Showing papers by "Mengdao Xing published in 2014"

A 2-D Space-Variant Chirp Scaling Algorithm Based on the RCM Equalization and Subband Synthesis to Process Geosynchronous SAR Data

Abstract: A space-variant chirp scaling algorithm based on the range cell migration (RCM) equalization and azimuth subband synthesis has been studied to process simulated geosynchronous synthetic aperture radar (GEO-SAR) data. The acceptable order of terms in polynomials for the slant range models in the RCM correction and phase error compensation, division of subband, and suppression of grating lobes of the subbands was investigated. Qualitatively and quantitatively, the method was able to focus simulated GEO-SAR signals well. Finally, the constraint on the spatial extent of azimuth and range dimensions using the algorithm was assessed.

Sparse Apertures ISAR Imaging and Scaling for Maneuvering Targets

Abstract: —In advanced multifunctional radar, inverse syntheticaperture radar (ISAR) imaging of sparse apertures for maneuver-ingtargets isachallengeproblem. Ingeneral,the Dopplermodula-tion of rotation motion can be modeled as linear frequency foruniformly accelerated rotation targets, which is spatial-variant intwo-dimension (2-D). The signal diversity inherently reflects themaneuverability and provides a rationale of rotation motion esti-mation. In this paper, we focus on the problem of sparse aperturesISAR imaging and scaling for maneuvering targets. The maneu-vering signal model is formulated as chirp code and representedusingachirp-Fourierbasis.Thensparserepresentationisappliedtorealize range-Doppler (RD) imaging from the sparse apertures,where the superposition of chirp parameters is acquired using themodified discrete chirp Fourier transform (MDCFT). After pre-processing,suchassampleselection,rotationcenterdetermination,and noise reduction, the chirp parameters are used to estimate theparameters of rotation motion using the weighted least square(WLS) method. Finally, a high-resolution scaled-ISAR image isachieved by rescaling the acquired RD image using the estimatedrotation velocity. Experiments are performed to confirm the effec-tiveness of the proposal.Index Terms—Inverse synthetic aperture radar (ISAR),maneuvering targets, scaling, sparse apertures, sparserepresentation.

Multichannel HRWS SAR Imaging Based on Range-Variant Channel Calibration and Multi-Doppler-Direction Restriction Ambiguity Suppression

Abstract: In order to obtain high-resolution wide-swath (HRWS) images, the multichannel in azimuth synthetic aperture radar (SAR) system has been adopted to deal with the contradiction problem between high resolution and low pulse repetition frequency (PRF). In this paper, a novel channel-calibration method is proposed for the multichannel in azimuth HRWS SAR imaging system. During the channel calibration, the mismatch between the channels, which results from the gain-phase error and the range sampling time error, is first corrected by the coarse-calibration processing in the range frequency domain. Then, the along azimuth baseline measurement error is estimated. Considering the range variance in the residual phase error, the data are processed in blocks along the range time domain, and the error of every subblock data is estimated. After that, a fitting and filtering is implemented along the range to the estimated values of the phase error of all subblocks. The range-variant phase error is then compensated using their estimated values. After channel calibration, this paper also presents a new Doppler ambiguity suppression algorithm which nulls the ambiguity components in the Doppler domain. The newly proposed algorithm outperforms the post-Doppler ambiguity suppression algorithm. The airborne real measured scan synthetic aperture radar data, which are acquired by a seven-channel in azimuth SAR imaging system with the system working at X-band, are utilized to demonstrate the performance of the newly proposed channel-calibration method and the new Doppler ambiguity suppression algorithm.

Minimum-Entropy-Based Autofocus Algorithm for SAR Data Using Chebyshev Approximation and Method of Series Reversion, and Its Implementation in a Data Processor

Abstract: A novel autofocus method for synthetic aperture radar (SAR) image is studied. Based on a quadratic model for the phase error within each sub-area (narrow strip × sub-aperture) after a wide range swath is subdivided into narrow range strips and long azimuth aperture into sub-apertures, an objective function for estimation of the error is derived through the principle of minimum entropy. There is only one unknown variable in the function. With the Chebyshev approximation, the function is approximated as a polynomial, and the unknown is then solved using the method of series reversion. Curve-fitting methods are applied to estimate phase error for an entire scene of the full-swath by full-aperture. Through simulations, the proposed method is applied to restore the defocused SAR imagery that is well focused. The restored and original images are almost identical qualitatively and quantitatively. Next, the method is implemented into an existing SAR data processor. Two sets of SAR raw data at X- and Ku-bands are processed and two images are formed. Well-focused and high-resolution images from plain and rugged terrain are obtained even without the use of ancillary attitude data of the airborne SAR platform. Thus, the studied method is verified.

Phase adjustment and isar imaging of maneuvering targets with sparse apertures

Abstract: A multifunctional radar system can only acquire limited and discontinuous wideband pulses, which form sparse aperture (SA) observations of a target. To carry out radar activities (detection, tracking, and imaging) simultaneously for multiple targets, inverse synthetic aperture radar (ISAR) imaging exploiting these SA data is essential for multifunctional radar. In this paper, we study the phase adjustment and full-aperture (FA) reconstruction for SA-ISAR imaging of maneuvering targets. A modified eigenvector-based autofocus approach is proposed to correct phase errors within SA measurements of maneuvering targets. After phase correction, the FA data are reconstructed from SA measurements via sparse representation under a redundant chirp-Fourier dictionary. An efficient algorithm is developed to solve the sparse decomposition optimization, and ISAR images of the maneuvering target are obtained by adaptive joint time-frequency imaging approaches with the reconstructed data. Both simulated and real data sets are used to confirm the effectiveness of the proposed methods.

Polarimetric Target Decomposition Based on Attributed Scattering Center Model for Synthetic Aperture Radar Targets

Abstract: In this letter, a novel polarimetric target decomposition (PTD) method based on the attributed scattering center (ASC) model is proposed for man-made targets in synthetic aperture radar (SAR) images By extracting attributed parameters, polarimetric characteristics of targets can be exploited by performing PTD on the extracting parameters of ASCs instead of pixels in conventional PTD algorithms As a result, the integrity of target components is enhanced, leading to a reliable analysis on the polarimetric scattering mechanisms of SAR targets In the proposal, an attributed parameters extraction method based on joint exploitation of multiple polarimetric channels and a target discriminating method based on a constant-false-alarm threshold are developed to improve its robustness in strong noise scenarios Experimental results confirm the effectiveness of the proposed algorithm

Azimuth Resampling Processing for Highly Squinted Synthetic Aperture Radar Imaging With Several Modes

Abstract: The linear range walk yields a significant range-azimuth coupling effect in a highly squinted synthetic aperture radar (SAR). Although the linear range walk correction (LRWC) technique can effectively mitigate such coupling effect, it causes azimuth variation in the resulting signal and, as such, the so-called “azimuth-shift invariance” property becomes invalid. In order to eliminate the azimuth variation, a new spectrum processing approach based on azimuth resampling is proposed in this paper. After performing the LRWC, the azimuth resampling is carried out in the 2-D frequency domain and transforms the signal spectrum to be equivalent to that of a broadside SAR. For squinted beamsteering SAR (BS-SAR), e.g., spotlight SAR, sliding spotlight SAR, and Terrain Observation by Progressive Scans SAR, the azimuth resampling is combined with the azimuth signal reconstruction algorithm. As a result, both the azimuth variation, which is induced by the LRWC, and the aliasing, which is caused by antenna beam steering, can be avoided. Therefore, after the azimuth resampling, the squinted SAR data can be focused by exploiting a conventional broadside SAR imaging algorithm. An analysis of the motion error for airborne SAR data processing is also provided. Simulation and real data results show the effectiveness of the proposed algorithm.

An Azimuth Frequency Non-Linear Chirp Scaling (FNCS) Algorithm for TOPS SAR Imaging With High Squint Angle

Abstract: During the data acquisition of a squint terrain observation by progressive scan (TOPS) synthetic aperture radar (SAR), the steering of the antenna main beam increases the azimuth bandwidth and results in the azimuth signal aliasing in the Doppler domain. Besides, the range curvature and the Doppler frequency modulation (FM) rates after linear range walk correction are azimuth-variant for squint TOPS SAR. These problems may cause some difficulties for the SAR data processing. To deal with the problems, a new imaging algorithm for the squint TOPS SAR is introduced in this paper. After linear range walk correction, the azimuth preprocessing is implemented to achieve the two-dimensional frequency spectrum without aliasing. Then, utilizing a modified chirp scaling algorithm, we complete the range cell migration correction (RCMC) and range compression to the TOPS SAR data without subaperture. Finally, the frequency nonlinear chirp scaling (FNCS) is proposed to correct the variation of the FM rates and the azimuth signal is focused in the Doppler domain via the spectral analysis (SPECAN) method. Both simulation and real data results show the effectiveness of the proposed algorithm.

A Novel Moving Target Imaging Algorithm for HRWS SAR Based on Local Maximum-Likelihood Minimum Entropy

Abstract: For high-resolution wide-swath (HRWS) SAR based on multiple receive apertures in azimuth, this paper proposes a novel imaging approach for moving targets. This approach utilizes the wide bandwidth characteristics of the transmitted signal (multiple wavelengths) to estimate the moving target velocity. First, this paper explains that there is a phase mismatch (PM) between azimuth channels for the echo of a moving target, which depends on range frequency. In order to correct the PM, an algorithm based on local maximum-likelihood minimum entropy is proposed. The linear dependence of the PM on range frequency is employed to estimate the target velocity. Second, after the signal reconstruction in Doppler frequency and the compensation of the PM for a moving target, the estimated target velocity is utilized to implement the linear range cell migration correction and the Doppler centroid shifting. Then, the quadratic range cell migration is corrected by the keystone processing. After that, the focused moving target image can be obtained using the existing azimuth focusing approaches. Theoretical analysis shows that no interpolation is needed. The effectiveness of the imaging algorithm for moving targets is demonstrated via simulated and real measured ship HRWS ScanSAR data.

Deramp Space–Time Adaptive Processing for Multichannel SAR Systems

Abstract: This letter proposes a novel deramp space-time adaptive processing (Deramp-STAP) method for synthetic aperture radar (SAR) systems to achieve effective clutter suppression. Compared with the traditional STAP, the proposed method can overcome the spectral wrapping problem of a moving target from a Doppler shift. Furthermore, in the case of signal undersampling, the ambiguously focused position in azimuth for a moving target can be avoided by the proposed method. Moreover, the computational complexity can be drastically reduced because we only need to consider the baseband velocity of the moving target; here, the range of the baseband velocity is much smaller than that of the real target velocity, for clutter suppression in this method. Simulation results validate the effectiveness of the proposed algorithm.

Precise Cross-Range Scaling for ISAR Images Using Feature Registration

Abstract: This letter proposes a precise cross-range scaling algorithm for inverse synthetic aperture radar (ISAR) images by estimating the effective rotation angle through coordinate locations of feature points extracted from two sequenced subaperture ISAR images. In the approach, we first extract adequate feature points and feature descriptor vectors from these two images by scale-invariant feature transform and speeded-up robust features. Then, a two-stage registering scheme is employed to match these feature points to link the two images. Consequently, the effective rotation angle is efficiently and robustly estimated by evaluating a cost function based on the coordinate locations of the matched feature points. Experiments of simulated and real signals validate this proposal.

Squinted TOPS SAR Imaging Based on Modified Range Migration Algorithm and Spectral Analysis

Abstract: For the squinted terrain observation by progressive scans (TOPS) imaging mode, three problems need to be considered: azimuth spectrum aliasing, serious range–azimuth coupling, and azimuth time aliasing after range cell migration correction (RCMC). For these problems, a subaperture imaging algorithm based on the modified range migration algorithm (RMA) combined with spectral analysis (SPECAN) is proposed in this letter. Echo data are properly divided into subapertues so that the 2-D spectrum of each subaperture without aliasing can be obtained; then, the modified RMA is used to perform RCMC; finally, the signal is focused in the Doppler domain by SPECAN and deramping after subaperture recombination. Both simulated and real SAR data in the squinted TOPS mode are used to validate the proposed algorithm.

Analysis of three-component decomposition to compact polarimetric synthetic aperture radar

Abstract: The compact polarimetric (CP) synthetic aperture radar (SAR) data is directly decomposed into three canonical components involving surface, double-bounce and volume, which avoids the approximated quad-polarimetric reconstruction based on several promising assumptions. Through several algebraic operations, the three-component decomposition under CP modes ( π /4 mode and right circular transmit, linear receive (CTLR) mode) is deduced. With the experiments by using two classical data sets - San Francisco data from AIRSAR system and Oberpfaffenhofen data from ESAR system, the feasibility and flexibility of the CP decomposition are validated. Also, it has been found that the use of CP data can be further extended into many other polarimetric applications, and the three-component decomposition can achieve a better result with CTLR mode than with π /4 mode.

Sparse aperture inverse synthetic aperture radar imaging of manoeuvring targets with compensation of migration through range cells

Abstract: In inverse synthetic aperture radar (ISAR) imaging of a target with significant manoeuvres, severe migration through range cells (MTRCs) and time-varying Doppler usually involve in the echoed signal. Both of them may challenge the conventional motion compensation and imaging methods, which are usually based on the assumption of small rotational angle with short coherent time duration. Moreover, for a multi-functional ISAR, full aperture (FA) data collection might be unachievable because of the conflict with other radar activities, resulting in sparse aperture (SA) data. In this study, an ISAR imaging method of manoeuvring targets with SA data is proposed, where MTRC compensation and time-varying Doppler are well accounted. By using a sparse chirp-Fourier basis with first-order range–azimuth coupling term, an improved orthogonal match pursuit algorithm is implemented to solve the sparsity-driven optimisation for FA data reconstruction from SA-ISAR measurements. As a primary item, MTRC compensation is seamlessly embedded into the FA signal reconstruction for ISAR imaging of manoeuvring targets. Both simulated and real data are utilised to confirm the effectiveness of the proposed method.

Imaging of missile-borne bistatic forward-looking SAR

Abstract: As a special imaging mode, missile-borne bistatic forward-looking synthetic aperture radar (MBFL-SAR) has many advantages in two-dimensional (2-D) imaging capability for targets in the straight-ahead position over mono-static missile-borne SAR and airborne SAR. It is difficult to obtain the 2-D frequency spectrum of the target echo signal due to the high velocity and acceleration in this configuration, which brings a lot of obstacles to the following imaging processing. A new imaging algorithm for MBFL-SAR configuration based on series reversion is proposed in this paper. The 2-D frequency spectrum obtained through this method can implement range compression and range cell migration correction (RCMC) effectively. Finally, some simulations of point targets and comparison results confirm the efficiency of our proposed algorithm.

Super-resolution imaging algorithm based on attributed scattering center model

Abstract: Based on attributed scattering center, a novel algorithm of super-resolution synthetic aperture radar (SAR) imaging is proposed in this paper to characterize physical properties of the scattering object. An improved Orthogonal Matching Pursuit (OMP) algorithm is utilized to estimate the parameter of the simplified attributed scattering center model. To realize super-resolution, spectrum extrapolation is preformed in signal reconstruction based on the estimated model parameter. The method can accurately describe the physical structure compared with the traditional super-resolution algorithm based on the point scattering model. In addition, the method has fast computation efficiency and can achieve a better focusing performance with the utilization of the orientation angle. The simulation results validate the superiority of the proposed algorithm.

MIMO-Based Forward-Looking SAR Imaging Algorithm and Simulation

Abstract: Multiple-input multiple-output (MIMO) radar imaging can provide higher resolution and better sensitivity and thus can be applied to targets detection, recognition, and tracking. Missile-borne forward-looking SAR (MFL-SAR) is a new and special MIMO radar mode. It has advantage of two-dimensional (2D) imaging capability in forward direction over monostatic missile-borne SAR and airborne SAR. However, it is difficult to obtain accurate 2D frequency spectrum of the target echo signal due to the high velocity and descending height of this platform, which brings a lot of obstacles to imaging algorithm design. Therefore, a new imaging algorithm for MFL-SAR configuration based on the method of series reversion is proposed in this paper. This imaging method can implement range compression, secondary range compression (SRC), and range cell migration correction (RCMC) effectively. Finally, some simulations of point targets and comparison results confirm the efficiency of our proposed algorithm.

Property Analysis of MIMO-Based Missile-Borne Forward-Looking SAR

Abstract: As a special multiple-input multiple-output (MIMO) radar networking mode, missile-borne forward-looking synthetic aperture radar (MFL-SAR) has many potential applications. This paper describes and analyzes properties of this new configuration. Range history and Doppler history are analyzed and derived using the designed geometric configuration. Then the expressions of range and Doppler resolution are determined based on the validity of two-dimensional (2D) resolution imaging capability. To help to design the proper system and motion parameters of this configuration, key parameters affecting the imaging ability are found out. Due to high velocities and accelerations of both transmitter and receiver, high-order terms in the slant range equation should be kept to reduce the approximation error. The range resolution and Doppler resolution of MFL-SAR are both space-variant and time-variant owing to the complexity of this configuration. The tiny changes of 2D resolution during the synthetic aperture time should be considered when designing the imaging algorithm of MFL-SAR.

Stepped frequency synthetic preprocessing algorithm for inverse synthetic aperture radar imaging in fast moving target echo model

Abstract: This paper first introduces an accurate inverse synthetic aperture radar echo model for the fast moving targets. In this model, the target's motion during the time periods of the pulse transmitting, propagating and receiving have been taken into account, and some problems, which have been ignored in the `stop-go' model, may occur, for example, the varied ambiguity numbers and the drifted frequency centre. These problems will cause many difficulties in obtaining a high resolution range profile (HRRP) synthesis. To deal with these problems, a stepped frequency synthetic preprocessing (SFSP) algorithm is presented. The key of the proposed algorithm is synthetic preprocessing, including Doppler ambiguity suppression, echo coherence restoration and frequency centre correction, respectively. By completing the preprocessing, the HRRP can be achieved by a bandwidth synthesis and a well-focused image can be obtained by a keystone transform and an azimuth process, respectively. The simulation results validate the proposed SFSP algorithm by comparing it with the algorithm in the existing extended `stop-go' model.

Configuration study of missile-borne bistatic forward-looking SAR

Abstract: As a special bistatic SAR imaging mode, missile-borne bistatic forward-looking synthetic aperture radar (MBFL-SAR) has many potential applications in precision terminal guidance of missile. The properties of this new and special configuration are described and analyzed in this paper. Range history and Doppler history are analyzed and derived firstly, and then expressions of range and Doppler resolution are determined based on the gradient method. The key parameters affecting the imaging ability are found out to help to design the proper system and motion parameters of this configuration. The simulation results show that tiny changes of 2-D resolution during the synthetic aperture time should be considered when designing the imaging algorithm of MBFL-SAR.

3-D ghost imaging with microwave radar

Abstract: In this paper, we demonstrate a new three- dimensional (3-D) radar imaging mechanism borrowing the concept of optical ghost imaging (GI). High range resolution is achieved by transmitting wideband electromagnetic (EM) signal, while high resolution in the orthogonal plane is obtained by correlating the echoes with radar antenna's stochastically fluctuating radiation pattern which can be generated with a 2-D phased array. This new concept of radar imaging takes no advantage of relative motion between the target and radar platform. Moreover, by combining the compressive sensing (CS) theory, our proposed imaging system is capable of realizing super-resolution with fewer data samples. Numerical simulation is given to validate the proposal.

An Efficient Signal Reconstruction Algorithm for Stepped Frequency MIMO-SAR in the Spotlight and Sliding Spotlight Modes

Abstract: Multiple-input multiple-output (MIMO) synthetic aperture radar (SAR) using stepped frequency (SF) waveforms enables a high two-dimensional (2D) resolution with wider imaging swath at relatively low cost. However, only the stripmap mode has been discussed for SF MIMO-SAR. This paper presents an efficient algorithm to reconstruct the signal of SF MIMO-SAR in the spotlight and sliding spotlight modes, which includes Doppler ambiguity resolving algorithm based on subaperture division and an improved frequency-domain bandwidth synthesis (FBS) method. Both simulated and constructed data are used to validate the effectiveness of the proposed algorithm.

A Subaperture Imaging Algorithm to Highly Squinted TOPS SAR Based on SPECAN and Deramping

Abstract: As the azimuth beam sweeps at high squint angles, the real difficulty in processing high squinted terrain observation by progressive scans (TOPS) data is the azimuth spectrum aliasing of received signal and azimuth time aliasing after range cell migration correction (RCMC). For these problems, a subaperture imaging algorithm based on SPECAN and Deramping is proposed in this paper. Echo data is properly divided into subapertues so that azimuth spectrum without aliasing can be obtained; then the modified range migration algorithm (RMA), which can deal with the high squint case with low interpolation load, is used to perform RCMC; finally, the azimuth signal is focused in the Doppler domain by SPECAN and Deramping. To minimize the computation load of the proposed algorithm, the parameters used for SPECAN and Deramping should be accurately calculated. Point simulated SAR data in squinted TOPS mode are used to validate the effectiveness of the proposed algorithm.

OTHR Spectrum Reconstruction of Maneuvering Target with Compressive Sensing

Abstract: High-frequency (HF) over-the-horizon radar (OTHR) works in a very complicated electromagnetic environment. It usually suffers performance degradation caused by transient interference. In this paper, we study the transient interference excision and full spectrum reconstruction of maneuvering targets. The segmental subspace projection (SP) approach is applied to suppress the clutter and locate the transient interference. After interference excision, the spectrum is reconstructed from incomplete measurements via compressive sensing (CS) by using a redundant Fourier-chirp dictionary. An improved orthogonal matching pursuit (IOMP) algorithm is developed to solve the sparse decomposition optimization. Experimental results demonstrate the effectiveness of the proposed methods.

Transient interference excision and spectrum reconstruction with partial samples for over-the-horizon radar

Abstract: For target detection with sparsely sampled over-the-horizon radar (OTHR) signal, there are two major hassles puzzling its clutter and target Doppler spectrum reconstruction. On one hand, the OTHR signal is usually contaminated by transient interferences, which usually leads to a significant signal loss in its excision with conventional methods. On the other hand, the sparse OTHR signal will introduce serious grating-lobes in conventional Doppler analysis methods and thus degrade the performance of target detection. In this study, an integrate clutter and target spectrum reconstruction method for sparse OTHR signal are proposed. The proposed method contains two aspects. First, based on the sparse basis representation, a transient interference excision method is developed, which uses time-frequency modulated rectangle window basis to represent the OTHR signal in a sparse way to identify transient interferences. The second aspect lies in that, based on the compressive sensing, a spectrum reconstruction method is proposed to obtain the integrate clutter and target spectrum with sparse samples. By solving the Doppler sparsity constrained optimisation with greedy algorithms, the complete Doppler spectrum is recovered effectively for target detection. The performance of the authors proposal is validated by both simulation and real-measured data sets.

A subaperture imaging scheme for wide azimuth beam airborne SAR based on modified RMA with motion compensation

Abstract: Airborne SAR imaging processing needs to estimate motion error to compensate non-ideal trajectory. In this paper, a subaperture imaging scheme for wide azimuth beam airborne SAR systems is proposed. First, the motion error is estimated from the subaperture data and the modified range migration algorithm is applied to obtain the coarse focused image, whose azimuth resolution corresponds to the subaperture Doppler bandwidth. The subaperture image is then projected into a fine grid image, whose coordinates is defined by the imaging geometry. As the subaperture data stream is coming, the azimuth resolution of the grid image will become higher and higher. Finally, the fine image with the azimuth resolution corresponding to the full aperture data can be obtained. Since the motion error estimation is based on the sub-aperture data, the imaging processing is suitable for real-time SAR imaging.

A novel beam direction determination method for minimizing Doppler centroid in GEO SAR

Abstract: Due to the effects of the earth's rotation and the satellite's elliptical orbit, the Doppler centroid varies along the orbit in geosynchronous earth orbit synthetic aperture radar (GEO SAR). With an ultrahigh orbit height, the beam may illuminate outside the earth surface with a rotation angle large than 9 degrees. Therefore, the usual attitude steering methods to minimize the Doppler centroid in low earth orbit SAR (LEO SAR) may not be suitable for GEO SAR. Considering the above two effects of GEO SAR and the beam illuminating restriction, a beam determination method to minimize Doppler centroid in GEO SAR is proposed in this paper. Guaranteeing that the beam not illuminate outside the earth surface, the proposed method can drastically decrease the Doppler centroid and the equivalent squint angle.

An Azimuth Resampling based Imaging Algorithm for Highly Squinted Sliding Spotlight and TOPS SAR

Abstract: This paper focuses on the data processing of highly squinted sliding spotlight and Terrain Observation by Progressive Scans (TOPS) SAR and a novel azimuth resampling based imaging algorithm is proposed. After performing linear range walk correction (LRWC), azimuth convolution pre-processing is then performed to reconstruct the signal spectrum. A key step is to perform azimuth resampling in the two-dimensional frequency domain to eliminate the azimuth-variation induced by LRWC. As such, the data can be focused by exploiting a conventional broadside SAR imaging algorithm. Simulation and real data results show the effectiveness of the proposed algorithm.