Joint track-before-detection method for moving targets in space-based distributed video SAR

Abstract

The present invention discloses a method for joint detection and tracking of moving targets using space-based distributed video SAR, which mainly solves the problem of limited high-speed maneuvering target detection and tracking capabilities in single-platform space-based video SAR systems. The implementation scheme is as follows: constructing a space-based distributed video SAR collaborative detection model; sequentially connecting the short synthetic apertures formed by multiple space-based video SARs in the model to construct two equivalent long synthetic apertures, and performing imaging and focusing on them to obtain images, and then performing cancellation processing to obtain a difference video SAR image sequence after stationary clutter suppression; performing pre-detection, clustering, and matching on the difference images of the sequence to obtain a shadow pre-detection point set; performing velocity matching on the pre-detection points to achieve state initialization; performing shadow and energy joint value function accumulation based on the initial shadow state; and determining the target based on the accumulated value. The present invention greatly shortens the imaging time and improves the detection capability of moving targets, and can be used for ground moving target detection and tracking using space-based distributed video synthetic aperture radar.

Description

Technical Field

[0001] The present invention belongs to the field of radar technology, and in particular relates to a moving target tracking method before detection, which can be used for shadow detection and tracking of ground moving targets by space-based distributed video synthetic aperture radar. Background Art

[0002] Video synthetic aperture radar (SAR) is a typical high-frame-rate imaging system capable of dynamically monitoring hotspots and continuously tracking moving targets. Therefore, video SAR has great potential for application in environmental situational awareness and ground moving target indication (GMTI). In recent years, space-based video SAR has garnered widespread attention due to its robust survivability, wide detection range, and unrestricted geographic coverage.

[0003] However, space-based video SAR still faces several issues and challenges that have yet to be effectively addressed. First, space-based video SAR faces a conflict between high-frame-rate imaging and long-range detection. While maintaining azimuth resolution, increasing the radar's operating carrier frequency is an effective way to improve the imaging frame rate. However, atmospheric attenuation of electromagnetic waves and the current power limitations of high-frequency devices severely limit the detection range of high-frequency SAR systems. Conventional single-unit space-based video SAR cannot simultaneously meet the application requirements of high-frame-rate imaging and long-range detection. Second, space-based video SAR also faces a conflict between high-resolution imaging and detection of high-speed maneuvering targets. One effective approach to achieving high azimuth resolution in video SAR is to increase the synthetic aperture length to achieve a larger integration angle. However, a long synthetic aperture results in greater range migration and image defocus for high-speed maneuvering targets. Furthermore, in video SAR, a long synthetic aperture can cause the shadow of a high-speed moving target to blur its boundaries, reduce contrast with the background, and even render the shadow invisible. Therefore, increasing the synthetic aperture to improve azimuth resolution is not conducive to detecting and tracking high-speed maneuvering targets.

[0004] Currently, there are few reports on moving target detection and tracking in space-based video SAR. There are mainly two technologies:

[0005] First, in her paper "Research on High-Low Orbit Cooperative Bistatic Video-SAR Imaging and Target Tracking Methods," Cai Xuelian proposed a moving target track generation method based on a high-low orbit cooperative video SAR imaging model. After clutter cancellation, the method determines the target's initial position and velocity based on the first frame of dual-channel detection results. A local weighted dynamic programming track-before-detection algorithm is then used to generate the target track.

[0006] Second, in his paper "A Constant False Alarm Rate Detection Method for Moving Targets in Spaceborne Video SAR," Li Jinwei proposed a moving target detection process for single-channel spaceborne video SAR image sequences. The method's main steps include preprocessing, change detection factor calculation, single-frame detection threshold determination, single-frame detection fusion, and motion trajectory detection. While maintaining a constant false alarm rate, it rationally utilizes the statistical characteristics of SAR images and target motion patterns to achieve robust moving target detection.

[0007] However, both of the above methods study the problem of moving target detection in single-platform space-based video SAR, without considering the two major contradictions in actual space-based video SAR systems: high frame rate imaging and long-range detection, and high-resolution imaging and high-speed maneuvering target detection. This affects the detection and tracking performance of moving targets, especially the further improvement of the detection and tracking capabilities of high-speed maneuvering targets, thus limiting their application. Summary of the Invention

[0008] The purpose of the present invention is to address the deficiencies of the above-mentioned existing technologies and propose a joint detection and tracking method for ground moving targets using space-based distributed video SAR to improve the detection and tracking performance of moving targets, especially the detection and tracking capabilities of high-speed maneuvering targets.

[0009] To achieve the above objectives, the implementation steps of the technical solution of the present invention include the following:

[0010] (1) Constructing a collaborative detection model:

[0011] Set up N video SARs, these space-based video SARs maintain a constant spacing and move in a straight line configuration, and use a spotlight mode to observe the same target area;

[0012] The difference frequency Δf is designed to transmit a series of time-synchronized instantaneous frequency-divided orthogonal linear frequency modulation continuous wave signals with minimal difference frequency. During reception, each space-based video SAR retains only the echo signal corresponding to its own carrier frequency through orthogonal isolation.

[0013] (2) Assume that the space-based distributed video SAR system performs M observations in total. In the kth and k+1th observations, two equivalent long synthetic apertures α that meet the DPCA conditions are constructed by sequentially connecting multiple short synthetic apertures formed by multiple space-based video SARs. k and β k+1 ;

[0014] (3) Using the frequency domain imaging algorithm represented by polar coordinate formatting, the equivalent long synthetic aperture α k and β k+1 Focus to obtain the video SAR images corresponding to the two apertures and Finally, two sets of video SAR image sequences are obtained and The difference video SAR image sequence Π={ΔI1,...,ΔI k ,...,ΔI M-1},in is the difference video SAR image obtained for the kth time;

[0015] (4) Pre-detection and clustering are performed on the difference video SAR images ΔI1 and ΔI2, and the shadow and energy matching of the same moving target is achieved based on the range coordinates, and the shadow pre-detection point sets Γ1 and Γ2 of the images ΔI1 and ΔI2 are obtained respectively:

[0016]

[0017] Where r=1,...,R,q=1,...,Q,R and Q are the total number of pre-detection points on ΔI1 and ΔI2 respectively, are the rth and qth shadow detection points on ΔI1 and ΔI2 respectively, and are the azimuth offsets of the shadow detection point and energy detection point of the same moving target on ΔI1 and ΔI2 respectively;

[0018] (5) Based on the shadow pre-detection point set Γ1 and Γ2, the state is initialized by velocity matching to obtain the shadow initial state set in is the initial state of the shadow of the mth candidate target in the first frame, M t is the total number of candidate targets to be tracked;

[0019] (6) Based on the initial state of the shadow of the mth candidate target in the first frame In the M-1 frame video SAR image sequence Perform shadow and energy joint value function accumulation on:

[0020] (6a) Let the current frame be the hth frame, where h∈[1,M-1);

[0021] (6b) For the shadow state in the hth frame Perform inter-frame state transfer to obtain the shadow state in the h+1th frame

[0022]

[0023] in I2 is the second-order identity matrix, represents the Kronecker product of the matrix, δ x and δ y are the acceleration noises in the x-direction and y-direction respectively, and Δt is the time interval between two adjacent frames;

[0024] (6c) The shadow state of the mth candidate target in the h+1th frame Mapping to energy states

[0025] (6d) Joint Shadow State and energy status Perform value function accumulation to obtain cumulative value

[0026]

[0027] in is the inverse shadow amplitude, is the energy amplitude, are all states that can be transferred to in the hth frame The state set of

[0028] (7) Repeat step (6) to set the value function Accumulate to the M-1 frame, and then compare it with the set detection threshold V α Compare and determine whether the target to be detected exists:

[0029] like Then the mth target to be detected exists, and its trajectory in the M-1 frame is traced back.

[0030] Otherwise, the target to be detected does not exist;

[0031] (8) Repeat step (7) to complete M t Joint pre-detection tracking of multiple targets to be detected.

[0032] Compared with the prior art, the present invention has the following advantages:

[0033] 1) By sequentially connecting and splicing multiple short synthetic apertures formed by multiple space-based video SARs into an equivalent long synthetic aperture, the present invention significantly shortens imaging time while ensuring imaging resolution. This not only enables high imaging frame rates even in low-frequency bands, thus avoiding the conflict between high-frame-rate imaging and long-range detection by space-based video SAR, but also facilitates the detection of highly maneuverable targets, thus avoiding the conflict between high-resolution imaging and high-speed maneuvering target detection by space-based video SAR.

[0034] 2) The present invention performs pre-detection tracking of joint shadows and energy in the detection of ground moving targets, and can use the multi-dimensional characteristics of moving targets to achieve robust detection, thereby improving the detection capability of space-based video SAR for ground moving targets. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 It is an implementation flow chart of the present invention;

[0036] Figure 2 This is the result of coarse imaging of moving target scene using frequency domain algorithm (PFA);

[0037] Figure 3 for Figure 2 A magnified image of the target area. DETAILED DESCRIPTION

[0038] In order to enable those skilled in the art to better understand the solutions of the present invention, the following will be combined with the accompanying 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 embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of the present invention.

[0039] It should be noted that the step numbers in the specification and claims of the present invention are only for a clear description of the embodiments of the present invention to facilitate understanding, and the order of other numbers is not limited.

[0040] Reference Figure 1 The implementation steps of this example include the following:

[0041] Step 1: Build a space-based distributed video SAR collaborative detection model.

[0042] Set up N video SARs, these space-based video SARs maintain a constant spacing and move in a straight line configuration, and use a spotlight mode to observe the same target area;

[0043] The difference frequency Δf is designed to transmit a series of time-synchronized instantaneous frequency-divided orthogonal linear frequency modulation continuous wave signals with minimal difference frequency. During reception, each space-based video SAR retains only the echo signal corresponding to its own carrier frequency through orthogonal isolation.

[0044] The difference frequency Δf is designed as follows:

[0045] To ensure that the echo signals of each space-based video SAR can be coherently processed, the difference frequency Δf should be much smaller than the transmission signal bandwidth B;

[0046] In order to ensure that the echo signals of different video SAR can be orthogonally isolated, the difference frequency Δf should be set to be larger than the detection scene bandwidth B r =2w r γ / c, that is, B r <Δf<B, where w r is the imaging scene width, γ is the frequency modulation slope, and c is the speed of light.

[0047] Step 2: Construct a long synthetic aperture that meets the DPCA conditions.

[0048] 2.1) Assume that a space-based distributed video SAR system performs M observations;

[0049] 2.2) In the kth and k+1th observations, two equivalent long synthetic apertures α that meet the DPCA conditions are constructed by sequentially concatenating multiple short synthetic apertures formed by multiple space-based video SARs. k and β k+1 :

[0050] 2.2.2) During the k-th observation time Δt, the short synthetic aperture L formed by the n-th space-based video SAR is obtained nk , the equivalent long synthetic aperture α is obtained by sequentially connecting multiple short synthetic apertures of the second to Nth space-based video SAR k :

[0051] α k =L 2k ||L 3k ||...||L nk ||...||L Nk

[0052] 2.2.3) After time Δt, the k+1th observation is performed and the short synthetic aperture formed by the nth space-based video SAR is obtained as L n(k+1) By sequentially concatenating multiple short synthetic apertures of the first to the N-1th space-based video SAR, the equivalent long synthetic aperture β is obtained. k+1 :

[0053] β k+1 =L 1(k+1) ||L 2(k+1) ||...||L n(k+1) ||...||L (N-1)(k+1) .

[0054] Step three: perform frequency domain imaging focusing on the long synthetic aperture and cancel out the difference SAR image.

[0055] Frequency domain imaging focusing can be achieved through a frequency domain imaging algorithm, that is, through a range Doppler algorithm, a polar coordinate formatting algorithm, etc. This example adopts but is not limited to a frequency domain imaging algorithm represented by polar coordinate formatting.

[0056] The specific implementation of this step is as follows:

[0057] 3.1) Using frequency domain imaging algorithms represented by polar coordinate formatting, we can respectively calculate the equivalent long synthetic aperture α k and β k+1 Focus to obtain the video SAR images corresponding to the two apertures and The equivalent length of the synthetic aperture αk and β k+1 Meet DPCA conditions;

[0058] 3.2) Video SAR images and Cancellation is performed, that is, according to the situation where the aperture spatial position is the same but there is a time difference Δt, the corresponding video SAR image can be known and The amplitude and phase of the stationary clutter are consistent, while the amplitude and phase of the moving target are different. The difference video SAR image after the stationary clutter is suppressed can be obtained by complex image subtraction.

[0059] 3.3) Repeat step 3.1) for M-1 times to obtain two sets of video SAR image sequences and

[0060] 3.4) Repeat step 3.2) for M-1 times, and perform image cancellation to obtain the difference video SAR image sequence Π={ΔI1,...,ΔI k ,...,ΔI M-1}.

[0061] Step 4: perform pre-detection and clustering on the difference SAR image.

[0062] Pre-detection and clustering are performed on the difference video SAR images ΔI1 and ΔI2, and the shadow and energy of the same moving target are matched based on the range coordinates. The shadow pre-detection point sets Γ1 and Γ2 of the two difference images ΔI1 and ΔI2 are obtained respectively:

[0063] 4.1) Set the detection threshold V T , compare it with the difference video SAR image ΔI1 to determine whether shadow or energy exists:

[0064] If the SAR image value ΔI1(x,y) at the position with the direction x and the range y on ΔI1 is greater than the set detection threshold, then shadow or energy exists.

[0065] Otherwise, the shadow or energy does not exist;

[0066] The mathematical expression of this judgment is as follows:

[0067]

[0068] where x=1,...,N x , y=1,...,N y , N x and N yRespectively represent the number of resolution units in the azimuth and range directions of the SAR image, H1 indicates the presence of shadow or energy, and H0 indicates the absence of shadow or energy;

[0069] 4.2) Clustering the moving target shadow and energy detection results obtained in step 4.1) using a density clustering algorithm, and then averaging and fusing multiple points in the same cluster to obtain an accurate shadow or energy detection point;

[0070] 4.3) Matching the shadow and energy of the same moving target based on the range coordinates, and obtaining the shadow pre-detection point set Γ1 of the difference image ΔI1 and the shadow pre-detection point set Γ2 of the difference image ΔI2:

[0071] 4.3.1) Based on SAR images The neighborhood pixel mean of the upper detection point is used to distinguish the results, and all detection points are divided into two categories: shadow detection points and energy detection points;

[0072] 4.3.2) Let the rth shadow detection point be The jth energy detection point is And let Δr be the distance threshold and compare it with the detection point:

[0073] like Then the rth shadow detection point and the jth energy detection point belong to the same moving target, achieving the matching of the shadow and energy of the same moving target, and the azimuth offset is recorded as

[0074] 4.3.3) Repeat steps 4.3.1) to 4.3.2) to traverse all shadow detection points and finally obtain the shadow pre-detection point set

[0075] 4.3.4) Repeat steps 4.3.1) to 4.3.3) on the difference image ΔI2 to obtain the shadow pre-detection point set

[0076] Step 5: Initialize the state of the candidate target through velocity matching based on the shadow pre-detection point sets Γ1 and Γ2 to obtain the shadow initial state set C.

[0077] 5.1) Assume and are the detection points in the shadow pre-detection point sets Γ1 and Γ2, respectively, and the inter-frame coordinate difference Δx in the azimuth direction and the inter-frame coordinate difference Δy in the distance direction are calculated:

[0078]

[0079] 5.2) Assume that the inter-frame velocity range of the azimuth direction is The speed range in the distance direction is Determine the coordinate difference Δx between the azimuth frames and the coordinate difference Δy between the distance frames:

[0080] If the coordinate difference between frames satisfies and Then the detection point Consider it as a candidate target and set the initial shadow state of the mth candidate target in the first frame Expressed as:

[0081]

[0082] Otherwise, no action is taken;

[0083] 5.3) Repeat steps 5.1) to 5.2), traverse all detection points in Γ1 and match them with all detection points in Γ2 to obtain the shadow initial state set Among them, M t is the total number of candidate targets to be tracked.

[0084] Step 6: Based on the initial state of the shadow of the mth candidate target In the M-1 frame video SAR image sequence The shadow and energy joint value function is accumulated.

[0085] (6.1) Let the current frame be the hth frame, where h∈[1,M-1);

[0086] (6.2) For the shadow state in the hth frame Perform inter-frame state transfer to obtain the shadow state in the h+1th frame

[0087]

[0088] in represents a four-dimensional matrix, the symbol T represents transpose, I2 is the second-order unit matrix, represents the Kronecker product of the matrix, δ x and δ y are the acceleration process noise in the x-direction and y-direction respectively;

[0089] (6.3) The shadow state of the mth candidate target in the h+1th frame Mapping to energy states

[0090] 6.3.1) According to the azimuth offset of the mth candidate target The shadow state after the inter-frame state transfer Mapping to preliminary energy state

[0091]

[0092] in, is the azimuth coordinate of the mth candidate target in the h+1th frame, is the range coordinate of the mth candidate target in the h+1th frame;

[0093] 6.3.2) Compensate for the deviation between the initial estimated energy state and the actual state caused by the change in the speed of the moving target, that is, The azimuth coordinates are randomly expanded to obtain the expanded pixel coordinate set:

[0094]

[0095] in is the azimuthal coordinate after expansion, which is around the original position By taking a uniform distribution U D (x a ,x b ) is sampled D times; is the distance coordinate after expansion;

[0096] 6.3.3) Expand the coordinates and The pixel values ​​of all corresponding states are arranged in descending order, and the state with the highest pixel value is taken. As shadow state The energy state after mapping;

[0097] (6.4) Joint Shadow State and energy status Perform value function accumulation to obtain cumulative value

[0098]

[0099] in is the inverse shadow amplitude, is the energy amplitude, are all states that can be transferred to in the hth frame The state collection.

[0100] Step 7: Make target decision based on the joint accumulation value.

[0101] When the target does not exist, the detection threshold V is set according to the signal-to-noise ratio using the Monte Carlo simulation method. α ,

[0102] Repeat step 6 and accumulate the value function to the M-1th frame to obtain Then compare it with the set detection threshold V αCompare and determine whether the target to be detected exists:

[0103] like Then it is determined that the mth target to be detected exists, and its trajectory in the M-1 frame is traced back.

[0104] Otherwise, it is determined that the target to be detected does not exist.

[0105] Step 8, repeat step 7 to complete M t Joint pre-detection tracking of multiple targets to be detected.

[0106] The effects of the present invention can be further illustrated by the following simulation results:

[0107] 1. Simulation experiment parameters, as shown in Table 1

[0108] Table 1 Space-based cluster SAR simulation parameters

[0109] parameter value carrier frequency 94GHz Track height 550km Platform speed 7579m / s Range 800km Transmit power 500W Transmitting and receiving antenna gain 50dBi Pulse repetition frequency 9KHz Number of sub-platforms 10

[0110] 2. Simulation experiment content

[0111] Under the above simulation parameters, the frequency domain algorithm PFA is used to perform coarse imaging of the moving target scene, that is, to simulate the long aperture imaging of a single platform and the long aperture imaging of cluster SAR. The results are as follows: Figure 2 ,in:

[0112] Figure 2 (a) is the result of single-platform long-aperture imaging,

[0113] Figure 2 (b) is the result of cluster SAR long aperture imaging;

[0114] from Figure 2 (a) and Figure 2 (b) Comparison shows:

[0115] Figure 2 In the single-platform long-aperture imaging process shown in (a), the synthetic aperture length required to achieve a resolution of 1 m is 1212 m, and the accumulation time is 0.1667 s; Figure 2 The cluster SAR multi-platform long-aperture imaging shown in (b) has the same resolution as single-platform long-aperture imaging, but its synthetic aperture time is only one-tenth of that of single-platform long-aperture imaging.

[0116] Comparison results show that the present invention can greatly shorten the imaging time while ensuring imaging resolution by sequentially connecting and splicing multiple short synthetic apertures formed by multiple space-based video SARs into an equivalent long synthetic aperture. This not only enables a higher imaging frame rate to be obtained in the low-frequency band, thus avoiding the contradiction between high-frame-rate imaging of space-based video SAR and long-range detection, but also is more conducive to the detection of highly maneuverable targets, thus avoiding the contradiction between high-resolution imaging of space-based video SAR and detection of high-speed maneuverable targets.

[0117] The target area of ​​the above imaging results is enlarged, such as Figure 3 As shown, where:

[0118] Figure 3 (a) is a magnified image of the target area resulting from single-platform long-aperture imaging.

[0119] Figure 3 (b) is a magnified image of the target area resulting from cluster SAR long-aperture imaging;

[0120] from Figure 3 (a) and Figure 3 (b) Comparison shows:

[0121] Figure 3 (a) The long-aperture imaging of a single platform results in more severe range migration and imaging defocus of high-speed maneuvering targets; Figure 3 In (b), by sequentially stitching together the short synthetic apertures produced by multiple space-based video SARs into an equivalent long synthetic aperture, the target's movement distance can be reduced. Specifically, the range-dependent movement of high-speed targets can be reduced to one-tenth of its original value. This demonstrates that by sequentially stitching together the short synthetic apertures produced by multiple space-based video SARs into an equivalent long synthetic aperture, the space-based video SAR's detection capability for ground moving targets can be enhanced.

Claims

1. A method for joint tracking of moving targets before detection for space-based distributed video SAR, characterized in that: These include: (1) Constructing a collaborative detection model: Set up N video SARs, these space-based video SARs maintain a constant spacing and move in a straight line configuration, and use a spotlight mode to observe the same target area; The difference frequency △f is designed to transmit a series of instantaneous frequency-divided orthogonal linear frequency modulation continuous wave signals with minimal difference frequency, and when receiving, each space-based video SAR only retains the echo signal corresponding to its own carrier frequency through orthogonal isolation; (2) Assume that the space-based distributed video SAR system performs M observations in total. In the kth and k+1th observations, two equivalent long synthetic apertures α that meet the DPCA conditions are constructed by sequentially connecting multiple short synthetic apertures formed by multiple space-based video SARs. k and β k+1 ; (3) Using the frequency domain imaging algorithm represented by polar coordinate formatting, the equivalent long synthetic aperture α k and β k+1 Focus to obtain the video SAR images corresponding to the two apertures and Finally, two sets of video SAR image sequences are obtained and The difference video SAR image sequence Π={△I1,...,△I k ,...,△I M-1 },in is the difference video SAR image obtained for the kth time; (4) Pre-detection and clustering are performed on the difference video SAR images △I1 and △I2, and the shadow and energy matching of the same moving target is achieved based on the range coordinates, and the shadow pre-detection point sets Γ1 and Γ2 of the images △I1 and △I2 are obtained respectively: Where r=1,...,R,q=1,...,Q,R and Q are the total number of pre-detection points on △I1 and △I2 respectively, are the rth and qth shadow detection points on △I1 and △I2 respectively, and are the azimuth offsets of the shadow detection point and energy detection point of the same moving target on △I1 and △I2 respectively; (5) Based on the shadow pre-detection point set Γ1 and Γ2, the state is initialized by velocity matching to obtain the shadow initial state set in is the initial state of the shadow of the mth candidate target in the first frame, M t is the total number of candidate targets to be tracked; (6) Based on the initial state of the shadow of the mth candidate target in the first frame In the M-1 frame video SAR image sequence Perform shadow and energy joint value function accumulation on: (6a) Let the current frame be the hth frame, where h∈[1,M-1); (6b) For the shadow state in the hth frame Perform inter-frame state transfer to obtain the shadow state in the h+1th frame in I2 is the second-order identity matrix, represents the Kronecker product of the matrix, δ x and δ y are the acceleration noises in the x-direction and y-direction respectively, and △t is the time interval between two adjacent frames; (6c) The shadow state of the mth candidate target in the h+1th frame Mapping to energy states (6d) Joint Shadow State and energy status Perform value function accumulation to obtain cumulative value in is the inverse shadow amplitude, is the energy amplitude, are all transitions to state in the hth frame The state set of (7) Repeat step (6) to set the value function Accumulate to the M-1 frame, and then compare it with the set detection threshold V α Compare and determine whether the target to be detected exists: like Then the mth target to be detected exists, and its trajectory in the M-1 frame is traced back. Otherwise, the target to be detected does not exist; (8) Repeat step (7) to complete M t Joint pre-detection tracking of multiple targets to be detected.

2. The method according to claim 1, wherein the design principle of the difference frequency Δf in step (1) is as follows: To ensure that the echo signals of each space-based video SAR can be processed coherently, the difference frequency △f should be set to be smaller than the transmission signal bandwidth B; To ensure that the echo signals of different video SARs can be orthogonally isolated, the difference frequency △f should be greater than the detection scene bandwidth B r = 2w r γ / c, that is, B r <△f < B, where w r is the width of the imaging scene, γ is the frequency modulation slope, and c is the speed of light.

3. The method according to claim 1, wherein in step (2), two equivalent long synthetic apertures α satisfying the DPCA condition are constructed. k and β k+1 , which is expressed as follows: 2a) During the kth observation time △t, the short synthetic aperture L formed by the nth space-based video SAR is obtained nk , the equivalent long synthetic aperture α is obtained by sequentially concatenating multiple short synthetic apertures of the second to Nth space-based video SAR k : α k =L 2k ||L 3k ||...||L nk ||...||L Nk 2b) After time △t, the k+1th observation is performed to obtain the short synthetic aperture L formed by the nth space-based video SAR n(k+1) , by sequentially concatenating multiple short synthetic apertures of the first to the N-1th space-based video SAR, the equivalent long synthetic aperture β is obtained. k+1 : β k+1 =L 1(k+1) ||L 2(k+1) ||...||L n(k+1) ||...||L (N-1)(k+1) 。 4. The method according to claim 1, wherein in step (4), pre-detection and clustering are performed on the difference video SAR images ΔI1 and ΔI2, respectively, and shadow and energy matching of the same moving target is achieved based on range coordinates, and the implementation steps include the following: 4a) Set the detection threshold V T , and compare it with the difference video SAR image △I1 to determine whether there is a shadow or energy: if the SAR image value △I1(x,y) at the position x in the azimuth direction and y in the range direction on △I1 is greater than or equal to the set detection threshold, then the shadow or energy exists; otherwise, the shadow or energy does not exist. Its mathematical expression is as follows: where x=1,...,N x , y=1,...,N y , N x and N y Respectively represent the number of resolution units in the azimuth and range directions of the SAR image, H1 indicates the presence of shadow or energy, and H0 indicates the absence of shadow or energy; 4b) clustering the moving target shadow and energy detection results obtained in step 4a) using a density clustering algorithm, and then averaging and fusing multiple points in the same cluster to obtain an accurate shadow or energy detection point; 4c) Matching the shadow and energy of the same moving target based on the range coordinates to obtain a shadow pre-detection point set Γ1 of the difference video SAR image ΔI1 and a shadow pre-detection point set Γ2 of the difference video SAR image ΔI2: 4c1) Based on SAR images The neighborhood pixel mean of the upper detection point is used to distinguish the results, and all detection points are divided into two categories: shadow detection points and energy detection points; 4c2) Let the rth shadow detection point be The jth energy detection point is And let △r be the distance threshold and compare it with the detection point: like Then the rth shadow detection point and the jth energy detection point belong to the same moving target, achieving the matching of the shadow and energy of the same moving target, and the azimuth offset is recorded as 4c3) Repeat steps 4c1) to 4c2) to traverse all shadow detection points and finally obtain the shadow pre-detection point set 4c4) Repeat steps 4c1) to 4c3) on the difference video SAR image ΔI2 to obtain a shadow pre-detection point set 5. According to the method of claim 1, step (5) implements state initialization by velocity matching based on the shadow pre-detection point sets Γ1 and Γ2, and the implementation steps include the following: 5a) Set and They are the detection points in the shadow pre-detection point set Γ1 and Γ2 respectively. If the coordinate difference between frames satisfies and Then the detection point is considered as a candidate target and its initial state is expressed as: in, is the initial state of the shadow of the mth candidate target in the first frame, That is, the azimuth coordinate difference between frames, That is, the distance coordinate difference between frames, and These are the inter-frame velocity ranges set in azimuth and distance directions respectively; 5b) Repeat step 5a), traverse all detection points in Γ1 and match them with all detection points in Γ2 to obtain the shadow initial state set Among them, M t is the total number of candidate targets to be tracked.

6. The method according to claim 1, wherein in step (6c), the shadow state of the mth candidate target in the h+1th frame is Mapping to energy states The implementation steps include the following: 6c1) According to the azimuth offset of the mth candidate target The shadow state after the inter-frame state transfer Mapping to preliminary energy state in, is the azimuth coordinate of the mth candidate target in the h+1th frame, is the range coordinate of the mth candidate target in the h+1th frame; 6c2) Compensate for the deviation between the initial energy state and the actual state caused by the change in the speed of the moving target, that is, The azimuth coordinates are randomly expanded to obtain the expanded pixel coordinate set: in is the azimuthal coordinate after expansion, which is around the original position By taking a uniform distribution U D (x a ,x b ) is sampled D times; is the distance coordinate after expansion 6c3) Expand the coordinates and The pixel values ​​of all corresponding states are arranged in descending order, and the state with the highest pixel value is taken. As shadow state The energy state after mapping.

Images