

[0118] x = rcos(φ)cos(θ)

[0119] y = r cos(φ)sin(θ)

[0120] z = rsin(φ)

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

[0122] (4.2) Normalize the spatial rectangular coordinates to the airspace grid coordinates;

[0123] To normalize the (x, y, z) coordinates in the rectangular coordinate system into the airspace grid, quantization needs to be performed 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] Grid normalization:

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

[0129]

[0130] Step 5, modify the trace prediction model: According to the real-time attitude of the detected flying object, establish an attitude prediction model, 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] Adopt a Kalman filter combined with the dynamic model of the flying object and radar measurement data to estimate the attitude of the object;

[0133] Attitude model M:

[0134] M = (p x , p y , p z , v x , 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 velocity 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] Where: H k is the observation matrix, describing how the state is mapped to the observed value; x k is the observed quantity, describing the variable group of the flying object state;; v k is the observation noise, assumed to be zero-mean Gaussian noise with covariance matrix R k ;

[0139] Attitude change:

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

[0141] Where: F k is the attitude transition matrix, describing how the attitude transfers from time k - 1 to time k; B k is the control input matrix, describing the external factor uk Effect on attitude; w k is the process noise, assumed to be zero-mean Gaussian noise with covariance matrix Q k .

[0142] Attitude prediction:

[0143]

[0144] where: is the predicted attitude at time k, is the attitude estimate at time k-1.

[0145] Step 6, Flight trajectory prediction, introducing a time series variable to perform attitude integration on the flying object to achieve the prediction of the flying object's trajectory.

[0146] Step 7, Establish a flight safety model. The flight safety model includes two aspects: one is the flight safety model of the flying object itself, constructed based on the attitude and flight characteristics of the flying object itself; the other is the airspace safety model, constructed based on the flight characteristics and trajectories of all flying objects in the airspace grid, and pays more attention to the mutual influence between flying objects in the airspace.

[0147] In Step 7, specifically:

[0148] (7.1) Collision safety of the flying object itself:

[0149] p rel = P 0 - P min

[0150] v rel = v 0 - v max

[0151] where p rel is the spatial distance difference between the flying object and its neighboring flying objects in the airspace; P 0 is the position of the current flying object; P min is the position of the flying object closest to the current flying object; v rel is the spatial velocity difference between the flying object and its neighboring flying objects in the airspace; v 0 is the velocity of the current flying object; v max is the velocity of the flying object with the maximum velocity among the neighboring flying objects;

[0152] (7.2) Collision conditions:

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

[0154]

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

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

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

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

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

[0160] After calculating the safety factors of flying objects and the airspace based on Step 7, the safety situation of the flying objects themselves in the airspace environment, and the safety impact of the flying objects on the airspace grid cells can be obtained, and the safety coefficients in the airspace grid are synchronously updated.

[0161] Step 9, Flight safety warning. Classify the flight safety risks, and trigger different warning mechanisms for different risk levels to send warning messages to flying objects and airspace supervisors.

[0162] This embodiment can flexibly set the airspace monitoring range, quickly detect flying objects in the low-altitude airspace without blind spots (not affected by the appearance characteristics, power characteristics and electromagnetic characteristics of flying objects, not affected by weather), and can dynamically set the safety warning accuracy according to the requirements of the airspace application scenario, improving the safety warning efficiency and accuracy. For the fields of low-altitude applications and airspace safety management, it can quickly detect flying objects and conduct safety assessments, and at the same time make their safety impacts on the airspace environment, and efficiently synchronize them to other flying objects in the same airspace, which has extremely high application value in the field of full-airspace safe flight and supervision technology.

[0163] The above has schematically described the present invention and its implementation manners. This description is not restrictive. What is shown in the drawings is only one of the implementation manners of the present invention, and the actual structure is not limited thereto. Therefore, if those of ordinary skill in the art are inspired by it and design similar structural manners and embodiments without creative efforts without departing from the purpose of the present invention, they shall fall within the protection scope of the present invention.

Claims

1. A method for rapid detection of low-altitude flying objects and flight safety early warning, characterized in that: The following steps are involved: Step 1: Phased array radar scanning; Step 2: Establish an airspace grid space-time coordinate system. Establish an airspace grid coordinate system based on phased-control radar, radar networking or designated point. The time reference is based on Beidou satellite timing. Step 3: Scan the airspace. The phased array radar is driven by the scanning strategy 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 dimension is introduced to achieve the airspace grid spatiotemporal positioning of the flying object and form the spatiotemporal trajectory of the flying object; Step 5: Correction of trajectory prediction model: Establishing attitude prediction model according to the real-time attitude of the detected flying object, and correcting the subsequent attitude prediction model of the flying object according to the previous continuous attitude change rate; 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; 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 pays more attention to the mutual influence between aircraft in the airspace; Step 8: Flight impact assessment. Flight impact assessment includes two aspects: first, the safety impact assessment of the airspace environment on the flying object, which is carried out through the airspace grid safety factor; second, the safety impact assessment of the flying object on other flying objects in the airspace, which is carried out 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. A 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 perform airspace scanning. The phase of the electromagnetic wave is controlled by the phased array module to perform large-scale airspace scanning through the array antenna and multiple radars are networked to reduce the problem of scanning blind spots.

3. A 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 a variety of 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 in a right-handed coordinate system; l is the grid level at which the grid is located, l>0; t is the state of the grid at time phase t in the space-time sequence; w is the airspace safety factor of the grid at time phase t, which changes with the changes in the entire airspace safety environment.

4. A 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 realizes 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. A 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 distance, speed and angle of the detected object measured by the radar in step 3 are normalized to the spatial grid coordinate system and stored as spatial grid time-space coordinates to provide 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) Among them, 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 normalized to the spatial grid coordinates; The (x, y, z) coordinates in the rectangular coordinate system are normalized to the spatial grid, which needs to be quantified 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; Grid naturalization: Map (x,y,z) coordinates to grid indices (i,j,k):

6. A method for rapid detection of low-altitude flying objects and flight safety early warning according to claim 5, characterized in that: 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 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 Where: H k is the observation matrix, describing how the state is mapped to the observation value; x k is the observed quantity, a group of variables describing the state of the flying object; v k is the observation noise, assumed to be zero-mean Gaussian noise, and the covariance matrix is ​​R k ; 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; k is the process noise, assumed to be zero-mean Gaussian noise, and the covariance matrix is ​​Q k ; Posture prediction: in: is the predicted posture at time k, is the pose estimate at time k-1.

7. A method for rapid detection of low-altitude flying objects and flight safety early warning according to claim 6, characterized in that: 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 velocity 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 min <d safe , then the flying objects may collide.

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