CN111077524B - SAR-GMTI moving target repositioning improvement method - Google Patents
SAR-GMTI moving target repositioning improvement method Download PDFInfo
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Abstract
The invention belongs to the technical field of radars, and particularly relates to an SAR-GMTI moving target repositioning improvement method, which comprises the following steps: acquiring a multi-channel SAR image, a moving target detection position, a yaw angle compensation residue and a terrain elevation map; sequentially carrying out error compensation and image registration on the multi-channel SAR image to obtain a processed multi-channel SAR image; obtaining the radial speed of the moving target by utilizing self-adaptive matched filtering according to the processed multi-channel SAR image; obtaining an azimuth echo signal after the distance of the moving target is compressed according to the processed multi-channel SAR image; performing matched filtering on the azimuth echo signal after the distance compression of the moving target to obtain the azimuth speed of the moving target; and performing mobile target relocation on the processed multi-channel SAR image according to the mobile target radial speed, the mobile target azimuth speed, the mobile target detection position, the yaw angle compensation residue and the terrain elevation map. The positioning device has the beneficial effect of accurate positioning.
Description
Technical Field
The invention belongs to the technical field of radars, and particularly relates to an SAR-GMTI moving target repositioning improvement method.
Background
The SAR-GMTI can estimate and position the speed of a ground moving target while ensuring high-resolution imaging of the radar, and is a main function of a modern military early warning and monitoring radar system. In addition, in the civil field, SAR-GMTI has been widely applied to tasks such as traffic monitoring and planning, ship monitoring, ocean current observation, and the like.
SAR imaging achieves the purpose of high azimuth resolution by increasing observation aperture through azimuth multi-pulse. Scholars at home and abroad make a great deal of research and can well image static scenes, for example: RD (Range-Doppler) algorithm, CS (Chirp Scaling) algorithm, SPECAN (Spectral Analysis) algorithm, BP (Back Projection) algorithm, etc. However, in the SAR-GMTI system, lei Dazheng is in side view operation, the Doppler modulation frequency of the echo signal is related to the radial velocity of the moving target. In addition, in the case of platform yaw, the Doppler modulation frequency of the echo signals is also related to the azimuth velocity, elevation and yaw angle of the target. When a moving target is imaged, if a reference function is generated by the frequency modulation slope of a static target echo signal, the azimuth direction defocusing of the moving target is serious, and an image becomes fuzzy or even cannot be imaged. Meanwhile, the reduction of the target amplitude reduces the detection probability and affects the determination of the detection position, thereby affecting the relocation of the moving target on the SAR image. Therefore, a large number of scholars propose a moving target self-focusing algorithm without moving target parameter estimation, which mainly includes a spectral peak tracking method, a sub-aperture correlation (Map Drift, MD) method, a Phase Gradient self-focusing (PGA) method, a minimum entropy method, a second-order Keystone transformation method, a BFCA (bead Frequency Coherent integration) method, and the like; in addition, moving-target focusing imaging algorithms based on parameter estimation are also extensively studied and applied. The chirp signals are mainly classified into two types, and the first type is a parameter estimation method for a PPS (poly-phase signal) model, which mainly includes the following steps. Wherein, the method mainly comprises ML (Maximum Likelihood) method, MFT (Match Fourier Transform) method, NILS (Nonlinear instant Least square) method, DCFT (Discrete chip Fourier Transform) method, HAF (High-order Ambiguity Functions) method and the like; the other is a moving target focusing method based on Time-frequency transformation, which includes STFT (Short Time Fourier Transform) method, WVD (Wigner-Ville Distribution) method, S transformation, wavelet transformation, etc.
After the moving target is focused, the moving target is repositioned on the SAR image, which is an essential step of the SAR-GMTI system, and meanwhile, the positioning error is an important index for representing the data processing performance. The article states that the relative image offset of a moving object is related only to the moving object radial velocity, which affects the focus of the object only in the azimuthal direction, and is referred to herein as the "conventional repositioning method". However, in fact, the azimuthal velocity of the target affects the azimuthal focus of the target and also affects the relative offset of the moving target on the SAR image. Particularly, when the azimuth speed of the target is high, the positioning precision of the traditional repositioning method is obviously reduced; in addition, under the condition that the platform has residual yaw compensation and the moving target has elevation, the positioning precision of the traditional positioning method is further reduced.
Disclosure of Invention
In order to solve the problems in the prior art, the invention provides an improved SAR-GMTI moving target relocation method. The technical problem to be solved by the invention is realized by the following technical scheme:
a SAR-GMTI moving target relocation improving method comprises the following steps:
acquiring a multi-channel SAR image, a moving target detection position, a yaw angle compensation residue and a terrain elevation map;
sequentially carrying out error compensation and image registration on the multi-channel SAR image to obtain a processed multi-channel SAR image;
obtaining a moving target radial velocity by utilizing self-adaptive matched filtering according to the processed multi-channel SAR image;
obtaining an azimuth echo signal after the distance of the moving target is compressed according to the processed multi-channel SAR image;
performing matched filtering on the azimuth echo signal after the moving target distance compression to obtain the azimuth speed of the moving target;
and performing mobile target relocation on the processed multi-channel SAR image according to the mobile target radial speed, the mobile target azimuth speed, the mobile target detection position, the yaw angle compensation residue and the terrain elevation map.
In an embodiment of the present invention, obtaining a moving target radial velocity by using adaptive matched filtering according to the processed multi-channel SAR image includes:
selecting a clutter sample at the position of the moving target on the processed multi-channel SAR image, and obtaining a clutter covariance matrix according to the clutter sample;
and setting a moving target radial speed search range on the clutter covariance matrix, and carrying out adaptive matched filtering search on the clutter covariance matrix according to the moving target radial speed search range to obtain the moving target radial speed.
In one embodiment of the invention, the moving target radial velocity
The expression is as follows:
wherein, the first and the second end of the pipe are connected with each other,
R cn is a clutter covariance matrix, x s For moving object multi-channel data, a (v) r ) Searching a guide vector for the radial velocity of a moving target, wherein L is the number of samples, N is the number of antenna azimuth channels, d is the channel spacing, lambda is the signal wavelength, v p Is the platform velocity.
In an embodiment of the present invention, performing matched filtering on the azimuth echo signal after compressing the distance of the moving target to obtain the azimuth speed of the moving target includes:
performing matched filtering on the azimuth echo signal after the moving target distance compression to obtain Doppler frequency modulation rate
Further obtaining the azimuth velocity v of the moving target a ：
Wherein v is a For moving the target azimuth speed, s r (t) is the azimuth echo signal after the distance compression of the moving target, f dc ＝2v r λ is Doppler center frequency, T m For azimuthal accumulation of time, R t The distance between two adjacent targets is the slant distance of the moving target,
is the moving target radial velocity.
The invention has the beneficial effects that:
the invention considers the azimuth speed of the moving target, and can accurately position the moving target when the azimuth speed of the moving target is higher; the invention also considers the yaw angle of the antenna, can adapt to a certain residual yaw SAR-GMTI system and accurately positions the moving target.
The present invention will be described in further detail with reference to the accompanying drawings and examples.
Drawings
FIG. 1 is a schematic flow chart of an improved SAR-GMTI moving target relocation method provided by an embodiment of the present invention;
FIG. 2 is a moving target imaging geometry of a SAR-GMTI moving target repositioning improvement method provided by an embodiment of the invention;
FIG. 3 is a moving target focused imaging diagram of an improved SAR-GMTI moving target repositioning method provided by an embodiment of the present invention;
FIG. 4 is a diagram of the result of error analysis of an improved SAR-GMTI moving target relocation method provided by the embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to specific examples, but the embodiments of the present invention are not limited thereto.
Referring to fig. 1, fig. 1 is a schematic flow chart of an improved method for relocation of a SAR-GMTI moving target according to an embodiment of the present invention, including:
acquiring a multi-channel SAR image, a moving target detection position, a yaw angle compensation residue and a terrain elevation map;
sequentially carrying out error compensation and image registration on the multi-channel SAR image to obtain a processed multi-channel SAR image;
obtaining a moving target radial velocity by utilizing self-adaptive matched filtering according to the processed multi-channel SAR image;
obtaining an azimuth echo signal after the distance of the moving target is compressed according to the processed multi-channel SAR image;
performing matched filtering on the azimuth echo signal after the moving target distance compression to obtain the azimuth speed of the moving target;
and performing mobile target relocation on the processed multi-channel SAR image according to the mobile target radial speed, the mobile target azimuth speed, the mobile target detection position, the yaw angle compensation residue and the terrain elevation map.
The invention considers the azimuth speed of the moving target, and can accurately position the moving target when the azimuth speed of the moving target is higher; the invention also considers the yaw angle of the antenna, can adapt to a certain residual yaw SAR-GMTI system and accurately positions the moving target.
In an embodiment of the present invention, obtaining a moving target radial velocity by using adaptive matched filtering according to the processed multi-channel SAR image includes:
selecting a clutter sample at the position of the moving target on the processed multi-channel SAR image, and obtaining a clutter covariance matrix according to the clutter sample;
and setting a moving target radial speed search range on the clutter covariance matrix, and carrying out adaptive matched filtering search on the clutter covariance matrix according to the moving target radial speed search range to obtain the moving target radial speed.
In one embodiment of the invention, the moving target radial velocity
The expression is as follows:
wherein the content of the first and second substances,
R cn is a clutter covariance matrix, x s For moving object multi-channel data, a (v) r ) Searching a guide vector for the radial velocity of a moving target, wherein L is the number of samples, N is the number of antenna azimuth channels, d is the channel spacing, lambda is the signal wavelength, v p Is the platform velocity.
In an embodiment of the present invention, performing matched filtering on the azimuth echo signal after compressing the distance of the moving target to obtain the azimuth speed of the moving target includes:
performing matched filtering on the azimuth echo signal after the moving target distance compression to obtain Doppler frequency modulation rate
Wherein v is a For moving target azimuth speed s r (t) is the azimuth echo signal after the distance compression of the moving target,
to move the target radial velocity, f dc ＝2v r λ is the Doppler center frequency, T m For azimuthal accumulation of time, R t Is the slant distance of the moving target.
Specifically, the azimuth echo signal after the distance compression can usually adopt a linear frequency modulation signal model, so that an echo doppler frequency modulation rate estimation can be obtained by adopting a matched filtering processing method, and further the azimuth speed of the moving target can be obtained.
Further, for accurate relocation of the moving target on the processed multi-channel SAR image, the relative offset of the moving target on the SAR image needs to be calculated, and the offset of the moving target on the SAR image is not only related to the target radial velocity (traditional location), but also related to the moving target azimuth velocity, the yaw angle compensation residue and the topographic elevation map.
Referring to fig. 2, fig. 2 is a moving target imaging geometric diagram of an improved SAR-GMTI moving target relocation method provided in an embodiment of the present invention, and meanwhile, considering a moving target radial velocity, a moving target azimuth velocity, a yaw angle compensation residue, and a terrain elevation diagram, an accurate expression of a slope distance is:
wherein R is B For a moving target the true nearest slope, y, on the SAR image 0 Is R B Projection in the azimuthal direction, R 0 Is R B Projection on a zero Doppler plane, v p Is the platform velocity, v r Is the moving target radial velocity;
where θ is the down viewing angle, θ yaw H is the platform height, and H is the height of the position of the moving target relative to the SAR image reference point, namely the target elevation.
Considering the influence of azimuth speed, yaw angle compensation residue and a terrain elevation map of the moving target, the slope distance of the moving target can be written as follows:
wherein, the first and the second end of the pipe are connected with each other,
assuming that the target is a slow target and does not generate doppler blur, the signal model represented by the above formula is transformed into a two-dimensional frequency domain according to the Principle of Stationary Phase (PSP), that is, the distance-azimuth two-dimensional frequency domain signal after distance compression is:
wherein σ s For moving target backscattering coefficient, P (f) is the distance packageFourier transform of the network, ω (t) m ) As a function of the azimuth window, c is the speed of light, f is the range frequency, f a Is the azimuth frequency, f c Is the carrier frequency;
the two-dimensional optimal matching reference function of the two-dimensional echo signal of the moving target echo is as follows:
wherein, W r (f,f a ) The two-dimensional frequency domain window function is adopted, the frequency domains are multiplied, and the signal frequency domain after the quadratic term is eliminated is as follows:
fourier Transform (IFT) is a time domain signal, and the imaging result after the two-dimensional compression of the moving target signal is obtained is as follows:
wherein t is the fast time of the distance, t m For azimuth slow time, G is the range pulse pressure gain, A is the azimuth compression gain, Δ B is the signal bandwidth, B D Is the target doppler bandwidth;
from the imaging offset of the moving target in the above formula, the precise repositioning formula of the present invention is as follows:
wherein the content of the first and second substances,
v′ r is an equivalent radial velocity, x d For the imaging azimuth position, R, of the moving target on the SAR image d The corresponding slant distance is increased for the position of the moving target on the SAR image, namely imagingAnd (4) slope distance.
From the above, it can be seen that when the radar front surface is not yawing, the equivalent radial velocity v' r ＝v r The method of the present invention degenerates to a relocation method that only considers azimuth velocity. At this time, if the target azimuth velocity satisfies v a <<v p The method is characterized in that the positioning error caused by the azimuth speed can be ignored, and the method is degenerated into the traditional positioning method; however, when the azimuth speed of the target is high, especially when the radar front surface has residual yaw angle compensation and the target has elevation, the positioning accuracy of the traditional positioning method is sharply reduced. Compared with the traditional method, the method comprehensively considers the influence of the target radial speed, the azimuth speed and the elevation and the residual compensation of the platform yaw angle, and can accurately reposition the moving target.
It should be noted that the accurate relocation of the moving target requires that the parameters of the platform and the moving target are accurately known, but due to the limitation of the accuracy of the speed measurement and height measurement algorithms, each parameter inevitably has a certain error. Thus, moving target azimuth repositioning will produce errors. According to the moving target accurate repositioning formula, the positioning accuracy is mainly related to the moving target radial velocity estimation error delta v r Moving target azimuth velocity estimation error delta v a Target elevation estimation error delta h and yaw angle compensation residual delta theta yaw It is related.
(1) Moving target radial velocity estimation error:
(2) Moving target azimuth speed estimation error:
(3) Platform yaw angle compensation remains:
(4) Target elevation estimation error:
wherein the content of the first and second substances,
the error analysis results show that the larger the distance between the radar and the target is, the more obvious the influence of target radial speed and azimuth speed estimation errors and residual yaw angle compensation on positioning errors is; in addition, under the influence of elevation errors, the positioning accuracy of the moving target is in negative correlation with the action distance, and the influence of the elevation of the target on the positioning accuracy is smaller when the distance is longer.
The effect of the present invention can be illustrated by the following simulation experiment:
1. simulation conditions are as follows:
the experimental simulation aims at solving the problems that for a typical airborne SAR-GMTI system, a radar works in an X wave band and a linear frequency modulation signal carrier frequency f c =9GHz, bandwidth Δ B =150MHz, pulse width T p =5 μ s, pulse repetition frequency PRF =1000Hz, light speed c =3 × 10 8 m/s, aircraft altitude H =8000m, aircraft speed v p =200m/s, antenna yaw angle θ yaw =0.5 °, moving object located at scene center, moving object radial velocity v r =5m/s, moving target azimuth velocity v a =10m/s, topographic elevation map h =50m.
2. Simulation content and result analysis:
In order to compare the conventional positioning method with the present invention, moving targets with different parameters are set, and after imaging, self-focusing and repositioning, the azimuth positioning error is calculated, as shown in the following table:
comparing table between traditional positioning method and the method of the present invention
As can be seen from the comparison table of the traditional positioning method and the method of the invention, under the condition that the aircraft has no yaw, when the target has only radial speed, the traditional positioning method can accurately position the target; when the target has azimuth speed, the positioning accuracy of the traditional method is reduced; under the condition that the aircraft has yaw, the repositioning error of the traditional method is increased sharply, and meanwhile, the target elevation also has certain influence on the target repositioning; however, in the above several cases, the method provided by the present invention can accurately locate the moving target.
And 2, in order to analyze the influence of the estimation error of each parameter on the positioning accuracy of the method provided by the invention, computer simulation is respectively carried out on point targets at the positions 10km, 30km and 50km away from the radar by combining with a signal model, the simulation result refers to fig. 4, and fig. 4 is an error analysis result diagram of the SAR-GMTI moving target relocation improvement method provided by the embodiment of the invention.
For a typical airborne SAR-GMTI system, as can be seen from fig. 4, the position location accuracy and each error are approximately linear for moving targets at different distances.
As can be seen from fig. 4 (a) and 4 (b), the azimuth positioning accuracy of the moving target on the SAR image is mainly determined by the target radial velocity error and the yaw angle compensation margin, and the larger the detection distance is, the more the positioning accuracy deteriorates. Therefore, accurate estimation of the target radial velocity and accurate compensation of the platform yaw angle are required in order to achieve accurate positioning of the target.
As can be seen from fig. 4 (c), the target azimuth velocity estimation accuracy also has a certain influence on the moving target positioning. The farther the target is from the radar, the greater the slope of the error curve, i.e., the farther the target is from the radar, the more sensitive the positioning error is to the target azimuth velocity estimation error.
However, the target elevation estimation error from FIG. 4 (d) has less impact on the moving target relocation method of the present invention. Moreover, the farther the moving target is away from the platform, the less sensitive the positioning accuracy is to the moving target elevation error.
The foregoing is a more detailed description of the invention in connection with specific preferred embodiments and it is not intended that the invention be limited to these specific details. For those skilled in the art to which the invention pertains, several simple deductions or substitutions can be made without departing from the spirit of the invention, and all shall be considered as belonging to the protection scope of the invention.
Claims (4)
1. A SAR-GMTI moving target relocation improving method is characterized by comprising the following steps:
acquiring a multi-channel SAR image, a moving target detection position, a yaw angle compensation residue and a terrain elevation map;
sequentially carrying out error compensation and image registration on the multi-channel SAR image to obtain a processed multi-channel SAR image;
obtaining a moving target radial velocity by utilizing self-adaptive matched filtering according to the processed multi-channel SAR image;
obtaining an azimuth echo signal after the distance of the moving target is compressed according to the processed multi-channel SAR image;
performing matched filtering on the azimuth echo signal after the distance compression of the moving target to obtain the azimuth speed of the moving target;
and performing target relocation on the processed multi-channel SAR image according to the moving target radial speed, the moving target azimuth speed, the moving target detection position, the yaw angle compensation residue and the terrain elevation map.
2. The SAR-GMTI moving target repositioning improvement method according to claim 1, wherein obtaining a moving target radial velocity by using adaptive matched filtering according to the processed multi-channel SAR image comprises:
selecting a clutter sample at the position of the moving target on the processed multi-channel SAR image, and obtaining a clutter covariance matrix according to the clutter sample;
and setting a moving target radial speed search range on the clutter covariance matrix, and carrying out adaptive matched filtering search on the clutter covariance matrix according to the moving target radial speed search range to obtain the moving target radial speed.
3. The SAR-GMTI moving target relocation improvement method according to claim 1, characterized in that the moving target radial velocity
The expression is as follows:
wherein the content of the first and second substances,
R cn is a clutter covariance matrix, x s For moving object multi-channel data, a (v) r ) Searching a guide vector for the radial velocity of a moving target, wherein L is the number of samples, N is the number of antenna azimuth channels, d is the channel spacing, lambda is the signal wavelength, v p Is the platform velocity.
4. The SAR-GMTI moving target repositioning improvement method according to claim 1, wherein the obtaining of the moving target azimuth speed by performing matched filtering on the azimuth echo signal after the moving target distance compression comprises:
the azimuth echo signal after the distance compression of the moving target is carried outObtaining Doppler frequency modulation rate by matched filtering
Further obtaining the azimuth velocity v of the moving target a ：
Wherein v is a For moving the target azimuth speed, s r (t) is the azimuth echo signal after the distance compression of the moving target, f dc ＝2v r λ is Doppler center frequency, T m For azimuthal accumulation of time, R t The distance between two adjacent targets is the slant distance of the moving target,
is the moving target radial velocity.
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| CN111965643B (en) * | 2020-07-10 | 2022-11-04 | 西安电子科技大学 | Method for refocusing moving ship target in squint SAR BP image |
| CN112162281B (en) * | 2020-08-28 | 2022-11-25 | 西安电子科技大学 | Multi-channel SAR-GMTI image domain two-step processing method |
| CN113447925B (en) * | 2021-05-12 | 2022-10-11 | 北京理工大学 | Ground moving object parameter estimation method based on image domain deviation characteristics |
| CN115128610B (en) * | 2022-09-01 | 2022-12-06 | 中国科学院空天信息创新研究院 | Satellite-borne SAR-GMTI moving target geometric positioning method |
| CN115267721B (en) * | 2022-09-27 | 2022-12-20 | 中国电子科技集团公司第十四研究所 | Ground moving target radial velocity estimation method based on double-frequency SAR |
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