CN113687356A - Airborne multi-channel circular track SAR moving target detection and estimation method - Google Patents

Airborne multi-channel circular track SAR moving target detection and estimation method Download PDF

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CN113687356A
CN113687356A CN202111084455.2A CN202111084455A CN113687356A CN 113687356 A CN113687356 A CN 113687356A CN 202111084455 A CN202111084455 A CN 202111084455A CN 113687356 A CN113687356 A CN 113687356A
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CN113687356B (en
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宋冲
汪丙南
周良将
向茂生
施瑞华
王钟斌
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Aerospace Information Research Institute of CAS
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    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/88—Radar or analogous systems specially adapted for specific applications
    • G01S13/89—Radar or analogous systems specially adapted for specific applications for mapping or imaging
    • G01S13/90—Radar or analogous systems specially adapted for specific applications for mapping or imaging using synthetic aperture techniques, e.g. synthetic aperture radar [SAR] techniques
    • G01S13/9004—SAR image acquisition techniques
    • G—PHYSICS
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    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/88—Radar or analogous systems specially adapted for specific applications
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    • G01S13/90—Radar or analogous systems specially adapted for specific applications for mapping or imaging using synthetic aperture techniques, e.g. synthetic aperture radar [SAR] techniques
    • G01S13/9021—SAR image post-processing techniques
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/88—Radar or analogous systems specially adapted for specific applications
    • G01S13/89—Radar or analogous systems specially adapted for specific applications for mapping or imaging
    • G01S13/90—Radar or analogous systems specially adapted for specific applications for mapping or imaging using synthetic aperture techniques, e.g. synthetic aperture radar [SAR] techniques
    • G01S13/904—SAR modes
    • G01S13/9052—Spotlight mode
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/88—Radar or analogous systems specially adapted for specific applications
    • G01S13/89—Radar or analogous systems specially adapted for specific applications for mapping or imaging
    • G01S13/90—Radar or analogous systems specially adapted for specific applications for mapping or imaging using synthetic aperture techniques, e.g. synthetic aperture radar [SAR] techniques
    • G01S13/9094—Theoretical aspects
    • G—PHYSICS
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    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/023—Interference mitigation, e.g. reducing or avoiding non-intentional interference with other HF-transmitters, base station transmitters for mobile communication or other radar systems, e.g. using electro-magnetic interference [EMI] reduction techniques
    • G—PHYSICS
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    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
    • G01S7/414—Discriminating targets with respect to background clutter
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
    • G01S7/415—Identification of targets based on measurements of movement associated with the target
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
    • G01S7/418—Theoretical aspects

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Abstract

The invention provides a method for detecting and estimating an airborne multi-channel circular track SAR moving target, which comprises the following steps: preprocessing an original echo signal; projecting the multi-channel echo signal to a noise subspace by utilizing subspace projection in an original data domain to carry out clutter suppression; positioning the geographic space of the image in an absolute geographic space coordinate system, and constructing a back projection imaging model; performing point-by-point pulse-by-pulse coherent accumulation imaging by using the two-dimensional motion characteristics of the moving target and a back projection algorithm, compensating aircraft motion errors, orientation space-variant errors and errors caused by two-dimensional motion of the moving target, and directly outputting a digital orthophoto map in a geographic reference coordinate system by an imaging result; forming a guide vector by using phase differences generated by the moving target among different channel SAR images, and performing coherent superposition on the multi-channel SAR images to improve the signal-to-noise ratio of the target; and detecting a moving target of the synthesized SAR image, and estimating a two-dimensional motion parameter of the target.

Description

Airborne multi-channel circular track SAR moving target detection and estimation method
Technical Field
The invention relates to the technical field of radars, in particular to a method for detecting and estimating an airborne multi-channel circular SAR moving target.
Background
Synthetic Aperture Radars (SAR) synthesize a large antenna array by platform motion, thereby greatly improving the transverse resolution and realizing two-dimensional high-resolution imaging to the ground. Synthetic Aperture Radar (SAR) -Ground Moving Target Indication (GMTI) Radar system combines SAR imaging and Ground Moving Target Indication technology, has the advantages of all-weather all-time, and therefore has wide application potential in civil and military fields. The airborne multi-channel SAR system can effectively inhibit clutter and interference due to the increase of the airspace degree of freedom, and the detection performance of the system on a moving target is obviously improved. Conventional airborne multi-channel SAR-GMTI systems typically travel in a straight line and have been extensively studied for many years. However, the linear SAR has short observation time for the moving target in the observation area, so that the continuous observation for the moving target cannot be realized, the moving target is inconvenient to track for a long time, and in addition, the linear SAR is sensitive to the distance moving target and is insensitive to the direction moving target. The Multichannel Circular track SAR-GMTI (Multichannel Circular track SAR-GMTI) is used as a new observation mode, has the capability of acquiring 360-degree scattering information, can acquire two-dimensional velocity values of a moving target in an observation area under a plurality of observation angles, and is favorable for estimating the velocity vector of the moving target.
Due to the unknown motion rule of the moving object, the core content of detecting the moving object from the static scene comprises two parts: 1) clutter suppression, namely separating echoes of a moving target and a static target, improving the signal-to-clutter ratio as much as possible and improving the detection rate of the target; 2) and detecting and estimating parameters, namely accurately estimating the motion parameters of the moving target so as to accurately position the moving target. In general, the MCSAR-GMTI system operates in a downward-looking mode when detecting a ground moving target, so that the influence of ground clutter on the detection performance of the system is very serious. The ground clutter has wide distribution range and high intensity, and simultaneously, because the radar platform continuously moves, the ground clutter in different directions have different speeds relative to the radar platform, so that the clutter spectrum is seriously widened, an echo signal of a moving target is submerged in the strong ground clutter, and the detection of the system on the moving target is seriously influenced. In addition, the two-dimensional motion characteristics and low Radar Cross Section (RCS) of slow moving objects exacerbate this difficulty. With the development of MCSAR-GMTI towards high detection rate and high parameter estimation accuracy for slow moving targets, the conventional MCSAR-GMTI clutter suppression and detection processing algorithm cannot meet the requirement.
The traditional detection and estimation algorithm based on the data domain has the following technical defects: the method generally utilizes the space-time two-dimensional characteristic of the clutter to perform self-adaptive clutter suppression, has good clutter suppression performance under ideal conditions, and can detect the slow-speed moving target. However, in order to reduce the secondary phase influence of the moving target on the echo signal, the method generally uses less pulses, that is, the sub-aperture data for processing, so that the signal-to-noise ratio of the target is low, which affects the detection performance of the system. In addition, the adaptive algorithm in this kind of method needs to use uniform sample data to perform clutter covariance estimation, and in practical cases, the environment is non-uniform, so its application is limited, and the estimation and inversion process of the covariance matrix is also computationally complex.
The traditional detection and estimation algorithm based on image domain has the following technical defects: the method utilizes the focused SAR image for processing, and the detection performance is improved to a certain extent because the signal-to-noise ratio of the moving target in the image domain is improved to a certain extent. Because of the two-dimensional motion characteristic of the moving target, defocusing is performed on the SAR image, which causes a certain loss of the signal-to-noise ratio of the target and also deviates from the original position, which brings certain difficulty to the detection and parameter estimation of the target. Moreover, this type of method can only estimate the relative radial velocity of a moving target, but cannot estimate its speed along the course, which is incomplete for the parameter estimation of the target.
Disclosure of Invention
Since the onboard MCSAR-GMTI can carry out 360-degree observation on a moving target for a long time, the system is widely applied and developed in recent years. Considering that the application situation of the airborne MCSAR-GMTI is more and more challenging, such as a complex electromagnetic interference environment, mutual interference of targets in a multi-target distribution scene, small RCS of the targets caused by the use of special materials, submerging of slow moving targets in strong background clutter and the like, and the requirements on the detection capability and parameter estimation accuracy of the moving targets are higher and higher, which puts higher requirements on the airborne MCSAR-GMTI clutter suppression algorithm and the imaging algorithm. In addition, the CSAR-GMTI system is more suitable for being applied to light and small platforms such as unmanned planes and the like, the flight path is a circle, the motion error of the flight platform is larger, and higher requirements are provided for airborne SAR motion compensation algorithms.
The invention has the idea that under a geographic information space coordinate system, an imaging frame of point-by-point pulse-by-pulse coherent accumulation is adopted by a back projection algorithm, errors caused by two-dimensional motion of a moving target can be compensated pixel by pixel, and all-aperture compensation is performed on the space-variant errors of the directions of all pixels and the motion errors of an airplane platform, so that the algorithm is theoretically an algorithm without motion compensation errors. And because the slow-speed low RCS moving target is easily submerged by the widely distributed strong ground clutter background, clutter suppression is carried out in the original data domain by utilizing a subspace projection algorithm, and the signal-to-noise ratio of the target is improved.
Aiming at the moving target detection and estimation of the MCSAR-GMTI system, the method has the main characteristics that the clutter suppression process and the moving target imaging process are organically combined, the signal to noise ratio of the moving target is effectively improved, the detection rate of the system on the moving target is further improved, the two-dimensional motion parameters of the moving target are accurately estimated, and the method has good application potential. Therefore, compared with the traditional processing method, the method has the advantages of strong applicability, higher processing precision, stable detection performance and the like.
The technical scheme of the invention is as follows: an airborne multi-channel circular track SAR moving target detection and estimation method comprises the following steps: step 1, preprocessing MCSAR echo signals, including distance compression, channel equalization and baseline time delay compensation; step 2, projecting the multi-channel echo signal to a noise subspace by utilizing subspace projection to carry out clutter suppression; step 3, constructing a geographic information space of the imaging area network, completing geographic space positioning of the image in a unified absolute geographic space coordinate system, and further constructing a back projection model; step 4, in an absolute geographic space coordinate system, utilizing two-dimensional motion characteristics of a moving target and backward projection imaging to perform point-by-point pulse-by-pulse coherent accumulation imaging, compensating aircraft motion errors, orientation space-variant errors and errors caused by the motion of the moving target, and directly outputting a digital orthophotomap in a geographic reference coordinate system by an imaging result; step 5, obtaining a multi-channel SAR image after imaging, forming a guide vector by using phase differences between different channel SAR images generated by a moving target, and performing multi-channel SAR image coherent superposition to improve the signal-to-noise ratio of the target; and 6, detecting a moving target of the synthesized SAR image, and determining a two-dimensional moving parameter of the target by using the parameter result.
Has the advantages that:
the invention has the idea that under a geographic information space coordinate system, an imaging frame of point-by-point pulse-by-pulse coherent accumulation is adopted by a back projection algorithm, errors caused by two-dimensional motion of a moving target can be compensated pixel by pixel, and all-aperture compensation is performed on the space-variant errors of the directions of all pixels and the motion errors of an airplane platform, so that the algorithm is theoretically an algorithm without motion compensation errors. And because the slow-speed low RCS moving target is easily submerged by the widely distributed strong ground clutter background, clutter suppression is carried out in the original data domain by utilizing a subspace projection algorithm, and the signal-to-noise ratio of the target is improved. Aiming at the moving target detection and estimation of the MCSAR-GMTI system, the method has the main characteristics that the clutter suppression process and the moving target imaging process are organically combined, the signal to noise ratio of the moving target is effectively improved, the detection rate of the system on the moving target is further improved, the two-dimensional motion parameters of the moving target are accurately estimated, and the method has good application potential. Therefore, compared with the traditional processing method, the method has the advantages of strong applicability, higher processing precision, stable detection performance and the like.
In conclusion, the clutter suppression process and the imaging process of the moving target of the multi-channel circular track SAR system are organically combined, and the technical scheme has the remarkable advantages of strong environment adaptability, high motion compensation precision, high detection rate of the moving target, high two-dimensional motion parameter estimation precision and the like.
Drawings
FIG. 1 is a flow chart of an airborne multi-channel circular track SAR moving target detection and estimation method of the present invention;
FIG. 2 is an operation flow chart of an airborne multi-channel circular track SAR moving target detection and estimation method of the present invention;
FIG. 3 is a geometrical diagram of airborne multi-channel circular track SAR observation;
FIG. 4 is a schematic view of a subspace projection.
Detailed Description
The technical solutions in the embodiments of the present invention will be described clearly and completely with reference to the accompanying drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, rather than all embodiments, and all other embodiments obtained by a person skilled in the art based on the embodiments of the present invention belong to the protection scope of the present invention without creative efforts.
The invention discloses an airborne multi-channel circular track SAR moving target detection and estimation method, which comprises the steps of performing clutter suppression based on subspace projection of an original data domain under a geographic information space rectangular coordinate system, then performing MCSAR imaging by adopting a back projection imaging model, completing the processing steps of registration, phase unwrapping and the like while imaging, completing the coherent superposition of multi-channel SAR images by utilizing a guide vector between channels, and finally realizing the detection of a moving target and the estimation of a moving parameter of the moving target by an MCSAR-GMTI system.
The flow chart of the technical scheme of the invention is shown in figure 1, and the specific operation flow chart is shown in figure 2. The method specifically comprises the following steps:
step 1, preprocessing MCSAR echo signals, including distance compression, channel equalization, baseline delay compensation and the like.
And 2, projecting the multi-channel echo signal to a noise subspace by utilizing subspace projection to carry out clutter suppression.
And 3, constructing a geographic information space of the imaging area network, completing geographic space positioning of the image in a unified absolute geographic space coordinate system, and further constructing a back projection model.
And 4, in an absolute geographic space coordinate system, utilizing the two-dimensional motion characteristics of the moving target and backward projection imaging to perform point-by-point pulse-by-pulse coherent accumulation imaging, compensating aircraft motion errors, orientation space-variant errors and errors caused by the motion of the moving target, and directly outputting a digital orthophotomap in a geographic reference coordinate system by an imaging result.
And 5, obtaining a multi-channel SAR image after imaging, forming a guide vector by using phase differences between different channel SAR images generated by the moving target, and performing coherent superposition on the multi-channel SAR images to improve the signal-to-noise ratio of the target.
And 6, detecting a moving target of the synthesized SAR image, and determining a two-dimensional moving parameter of the target by using the parameter result.
Through the steps, the detection and parameter estimation processes of the MCSAR-GMTI system moving target can be completed.
The following detailed description of embodiments of the invention,
the method comprises the following steps that step 1, the MCSAR echo signals are preprocessed, and the preprocessing comprises distance compression, channel equalization, baseline delay compensation and the like.
FIG. 3 is a geometrical diagram of airborne multi-channel circular SAR observation, in which the radar platform has N channels along the course, and the motion track is a track with radius raHas an angular velocity of ω and a height of H. Rn(t) (N is 1, N) is the distance between the moving target and the radar channel N at the time t, t is the azimuth slow time, and the speed of the moving target along the x-axis direction is VxVelocity V in the y-axis directiony. Assuming that t is 0, the beam center of the radar passes through the target, and the radar is square to the x axisThe included angle is phi, and the radar coordinate is (r)acos(φ),rasin (phi), H), and the target position of motion is (x)0,y00), then the target is at a distance of 1 from the channel
Figure BDA0003265058880000051
The distance equation at time t is:
Figure BDA0003265058880000052
wherein the content of the first and second substances,
Figure BDA0003265058880000053
is the radial velocity of the moving object relative to the radar platform.
Assuming that the transmission signal is a chirp signal, the nth receiving channel moving target signal after demodulation and distance compression can be represented as:
Figure BDA0003265058880000054
τ is the range fast time, λ is the radar carrier wavelength, A0Is the complex scattering coefficient, p, of the objectr(g) Is the envelope of the distance-wise sinc function, wan(t) (N ═ 1.., N) is an azimuth window function.
Because the transceiving characteristics of each channel are different, channel equalization correction is needed, and the antenna directional diagram w of the nth channel is corrected by taking the first channel as a referencean(t) after channel equalization correction:
wa1(t)＝...＝waN(t)CN
wherein C isnComplex, corrected amplitude and phase;
after the channel equalization, the echo signal after the baseline delay compensation preprocessing can be:
Figure BDA0003265058880000055
wherein d isn(n＝1,...,N,d10) is the physical base length between the channels, from which equation a moving object produces one channel between the channels
Figure BDA0003265058880000056
The phase difference is fixed.
From s'n(τ, t) knowing that for stationary clutter background, i.e. Vx＝0,VyWhen the phase difference generated between the channels is 0, it is recorded as a clutter steering vector ac：
ac＝[1,1,…,1]T
Wherein [. ]]TIs a transpose of a matrix, acIs an N × 1 dimensional matrix.
And the moving object generates a fixed phase difference between the channels, which is recorded as a target guide vector at：
Figure BDA0003265058880000061
Step 2, utilizing subspace projection to project the multi-channel echo signal to a noise subspace for clutter suppression, specifically as follows:
as shown in FIG. 4, ΩcIs a clutter subspace, ΩnWhich are the noise subspaces, they are orthogonal. StFor moving object signals, θ is the vector StAnd omegacThe angle of the axes being determined by the radial velocity of the moving object, vector StIs indicative of the energy of the target signal. P is a clutter subspace projection matrix which can be guided by a clutter guide vector acStretching:
Figure BDA0003265058880000062
wherein [. ]]HFor matrix conjugate transposition [ ·]-1A matrix inversion operation is performed.
For clutter suppression, the signal should be projected into the noise subspace, and the projection matrix is:
ψ＝(I-P)
where I is an N dimensional identity matrix.
Considering practical conditions, the multi-channel radar echo signal S comprises a moving target signal StGround stationary clutter ScAnd N × 1 dimensional thermal noise W, i.e.:
S＝Sc+St+W
wherein StFor an N × 1 dimensional target signal:
Figure BDA0003265058880000063
Scis a static clutter of dimension Nx 1 (V)x＝0,Vy0) signal:
Figure BDA0003265058880000064
projecting the signal S into the noise subspace using a projection matrix:
S'＝ψS＝ψ(Sc+St+W)＝ψSt+W
line S't＝ψStAnd then:
Figure BDA0003265058880000071
meanwhile, the moving target guide vector also performs a rotation operation, namely:
a't＝ψat
the clutter suppression operation of the MCSAR-GMTI is realized by utilizing the process, and then the signal after clutter suppression is imaged by utilizing a back projection algorithm according to the possible motion parameters of the target so as to improve the signal-to-noise ratio of the target.
And 3, constructing a geographic information space of the imaging area network, completing geographic space positioning of the image in a unified absolute geographic space coordinate system, and further constructing a back projection model. The method comprises the following specific steps: from the above step 4, the imaging model signal after clutter suppression is:
S't＝s1(τ,t)a't
wherein s is1In (tau, t) signals
Figure BDA0003265058880000072
Is Doppler phase history compensation item, which can realize coherent accumulation in the synthetic aperture after compensating the phase, and the phase item and the two-dimensional motion parameter V of the moving targetxAnd VyIn relation to this, the image can thus be brought to the best focus by searching for different target parameters.
And 4, in an absolute geographic space coordinate system, point-by-point pulse-by-pulse coherent accumulation imaging is performed by utilizing the two-dimensional motion characteristics of the moving target and backward projection imaging, the aircraft motion error, the azimuth space-variant error and the error caused by the motion of the moving target are compensated, and the imaging result directly outputs a digital orthophotomap in a geographic reference coordinate system.
The basic idea of the back projection imaging algorithm is to find out a corresponding accumulation curve for coherent accumulation by calculating the two-way time delay from each pixel in an imaging area to an SAR antenna platform in an aperture length, thereby recovering the target function of each pixel. When the imaged motion parameters are matched with the motion parameters of the actual moving target, the signals after imaging the data after clutter suppression by utilizing a back projection algorithm are as follows:
Figure BDA0003265058880000073
wherein PRF (pulse repetition frequency) is the pulse repetition frequency, and M is the total number of pulses in the synthetic aperture time. Therefore, for any pixel point in the geocoded raster image, integration (coherent accumulation) is performed along the synthetic aperture time, and imaging of the pixel point can be achieved.
And 5, obtaining a multi-channel SAR image after imaging, forming a guide vector by using phase differences between different channel SAR images generated by the moving target, and performing coherent superposition on the multi-channel SAR images to improve the signal-to-noise ratio of the target. The method comprises the following specific steps:
when the search parameter is consistent with the motion target parameter, the image is best focused, the signal-to-noise ratio is highest, and the corresponding search parameter is assumed to be V'xAnd V'yAnd from this, V 'is calculated'rFrom V'rConstructing a target guide vector:
Figure BDA0003265058880000081
and performing coherent accumulation on the output multi-channel SAR image by using the guide vector, namely:
Figure BDA0003265058880000082
where K is the gain produced by coherent addition for the steering vector to match the phase difference between the channels.
Step 6, performing moving target detection on the synthesized SAR image, and determining a two-dimensional moving parameter of the target by using the parameter result, specifically including:
after the steps are carried out, the clutter suppression of the MCSAR-GMTI and the focusing process of the moving target are finished, then the moving target is detected, and according to the output value of Z (x, y):
Figure BDA0003265058880000083
wherein gamma is detection threshold, can be calculated from constant false alarm rate, and is H when output value Z (x, y) is greater than threshold1The case that the unit has a moving object, when Z (x, y) is less than the threshold, it is H0The case is that the unit does not have a moving object. Meanwhile, as the imaging result is related to the motion parameter of the target, the two-dimensional motion parameter estimation of the target can be carried out by using the method:
Figure BDA0003265058880000084
wherein omegavWhen different target motion parameters are used for back projection imaging and the output response Z (x, y) is maximum, the search parameters are considered as the parameters of the moving target.
Figure BDA0003265058880000085
And
Figure BDA0003265058880000086
the estimated speed of the target in the x-axis direction and in the y-axis direction.
Although illustrative embodiments of the present invention have been described above to facilitate the understanding of the present invention by those skilled in the art, it should be understood that the present invention is not limited to the scope of the embodiments, but various changes may be apparent to those skilled in the art, and it is intended that all inventive concepts utilizing the inventive concepts set forth herein be protected without departing from the spirit and scope of the present invention as defined and limited by the appended claims.

Claims (4)

1. An airborne multi-channel circular track SAR moving target detection and estimation method is characterized by comprising the following steps:
step 1, preprocessing MCSAR echo signals, including distance compression, channel equalization and baseline time delay compensation;
step 2, projecting the multi-channel echo signal to a noise subspace by utilizing subspace projection to carry out clutter suppression;
step 3, constructing a geographic information space of the imaging area network, completing geographic space positioning of the image in a unified absolute geographic space coordinate system, and further constructing a back projection model;
step 4, in an absolute geographic space coordinate system, utilizing two-dimensional motion characteristics of a moving target and backward projection imaging to perform point-by-point pulse-by-pulse coherent accumulation imaging, compensating aircraft motion errors, orientation space-variant errors and errors caused by the motion of the moving target, and directly outputting a digital orthophotomap in a geographic reference coordinate system by an imaging result;
step 5, obtaining a multi-channel SAR image after imaging, forming a guide vector by using phase differences between different channel SAR images generated by a moving target, and performing multi-channel SAR image coherent superposition to improve the signal-to-noise ratio of the target;
and 6, detecting a moving target of the synthesized SAR image, and determining a two-dimensional moving parameter of the target by using the parameter result.
2. The method for detecting and estimating the airborne multi-channel circular track SAR moving target according to claim 1, wherein the distance compression, the channel equalization and the baseline delay compensation in the step 1 are specifically as follows: let the n channel radar original echo signal be
Figure FDA0003265058870000011
N is 1, the distance direction fast time, t is the azimuth direction slow time, the distance direction matched filtering is carried out on the distance direction fast time, the filtering function is p (- τ), and the obtained distance compression signal is:
Figure FDA0003265058870000012
wherein
Figure FDA0003265058870000013
Is a convolution;
because the transmitting and receiving characteristics of each channel are different, channel equalization correction is needed, and the antenna directional diagram of the nth channel is wan(t), after channel equalization correction:
wa(t)＝wa1(t)*C1＝...＝waN(t)CN
wherein C isnComplex, corrected amplitude and phase;
since the base line length between the channels causes a phase shift, a baseline delay compensation is required:
Figure FDA0003265058870000014
wherein d isnIs the physical base length between channels, N110, ω is the angular velocity of the aircraft platform, raIs the flight circumference radius of the aircraft platform.
3. The method for detecting and estimating the airborne multi-channel circular track SAR moving target according to claim 1, wherein in the step 2, the multi-channel echo signal is projected to a noise subspace by using subspace projection, and clutter suppression is specifically performed as follows:
considering practical conditions, the multi-channel radar echo signal S comprises a moving target signal StGround stationary clutter ScAnd noise W, i.e.:
S＝Sc+St+W
projecting the echo signals to a noise subspace for clutter suppression:
S'＝ψS＝ψ(Sc+St+W)＝ψSt+W
where ψ is the projection matrix.
4. The method for detecting and estimating the moving target of the airborne multi-channel circular track SAR as claimed in claim 1, wherein the step 4 utilizes the two-dimensional moving feature of the moving target and backward projection imaging point-by-point pulse-by-pulse coherent accumulation imaging, and specifically comprises the following steps: for multi-channel circular track SAR, the base line exists and the motion characteristic of the moving target generates
Figure FDA0003265058870000021
Wherein V isrThe radial velocity of the moving target is the projection of the two-dimensional resultant velocity of the moving target on the slant distance surface; firstly, the echo signal of each channel is processed by utilizing a back projection algorithmPulse accumulation in synthetic aperture time is carried out to complete focusing imaging of the moving target, and then coherent superposition of echo signals between channels is carried out by utilizing phase difference between the channels:
Figure FDA0003265058870000022
(x, y) is a coordinate point of a geodetic coordinate system, K is a constant gain, M is the number of pulses in the synthetic aperture time, PRF (pulse repetition frequency) is the pulse repetition frequency, R is the pulse repetition frequency1And (t) the slant distance between the moving target and the 1 st channel of the radar, and the slant distance is related to the two-dimensional motion of the moving target and the motion of the airplane platform.
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