CN115356730B - High-resolution CSAR imaging method and device based on two-dimensional self-focusing - Google Patents
High-resolution CSAR imaging method and device based on two-dimensional self-focusing Download PDFInfo
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Abstract
The application relates to a high-resolution CSAR imaging method and device based on two-dimensional self-focusing. The method comprises the following steps: and dividing a scene into a plurality of sub-blocks according to the focusing depth, and refocusing by taking the center of each sub-block as an imaging center. And secondly, carrying out consistent motion compensation based on GPS measurement data aiming at each imaging center, namely carrying out rough compensation on envelope errors and phase errors of all target echo signals in a scene. Then the method is adopted to estimate the envelope error based on MD, carry out envelope error correction, and finally estimate and compensate the residual phase error by adopting PGA algorithm.
Description
Technical Field
The application relates to the technical field of radar signal processing, in particular to a high-resolution CSAR imaging method and device based on two-dimensional self-focusing.
Background
The circumferential synthetic aperture radar (Circular Synthetic Aperture Radar, CSAR) is a special mode Synthetic Aperture Radar (SAR), the CSAR realizes the synthetic aperture through the circular motion of the platform, different from the strip SAR observation geometry, the carrier platform moves along the circular track in the process of CSAR admission data, the wave beam always points to the center of an observation area, the accumulation time of an observation target is greatly prolonged, the omnibearing information of the target is obtained, and the detection area can be monitored for a long time. The three-dimensional imaging system has the advantages of omnibearing angle observation, high-resolution of wavelength level and three-dimensional imaging capability, and is widely applied to military use and civil use at present. Compared with the stripe SAR, the circular motion mode of the CSAR introduces serious azimuth and distance two-dimensional coupling, so that the partial SAR imaging algorithm is not applicable any more. The imaging algorithms currently applied to CSAR mainly include Back-Projection (BP) and polar formatting (Polar Format Algorithm, PFA). The time domain BP algorithm is suitable for any trajectory SAR imaging, however its computational effort is large, especially for high resolution large scenes. The frequency domain PFA algorithm is suitable for being applied to bunching SAR imaging, has no limitation on the motion track of a carrier, can be in linear motion or in curve motion, has higher operation efficiency compared with the BP algorithm and is easy to combine with a self-focusing algorithm, so that the PFA is widely applied to CSAR imaging.
Limited to GPS accuracy, PFA typically requires the use of a data-based self-focusing algorithm to compensate for residual motion errors after motion errors are compensated based on GPS measurement data. The existing self-focusing algorithm mainly comprises image shift (MD) and phase gradient self-focusing (PHASE GRADIENT Autofocus, PGA) and the like. The above-mentioned self-focusing algorithms all assume that the envelope error is smaller than a distance resolution unit and only correct the azimuth phase error. However, in high resolution SAR imaging, the distance resolution unit is small, and after correcting the system distance curvature by the imaging algorithm and performing motion compensation using GPS data, the residual motion error may still be larger than one distance resolution unit, which would result in the above-described self-focusing method being ineffective. Solving the above-mentioned problems requires the use of a two-dimensional self-focusing algorithm. The two-dimensional self-focusing algorithm is mainly divided into two types: the distance is reduced to resolution and the envelope is aligned. The distance resolution reducing method is to reduce the distance resolution to make the distance envelope error smaller than a coarse resolution distance unit, then estimate the azimuth phase error by the traditional self-focusing method, and then construct a distance envelope error compensation function by utilizing the relation between the azimuth phase error and the distance envelope error, correct the envelope error and realize high resolution imaging. The method has the problems of more iteration times and reduced selectable reference distance units. The envelope alignment method is to perform correlation processing along azimuth, realize envelope alignment, correct envelope errors, and then correct azimuth phase errors by using a traditional self-focusing method. The method has the problems of high requirement on the signal-to-noise ratio of the image and poor robustness. In the PFA algorithm, a plane wave assumption is adopted to introduce a phase error, so that the focusing depth is limited, and a block imaging method is generally adopted to solve the problem.
Disclosure of Invention
Based on the foregoing, it is necessary to provide a two-dimensional self-focusing-based high-resolution CSAR imaging method and device capable of focusing a scene to be imaged well.
A high resolution CSAR imaging method based on two-dimensional self-focusing, the method comprising:
Acquiring an original echo signal of a target to be imaged, which is recorded based on a CSAR radar, an imaging scene and positioning measurement data when the CSAR radar records the original echo signal, and preprocessing the original echo signal to obtain a first echo signal;
dividing the imaging scene into a plurality of sub-block scenes, constructing a compensation function according to the plurality of sub-block scenes and positioning measurement data, and performing coarse compensation of envelope errors and phase errors on the first echo signals by using the compensation function to obtain second echo signals;
Performing data interception on the second echo signal according to the size of the sub-block scene, and then performing two-dimensional interpolation to obtain a third echo signal;
After performing distance IFFT processing on the third echo signal, estimating a quadratic term phase error according to an MD algorithm, obtaining an envelope error according to the quadratic term phase error by utilizing the relation between the phase error and the envelope error, and correcting the third echo signal according to the envelope error to obtain a fourth echo signal;
Performing distance and azimuth FFT processing on the fourth echo signal to obtain coarse sub-block images corresponding to each sub-block scene, and performing phase error correction on each coarse sub-block image by using a PGA algorithm to obtain corrected coarse sub-block images;
and carrying out space-variant filtering on each corrected rough sub-block image to carry out image distortion correction, and then splicing to obtain a complete target image.
In one embodiment, the method comprises: the positioning measurement data are acquired by a positioning system arranged on the CSAR radar airborne platform.
In one embodiment, preprocessing the original echo signal to obtain a first echo signal includes:
And performing distance pulse pressure and distance FFT processing on the original echo signals to obtain the first echo signals.
In one embodiment, dividing the imaging scene into a plurality of sub-block scenes comprises: the imaging scene is divided into a plurality of sub-block scenes according to the depth of focus of the PFA algorithm.
In one embodiment, constructing the compensation function from the plurality of sub-block scenarios and the positioning measurement data includes: the compensation function is constructed from the positioning measurement data and the relative distance between the centers of the respective sub-block scenes.
In one embodiment, performing phase error correction on each coarse sub-block image by using a PGA algorithm to obtain a corrected coarse sub-block image includes:
and estimating the phase error of each coarse sub-block image by adopting a PGA algorithm, and correcting each coarse sub-block image according to the estimated phase error to obtain a corrected coarse sub-block image.
A high resolution CSAR imaging device based on two-dimensional focusing, the device comprising:
The data acquisition module is used for acquiring an original echo signal of a target to be imaged, which is recorded based on the CSAR, an imaging scene and positioning measurement data when the CSAR records the original echo signal, and preprocessing the original echo signal to obtain a first echo signal;
the envelope error and phase error coarse compensation module is used for dividing the imaging scene into a plurality of sub-block scenes, constructing a compensation function according to the plurality of sub-block scenes and positioning measurement data, and performing coarse compensation on the envelope error and the phase error of the first echo signal by utilizing the compensation function to obtain a second echo signal;
The two-dimensional interpolation module is used for carrying out data interception on the second echo signal according to the size of the sub-block scene and then carrying out two-dimensional interpolation to obtain a third echo signal;
The envelope error correction module is used for estimating a quadratic term phase error according to an MD algorithm after performing distance IFFT processing on the third echo signal, obtaining an envelope error according to the quadratic term phase error by utilizing the relation between the phase error and the envelope error, and correcting the third echo signal according to the envelope error to obtain a fourth echo signal;
The phase error correction module is used for carrying out distance and azimuth FFT processing on the fourth echo signal to obtain rough sub-block images corresponding to each sub-block scene, and carrying out phase error correction on each rough sub-block image by utilizing a PGA algorithm to obtain corrected rough sub-block images;
And the complete target image obtaining module is used for carrying out image distortion correction on each corrected rough sub-block image by adopting space-variant post-filtering and then splicing to obtain the complete target image.
A computer device comprising a memory storing a computer program and a processor which when executing the computer program performs the steps of:
Acquiring an original echo signal of a target to be imaged, which is recorded based on a CSAR radar, an imaging scene and positioning measurement data when the CSAR radar records the original echo signal, and preprocessing the original echo signal to obtain a first echo signal;
dividing the imaging scene into a plurality of sub-block scenes, constructing a compensation function according to the plurality of sub-block scenes and positioning measurement data, and performing coarse compensation of envelope errors and phase errors on the first echo signals by using the compensation function to obtain second echo signals;
Performing data interception on the second echo signal according to the size of the sub-block scene, and then performing two-dimensional interpolation to obtain a third echo signal;
After performing distance IFFT processing on the third echo signal, estimating a quadratic term phase error according to an MD algorithm, obtaining an envelope error according to the quadratic term phase error by utilizing the relation between the phase error and the envelope error, and correcting the third echo signal according to the envelope error to obtain a fourth echo signal;
Performing distance and azimuth FFT processing on the fourth echo signal to obtain coarse sub-block images corresponding to each sub-block scene, and performing phase error correction on each coarse sub-block image by using a PGA algorithm to obtain corrected coarse sub-block images;
and carrying out space-variant filtering on each corrected rough sub-block image to carry out image distortion correction, and then splicing to obtain a complete target image.
A computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of:
Acquiring an original echo signal of a target to be imaged, which is recorded based on a CSAR radar, an imaging scene and positioning measurement data when the CSAR radar records the original echo signal, and preprocessing the original echo signal to obtain a first echo signal;
dividing the imaging scene into a plurality of sub-block scenes, constructing a compensation function according to the plurality of sub-block scenes and positioning measurement data, and performing coarse compensation of envelope errors and phase errors on the first echo signals by using the compensation function to obtain second echo signals;
Performing data interception on the second echo signal according to the size of the sub-block scene, and then performing two-dimensional interpolation to obtain a third echo signal;
After performing distance IFFT processing on the third echo signal, estimating a quadratic term phase error according to an MD algorithm, obtaining an envelope error according to the quadratic term phase error by utilizing the relation between the phase error and the envelope error, and correcting the third echo signal according to the envelope error to obtain a fourth echo signal;
Performing distance and azimuth FFT processing on the fourth echo signal to obtain coarse sub-block images corresponding to each sub-block scene, and performing phase error correction on each coarse sub-block image by using a PGA algorithm to obtain corrected coarse sub-block images;
and carrying out space-variant filtering on each corrected rough sub-block image to carry out image distortion correction, and then splicing to obtain a complete target image.
According to the high-resolution CSAR imaging method and device based on the two-dimensional self-focusing, a scene is divided into a plurality of sub-blocks according to the focusing depth, and the center of each sub-block is used as an imaging center for refocusing. And secondly, carrying out consistent motion compensation based on GPS measurement data aiming at each imaging center, namely carrying out rough compensation on envelope errors and phase errors of all target echo signals in a scene. Then the method is adopted to estimate the envelope error based on MD, carry out envelope error correction, and finally estimate and compensate the residual phase error by adopting PGA algorithm, so that the focusing effect in the imaging result is better.
Drawings
FIG. 1 is a flow diagram of a high resolution CSAR imaging method based on two-dimensional self-focusing in one embodiment;
FIG. 2 is a schematic diagram of a geometric model of CSAR acquisition data in one embodiment;
FIG. 3 is a schematic diagram of a vehicle flight trajectory deviating from an ideal trajectory in one embodiment, wherein: (a) Representing a track plan view, (b) representing a track side view;
FIG. 4 is a schematic diagram of data truncation of echoes according to sub-block scene size in one embodiment;
FIG. 5 is a schematic diagram of estimating echo secondary phase error based on MD in accordance with an embodiment;
FIG. 6 is a block diagram of a practical operation algorithm of a high resolution CSAR imaging method according to another embodiment;
FIG. 7 is an optical image of measured data in an experiment;
FIG. 8 is a schematic diagram of the results of CSAR measured data processing in an experiment, wherein: fig. 8 (a) is a schematic diagram of a distance compression result after coarse compensation and polar coordinate formatted interpolation by using GPS measurement data, fig. 8 (b) is a schematic diagram of an envelope processed by the method, fig. 8 (c) is a schematic diagram of an imaging result after coarse compensation by using GPS measurement data, fig. 8 (d) is a schematic diagram of a result after correction by using GPS measurement data and PGA phase error but without envelope correction, fig. 8 (e) is a schematic diagram of a result after correction by using PGA algorithm by using the method, fig. 8 (f) is an enlarged view of a black frame part in fig. 8 (d), and fig. 8 (g) is an enlarged view of a black frame part in fig. 8 (e);
FIG. 9 is a schematic view of an experimental azimuth and distance section, wherein FIG. 9 (a) is a schematic view of an azimuth section, and FIG. 9 (b) is a schematic view of a distance section;
FIG. 10 is a schematic diagram of the result of estimating the envelope error by different methods in an experiment, wherein: fig. 10 (a) is a schematic diagram of a distance compression result after original polar coordinate formatted interpolation, fig. 10 (b) is an envelope error estimated by the present method, fig. 10 (c) is a schematic diagram of a result of compensating for distance compression by the envelope error estimated by the present method, fig. 10 (d) is an envelope error estimated by a distance-wise resolution reduction method, fig. 10 (e) is a schematic diagram of a result of compensating for distance compression by the envelope error estimated by a distance-wise resolution reduction method, fig. 10 (f) is an envelope error estimated by a sub-block PGA method, and fig. 10 (g) is a schematic diagram of a result of compensating for distance compression by the envelope error estimated by a sub-block PGA method;
FIG. 11 is a block diagram of a high resolution CSAR imaging device based on two-dimensional focusing in one embodiment;
Fig. 12 is an internal structural diagram of a computer device in one embodiment.
Detailed Description
The present application will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present application more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application.
As shown in fig. 1, there is provided a high resolution CSAR imaging method based on two-dimensional self-focusing, comprising the steps of:
Step S100, acquiring an original echo signal of a target to be imaged, which is recorded based on a CSAR radar, an imaging scene and positioning measurement data when the CSAR radar records the original echo signal, and preprocessing the original echo signal to obtain a first echo signal;
Step S110, dividing an imaging scene into a plurality of sub-block scenes, constructing a compensation function according to the plurality of sub-block scenes and positioning measurement data, and performing coarse compensation of envelope errors and phase errors on the first echo signal by using the compensation function to obtain a second echo signal;
Step S120, performing data interception on the second echo signal according to the size of the sub-block scene, and performing two-dimensional interpolation to obtain a third echo signal;
step S130, estimating a quadratic term phase error according to an MD algorithm after performing distance IFFT processing on the third echo signal, obtaining an envelope error according to the quadratic term phase error by utilizing the relation between the phase error and the envelope error, and correcting the third echo signal according to the envelope error to obtain a fourth echo signal;
step S140, performing distance and azimuth FFT processing on the fourth echo signal to obtain coarse sub-block images corresponding to each sub-block scene, and performing phase error correction on each coarse sub-block image by using a PGA algorithm to obtain corrected coarse sub-block images;
And step S150, performing space-variant post-filtering on each corrected rough sub-block image to perform image distortion correction, and then splicing to obtain a complete target image.
In step S100, positioning measurement data is acquired by a positioning system disposed on the CSAR radar airborne platform, so that a precise track of the CSAR radar, that is, a precise position of the CSAR radar, may be obtained, where the positioning system may employ a GPS system. The preprocessing of the original echo signal comprises the steps of performing distance pulse pressure and distance FFT processing on the echo signal to obtain the first echo signal.
Specifically, the SAR radar receives an original echo signal, performs distance pulse pressure and distance FFT on the original echo signal, and obtains an echo fundamental frequency signal of a target, that is, a first echo signal:
In the case of the formula (1), Representing the instantaneous pitch of the radar to the target, Is the vector form of the target point, T p is the aperture integration time.
In step S110, dividing the imaging scene into a plurality of sub-block scenes includes: the imaging scene is divided into a plurality of sub-block scenes according to the depth of focus of the PFA algorithm.
Specifically, as shown in FIG. 2, based on the geometric relationship of CSAR imaging, the method willAt/>Taylor expansion is carried out at the position to obtain:
In equation (2), R c is the vehicle flight radius, Φ 0 is the look-down angle, θ is the azimuth angle, and R HOT (θ) is the higher order term that introduces non-negligible phase and envelope errors when imaging a scene in close range large scenes. According to the higher-order phase error smaller than pi/4, the focus depth of PFA can be obtained as follows:
in formula (3), λ c is the wavelength, R 0 is the radial length with the imaging center as the origin, ρ a is the azimuth resolution, and R ref is the reference pitch, which is typically the distance of the radar from the imaging scene center.
Defocus due to higher order phase errors can be considered to have no effect on imaging when the imaging range is less than r 0, and scenes greater than r 0 can be defocused. Referring to fig. 2, a scene is divided into several sub-block scenes according to the size of r 0, and a point a (x a,ya) is a center point of any sub-block scene.
In this embodiment, constructing the compensation function from the plurality of sub-block scenarios and the positioning measurement data includes: the compensation function is constructed from the positioning measurement data and the relative distance between the centers of the respective sub-block scenes. The above-mentioned deduction process assumes that the airborne platform flies along an ideal track, and then the airborne platform cannot guarantee the ideal track due to the problems of airflow, flight attitude control and the like in the actual flying process, as shown in fig. 3, wherein fig. 3 (a) is a track top view, and fig. 3 (b) is a track side view. Thus, in the case of the imaging center and the actual track with the point a,Can be expressed as:
In equation 4, R a′(tm) is the instantaneous skew of the on-board channel to the center of the scene, phi 0 'is the actual depression angle, and θ' is the actual azimuth angle. The echo fundamental frequency signal s (f, t m;rp) of the target brought into the equation (4), that is, the equation (1), is obtained:
From the GPS measurement of the position of the airborne platform and the coordinates of point a (i.e. the central coordinates of each sub-block scene), a coarse compensation function can be constructed:
The envelope error and the phase error can be coarsely supplemented by multiplying the formula (6) with the echo fundamental frequency signal (formula (1)). However, limited by the accuracy of the positioning system measurement, residual motion errors still result in defocusing of the image, where the fundamental echo signal (i.e., the second echo signal) is represented as:
In equation (7), Δr (t m) is the residual motion error.
In step S120, since the imaging scene required for the sub-block image is smaller, the data can be truncated according to the sub-block image size before the two-dimensional interpolation, so as to reduce the redundant data amount and improve the operation efficiency.
Specifically, the echo baseband signal (second echo signal) is subjected to FFT along the distance and azimuth dimensions, respectively, to obtain the distance-doppler domain of the echo. As shown in fig. 4, the range of the skew (R min,Rmax) and the expression of the doppler bandwidth B s can be obtained according to the scene size:
and the echo data is truncated in the range-Doppler domain according to the range of the oblique distance and the Doppler bandwidth, so that the data volume is greatly reduced, and the operation efficiency is improved for the subsequent interpolation processing.
Furthermore, since the distance direction and the azimuth direction coordinates must be strictly monotonic and equally spaced when performing the two-dimensional interpolation operation, the echo signals need to be uniformly sampled to eliminate two-dimensional coupling, and the PFA algorithm converts the data of the polar coordinate distribution into rectangular distribution data through polar coordinate formatted interpolation, namely:
in formulas (9) and (10), k x and k y represent the post-conversion azimuth coordinate and the distance-wise coordinate, respectively.
From this, the second echo signal s (f, t m;rp) can be obtained, and the echo signal Ss (k x,ky;rp) after two-dimensional interpolation is:
in the formula (11) of the present invention, Representing the residual phase error after two-dimensional interpolation.
Next, taylor expansion of the second phase term in equation (11) at k y =0 yields:
In the formula (12) of the present invention, Thus equation (12) can be written as:
and then bringing the formula (13) into the formula (11) to obtain the following formula:
From the above, it can be seen that Is the residual azimuth phase error,/>Is residual envelop migration, and the following relationship exists between the residual envelop migration and the residual envelop migration:
In step S130, the envelope migration error may be obtained by estimating the phase error according to the relationship between the envelope migration error and the phase error. Since the echo traverses the range bin at this time, the self-focusing method cannot accurately estimate the phase error. Conventional two-dimensional self-focusing methods typically require pre-processing at this step, such as: reduced resolution and sub-aperture PGA. The resolution is reduced by combining a plurality of distance units into one distance unit, so that the phase error can be estimated by applying the self-focusing method. However, this method requires a number of iterations and the reduced resolution results in a significantly reduced number of reference distance units for estimating the phase error, thereby affecting the error estimation. The sub-aperture PGA divides the echo into a plurality of sub-apertures along the azimuth direction, estimates the phase error of each sub-aperture echo by using PGA, and finally combines the sub-aperture echoes together to obtain the phase error. However, the PGA cannot estimate the phase error of the term once, so that sub-image cross-correlation is required to be performed for merging before merging, and the method needs to be iterated for many times, which affects the operation efficiency. The MD adopted to estimate the phase error does not need pretreatment, so the method has the characteristics of simple operation and high efficiency. MD is a classical self-focusing method, which requires dividing the aperture into several sub-blocks when estimating the phase error, compared to PGA. Therefore, only proper sub-aperture size is selected, and the envelope is ensured not to cross the distance unit in the sub-aperture, so that the phase error can be estimated correctly. As shown in fig. 5, N sub-apertures are divided in the azimuth direction in the schematic diagram of the echo secondary phase error estimated based on MD, and the envelope does not span the distance unit within the sub-apertures. MD can only estimate the quadratic term phase error, which is the main component of the phase error and is also the main cause of envelope transition, so that the envelope migration can be solved after compensating the quadratic term error.
In the estimation, quadratic phase error is obtainedAnd then constructing an envelope error compensation function according to the relation between the phase error and the envelope error:
And multiplying the formula (16) with the formula (14) to realize the compensation of the envelope error and obtain a fourth echo signal after the envelope error correction.
In step S140, the envelope error corrected echo signal Ss (k x,ky;rp) (i.e., the fourth echo signal) is subjected to azimuth FFT to obtain a distance compression result:
In the formula (17) of the present invention, Is the residual phase error. The envelope error in the echo signal has been corrected in step S130, so that the residual phase error can be corrected using the conventional self-focusing method. PGA is a common self-focusing method, which is robust and can estimate any order of phase error.
In one embodiment, performing phase error correction on each coarse sub-block image by using a PGA algorithm to obtain a corrected coarse sub-block image includes: and estimating the phase error of each coarse sub-block image by adopting a PGA algorithm, and correcting each coarse sub-block image according to the estimated phase error to obtain a corrected coarse sub-block image.
In step S150, since the sub-block imaging can only solve the higher order term phase error in the plane wave approximation, the image distortion caused by the first order term phase error cannot be ignored, and therefore, it is also necessary to correct the image distortion by using SVPF.
In formula (18), (x p,yp) is the actual position of the target point, (x p',yp ') is the position in the PFA image, θ 0 ' is the azimuth angle of the carrier at the center of the sub-aperture in the point a being the origin of the coordinate system, Φ 0 ' is the pitch angle of the carrier at the center of the sub-aperture, and R a is the skew distance of the carrier at the center of the sub-aperture from point a. According to the above relation, image domain two-dimensional interpolation is adopted to correct image distortion.
And after all the sub-block images finish the steps, splicing according to the relative positions among the sub-block images to obtain a complete high-precision imaging result.
As shown in fig. 6, there is also provided a block flow diagram of an algorithm when actually operating according to the present method.
According to the high-resolution CSAR imaging method based on the two-dimensional self-focusing, after the envelope error and the phase error in the target echo signal are roughly compensated, the envelope error is estimated based on MD, envelope error correction is carried out, and finally the residual phase error is estimated and compensated by adopting PGA algorithm, so that the imaging result is well focused.
The actual CSAR data are used below, and comparative experiments are designed to demonstrate the effectiveness and superiority of the proposed algorithm.
In the experiment, high-resolution CSAR original data is recorded by a Ku band airborne radar, the bandwidth of a transmitting signal is 720MHz, the speed of the carrier is about 33m/s, the distance-wise theoretical resolution is 0.26m (without windowing), and the azimuth-wise theoretical resolution is about 0.3m (without windowing). As shown in fig. 7, for the optical image of measured data provided in this embodiment, the center of the imaging area is composed of 6 different types of vehicles.
Firstly, performing coarse compensation of phase errors and envelope errors based on GPS information, performing MD-based envelope error correction on two-dimensional polar coordinate formatted data, and finally estimating and compensating residual phase errors by adopting PGA. Fig. 8 (a) is an envelope diagram after the phase error and the envelope error are roughly compensated and the polar coordinates are formatted using only GPS information, and fig. 8 (b) is an envelope diagram processed by the method of the present invention. Due to motion errors and poor GPS measurement accuracy, the envelope in fig. 8 (a) is subject to curvature across the range bin. Obviously, the envelope curvature is corrected in fig. 8 (b). The envelope can be straightened by the method, which demonstrates the effectiveness of the method. Fig. 8 (c) is an imaging result of coarse compensation using only GPS data, and residual envelope errors and phase errors seriously affect focusing of the imaging result, so that the image looks blurred. Fig. 8 (d) shows the imaging result after the GPS data coarse compensation and PGA self-focusing compensation, and fig. 8 (e) shows the processing result of the imaging procedure using the present method. Fig. 8 (f) and 8 (g) are schematic views of the enlarged results of the framed portions of fig. 8 (d) and 8 (e), respectively, and it can be seen that focusing effect is good, particularly, focusing is good in the distance direction by the present method. To further compare the improvement of the focusing quality of the imaging results by the present method, the Long Bo lenses (circled) in fig. 8 (f) and 8 (g) were selected for azimuth and distance profile. Referring to fig. 9, the envelope correction front distance is severely defocused, while the estimation and compensation of the azimuth phase error by the self-focusing method is affected by the envelope curvature. The method can obtain the point target with good focusing along the distance direction and the azimuth direction, wherein the resolution of the distance direction is 0.28m, the resolution of the azimuth direction is 0.32m, and the theoretical resolution is satisfied.
To verify that MD-based envelope error correction has an efficiency improvement over conventional range-down resolution and sub-block PGA. The time of processing the echo data (envelope error estimation process only) by the different algorithms is shown in table one
Table one: each algorithm estimates envelope error time
As shown in fig. 10, by comparing fig. 10 (b), fig. 10 (d) and fig. 10 (f) can see that both the sub-aperture PGA method and the present method can well estimate the envelope error. However, the estimation accuracy of the range-down resolution is somewhat poor, mainly due to the reduced reference pitch that can be estimated by the resolution-down, affecting the error estimation. It can be seen from table one that the efficiency of the present method is highest.
It should be understood that, although the steps in the flowchart of fig. 1 are shown in sequence as indicated by the arrows, the steps are not necessarily performed in sequence as indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in fig. 1 may include multiple sub-steps or stages that are not necessarily performed at the same time, but may be performed at different times, nor do the order in which the sub-steps or stages are performed necessarily performed in sequence, but may be performed alternately or alternately with at least a portion of other steps or sub-steps of other steps.
In one embodiment, as shown in fig. 11, there is provided a high resolution CSAR imaging device based on two-dimensional focusing, comprising: a data acquisition module 200, an envelope error and phase error coarse compensation module 210, a two-dimensional interpolation module 220, an envelope error correction module 230, a phase error correction module 240 and a complete target image obtaining module 250, wherein:
the data acquisition module 200 is configured to acquire an original echo signal, an imaging scene, and positioning measurement data when the original echo signal is acquired by the CSAR radar, and perform preprocessing on the original echo signal to obtain a first echo signal;
the envelope error and phase error coarse compensation module 210 is configured to divide the imaging scene into a plurality of sub-block scenes, construct a compensation function according to the plurality of sub-block scenes and the positioning measurement data, and perform coarse compensation of the envelope error and the phase error on the first echo signal by using the compensation function to obtain a second echo signal;
the two-dimensional interpolation module 220 is configured to perform data interception on the second echo signal according to the size of the sub-block scene, and then perform two-dimensional interpolation to obtain a third echo signal;
The envelope error correction module 230 is configured to perform distance IFFT processing on the third echo signal, estimate a quadratic term phase error according to an MD algorithm, obtain an envelope error according to the quadratic term phase error by using a relationship between the phase error and the envelope error, and correct the third echo signal according to the envelope error to obtain a fourth echo signal;
the phase error correction module 240 is configured to perform distance and azimuth FFT processing on the fourth echo signal to obtain coarse sub-block images corresponding to each sub-block scene, and perform phase error correction on each coarse sub-block image by using a PGA algorithm to obtain corrected coarse sub-block images;
The complete target image obtaining module 250 is configured to perform image distortion correction on each corrected coarse sub-block image by using space-variant post-filtering, and then stitch the corrected coarse sub-block images to obtain a complete target image.
For specific limitations on the two-dimensional focusing-based high-resolution CSAR imaging device, reference may be made to the above limitation on the two-dimensional self-focusing-based high-resolution CSAR imaging method, and no further description is given here. The various modules in the above-described two-dimensional focus-based high-resolution CSAR imaging device may be implemented in whole or in part by software, hardware, and combinations thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.
In one embodiment, a computer device is provided, which may be a terminal, and the internal structure thereof may be as shown in fig. 12. The computer device includes a processor, a memory, a network interface, a display screen, and an input device connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a high resolution CSAR imaging method based on two-dimensional self-focusing. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, can also be keys, a track ball or a touch pad arranged on the shell of the computer equipment, and can also be an external keyboard, a touch pad or a mouse and the like.
It will be appreciated by those skilled in the art that the structure shown in FIG. 12 is merely a block diagram of some of the structures associated with the present inventive arrangements and is not limiting of the computer device to which the present inventive arrangements may be applied, and that a particular computer device may include more or fewer components than shown, or may combine some of the components, or have a different arrangement of components.
In one embodiment, a computer device is provided comprising a memory and a processor, the memory having stored therein a computer program, the processor when executing the computer program performing the steps of:
Acquiring an original echo signal of a target to be imaged, which is recorded based on a CSAR radar, an imaging scene and positioning measurement data when the CSAR radar records the original echo signal, and preprocessing the original echo signal to obtain a first echo signal;
dividing the imaging scene into a plurality of sub-block scenes, constructing a compensation function according to the plurality of sub-block scenes and positioning measurement data, and performing coarse compensation of envelope errors and phase errors on the first echo signals by using the compensation function to obtain second echo signals;
Performing data interception on the second echo signal according to the size of the sub-block scene, and then performing two-dimensional interpolation to obtain a third echo signal;
After performing distance IFFT processing on the third echo signal, estimating a quadratic term phase error according to an MD algorithm, obtaining an envelope error according to the quadratic term phase error by utilizing the relation between the phase error and the envelope error, and correcting the third echo signal according to the envelope error to obtain a fourth echo signal;
Performing distance and azimuth FFT processing on the fourth echo signal to obtain coarse sub-block images corresponding to each sub-block scene, and performing phase error correction on each coarse sub-block image by using a PGA algorithm to obtain corrected coarse sub-block images;
and carrying out space-variant filtering on each corrected rough sub-block image to carry out image distortion correction, and then splicing to obtain a complete target image.
In one embodiment, a computer readable storage medium is provided having a computer program stored thereon, which when executed by a processor, performs the steps of:
Acquiring an original echo signal of a target to be imaged, which is recorded based on a CSAR radar, an imaging scene and positioning measurement data when the CSAR radar records the original echo signal, and preprocessing the original echo signal to obtain a first echo signal;
dividing the imaging scene into a plurality of sub-block scenes, constructing a compensation function according to the plurality of sub-block scenes and positioning measurement data, and performing coarse compensation of envelope errors and phase errors on the first echo signals by using the compensation function to obtain second echo signals;
Performing data interception on the second echo signal according to the size of the sub-block scene, and then performing two-dimensional interpolation to obtain a third echo signal;
After performing distance IFFT processing on the third echo signal, estimating a quadratic term phase error according to an MD algorithm, obtaining an envelope error according to the quadratic term phase error by utilizing the relation between the phase error and the envelope error, and correcting the third echo signal according to the envelope error to obtain a fourth echo signal;
Performing distance and azimuth FFT processing on the fourth echo signal to obtain coarse sub-block images corresponding to each sub-block scene, and performing phase error correction on each coarse sub-block image by using a PGA algorithm to obtain corrected coarse sub-block images;
and carrying out space-variant filtering on each corrected rough sub-block image to carry out image distortion correction, and then splicing to obtain a complete target image.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (SYNCHLINK) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The above examples illustrate only a few embodiments of the application, which are described in detail and are not to be construed as limiting the scope of the application. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the application, which are all within the scope of the application. Accordingly, the scope of protection of the present application is to be determined by the appended claims.
Claims (7)
1. A high resolution CSAR imaging method based on two-dimensional self-focusing, the method comprising:
Acquiring an original echo signal of a target to be imaged, which is recorded based on a CSAR radar, an imaging scene and positioning measurement data when the CSAR radar records the original echo signal, and preprocessing the original echo signal to obtain a first echo signal;
dividing the imaging scene into a plurality of sub-block scenes, constructing a compensation function according to the plurality of sub-block scenes and positioning measurement data, and performing coarse compensation of envelope errors and phase errors on the first echo signals by using the compensation function to obtain second echo signals;
Performing data interception on the second echo signal according to the size of the sub-block scene, and then performing two-dimensional interpolation to obtain a third echo signal;
After performing distance IFFT processing on the third echo signal, estimating a quadratic term phase error according to an MD algorithm, obtaining an envelope error according to the quadratic term phase error by utilizing the relation between the phase error and the envelope error, and correcting the third echo signal according to the envelope error to obtain a fourth echo signal;
Performing distance and azimuth FFT processing on the fourth echo signal to obtain coarse sub-block images corresponding to each sub-block scene, and performing phase error correction on each coarse sub-block image by using a PGA algorithm to obtain corrected coarse sub-block images;
and carrying out space-variant filtering on each corrected rough sub-block image to carry out image distortion correction, and then splicing to obtain a complete target image.
2. The high resolution CSAR imaging method according to claim 1, wherein the method comprises: the positioning measurement data are acquired by a positioning system arranged on the CSAR radar airborne platform.
3. The high resolution CSAR imaging method according to claim 1, wherein preprocessing the raw echo signals to obtain first echo signals comprises:
And performing distance pulse pressure and distance FFT processing on the original echo signals to obtain the first echo signals.
4. The high resolution CSAR imaging method according to claim 1, wherein dividing the imaging scene into a plurality of sub-block scenes comprises: the imaging scene is divided into a plurality of sub-block scenes according to the depth of focus of the PFA algorithm.
5. The high resolution CSAR imaging method according to claim 4, wherein constructing a compensation function from a plurality of sub-block scenes and positioning measurement data comprises: the compensation function is constructed from the positioning measurement data and the relative distance between the centers of the respective sub-block scenes.
6. The method of claim 1, wherein performing phase error correction on each coarse sub-block image using a PGA algorithm to obtain a corrected coarse sub-block image comprises:
and estimating the phase error of each coarse sub-block image by adopting a PGA algorithm, and correcting each coarse sub-block image according to the estimated phase error to obtain a corrected coarse sub-block image.
7. A two-dimensional focusing-based high resolution CSAR imaging apparatus, the apparatus comprising:
The data acquisition module is used for acquiring an original echo signal of a target to be imaged, which is recorded based on the CSAR, an imaging scene and positioning measurement data when the CSAR records the original echo signal, and preprocessing the original echo signal to obtain a first echo signal;
the envelope error and phase error coarse compensation module is used for dividing the imaging scene into a plurality of sub-block scenes, constructing a compensation function according to the plurality of sub-block scenes and positioning measurement data, and performing coarse compensation on the envelope error and the phase error of the first echo signal by utilizing the compensation function to obtain a second echo signal;
The two-dimensional interpolation module is used for carrying out data interception on the second echo signal according to the size of the sub-block scene and then carrying out two-dimensional interpolation to obtain a third echo signal;
The envelope error correction module is used for estimating a quadratic term phase error according to an MD algorithm after performing distance IFFT processing on the third echo signal, obtaining an envelope error according to the quadratic term phase error by utilizing the relation between the phase error and the envelope error, and correcting the third echo signal according to the envelope error to obtain a fourth echo signal;
The phase error correction module is used for carrying out distance and azimuth FFT processing on the fourth echo signal to obtain rough sub-block images corresponding to each sub-block scene, and carrying out phase error correction on each rough sub-block image by utilizing a PGA algorithm to obtain corrected rough sub-block images;
And the complete target image obtaining module is used for carrying out image distortion correction on each corrected rough sub-block image by adopting space-variant post-filtering and then splicing to obtain the complete target image.
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