Showing papers by "Mengdao Xing published in 2019"
TL;DR: A MOCO algorithm based on two-step accuracy improvement based on a prior-information-based-weighted least square (PI-WLS) to improve the accuracy of RD phase error estimation and Processing of airborne real data validates the effectiveness of the proposed algorithm.
Abstract: The motion compensation (MOCO) for the airborne SAR with ultrahigh resolution and wide swath is required to consider the range-dependent (RD) phase error. The RD phase error may cause an RD residual-range cell migration (RCM) after the correction of RCM, which can degrade the performance of phase gradient autofocus (PGA) when estimating the phase error. In addition, because the PGA estimation is based on the strong scattering point, it may wrongly estimate the phase error for some observation scenes without strong scattering point. Alternatively, to take into account the above two problems, we study a MOCO algorithm based on two-step accuracy improvement. In the algorithm, the first step is to estimate and correct the RD residual-RCM and thus improves the accuracy of PGA. The second step is to develop a prior-information-based-weighted least square (PI-WLS) to further improve the accuracy of RD phase error estimation. Processing of airborne real data validates the effectiveness of the proposed algorithm.
39 citations
TL;DR: A frequency imaging algorithm based on an optimal linear range walk correction (LRWC) preprocessing and 2-D singular value decomposition (SVD) is studied to correct the azimuth-variance in curved trajectory spaceborne SAR and achieves the accurate range cell migration correction.
Abstract: The curved trajectory can lead to severely 2-D spatial-variance in spaceborne synthetic aperture radar (SAR). The azimuth-variance makes the traditional frequency domain imaging algorithms for the straight trajectory based on the assumption of azimuth translational invariance invalid. To correct the severely 2-D spatial-variance in curved trajectory spaceborne SAR, this paper studies a frequency imaging algorithm based on an optimal linear range walk correction (LRWC) preprocessing and 2-D singular value decomposition (SVD). Before the correction of the 2-D spatial-variance, an optimal LRWC preprocessing is introduced to minimize the azimuth-variance. Subsequently, a range block-SVD is proposed to correct the range-variance and, thus, achieves the accurate range cell migration correction. Finally, the azimuth tandem-SVD method is used to correct the azimuth-variance and, thus, accomplishes the azimuth compression for the whole azimuth scene. Processing of the simulated data validates the effectiveness of the proposed algorithm.
21 citations
TL;DR: A modified Stolt mapping method along with a modified joint time and Doppler resampling (JTDR) for highly squinted MEO SAR data processing is proposed and simulation results are shown to verify the effectiveness of the developed focusing approaches.
Abstract: A squinted observation geometry along with long integration time significantly aggravates the range walk and spatial variation of a medium-earth-orbit (MEO) synthetic aperture radar (SAR) signal. Variable pulse repeating frequency (PRF) is recommended to avoid the blockage in echo recording and save storage space. The existing wavenumber algorithms cannot handle the nonlinear and range–azimuth-coupled spatial variation (RACSP) over a large scene. In this paper, we propose a modified Stolt mapping method along with a modified joint time and Doppler resampling (JTDR) for highly squinted MEO SAR data processing. An azimuth timescale transformation is used to deal with the nonlinear spatial variation of the azimuth frequency-modulation (FM) rate. An extended Omega-K is used to linearize the range frequency and achieve range cell migration correction (RCMC). To address the RACSP, the Doppler is linearized in the range-Doppler domain using a range-dependent Doppler scale transformation. The computational complexity and geometry distortion correction (GDC) are also discussed. Simulation results are shown to verify the effectiveness of the developed focusing approaches.
19 citations
TL;DR: A refined algorithm based on the two-stage programming MB PU approach (TSPA), which improves the performance of stage 1 of TSPA through assuming terrain height surface in the neighborhood pixels can be approximated by a plane to combine more information of the interferometric phase in the local region to estimate the ambiguity number gradient.
Abstract: The problem of phase unwrapping (PU) in synthetic aperture radar (SAR) interferometry (InSAR) is caused by the measured range differences being ambiguous with the wavelength. Therefore, multi-baseline (MB) is a key processing step of MB InSAR. Compared with the traditional single-baseline (SB) PU, MB PU is advantageous in solving steep terrain due to its ability to break through the constraint of the phase continuity assumption. However, the accuracy of most of the existing MB PU methods is still limited to its mathematical foundation, i.e., the Chinese remainder theorem (CRT) is too sensitive to measurement bias. To solve this issue, this paper presents a refined algorithm based on the two-stage programming MB PU approach (TSPA) proposed by H. Yu. The significant advantage of the refined TSPA method (abbreviated as LPM-TSPA) is that it improves the performance of stage 1 of TSPA through assuming terrain height surface in the neighborhood pixels can be approximated by a plane to combine more information of the interferometric phase in the local region to estimate the ambiguity number gradient. The experiment results indicate that the LPM-TSPA method can significantly improve the accuracy of the MB PU solution.
18 citations
TL;DR: In this paper, a novel ISAR imaging and a cross-range scaling algorithm for a maneuvering target with a non-uniform rotation are proposed and the spatially variant phase error is compensated for by the joint phase error compensation method based on nonlinear chirp scaling (NCS) principle.
Abstract: The azimuth resolution of an inverse synthetic aperture radar (ISAR) image is determined by the angular diversity of the target. In order to improve the azimuth resolution of an ISAR image, it is necessary to view the target at more different aspect angles, which is commonly achieved by extending the coherent processing interval (CPI). However, as the CPI lengthens, the effective rotation of a target can no longer be approximated to be uniform and the rotational acceleration should be taken into consideration. The non-uniform rotation can bring about the 2-D space-variant phase error, which degrades the focusing quality of an ISAR image seriously. In this paper, a novel ISAR imaging and a cross-range scaling algorithm for a maneuvering target with a non-uniform rotation are proposed. In the proposed algorithm, the spatially variant phase error is compensated for by the joint phase error compensation method based on nonlinear chirp scaling (NCS) principle. The estimation of the effective rotational information required in the NCS-based joint phase error compensation method and the cross-range scaling is transformed into a nonlinear least-squares (NLS) problem. The NLS problem is solved by Gauss–Newton method and FFTs with high efficiency. The results acquired from the processing of both the simulation and real data validate the effectiveness of the proposed algorithm.
15 citations
TL;DR: A novel azimuth Doppler signal reconstruction algorithm is developed based on an equivalent baseline approximating in the azIMuth Doimuth chirp Fourier transform domain for the GEO-LEO bi-static multi-channel HRWS SAR system.
Abstract: For the geosynchronous-low earth orbit (GEO-LEO) bi-static multi-channel high-resolution and wide-swath synthetic aperture radar (HRWS SAR) system, a novel azimuth Doppler signal reconstruction algorithm is developed based on an equivalent baseline approximating in the azimuth Doppler chirp Fourier transform domain. The main difficulty for the GEO-LEO bistatic multi-channel HRWS SAR system is that the baseline is variant with the scene in the conventional Doppler Fourier transform domain during azimuth signal reconstruction. The developed approach first employs the linear range cell migration correction and chirp Fourier transform to obtain the coarse-focused ambiguity SAR image. More importantly, the baseline component can be approximated a uniform baseline length for the whole image scene and the ambiguous Doppler spectrum can be reconstructed using the available Doppler signal reconstruction approach. Finally, the experimental results for a simulation GEO-LEO bi-static multi-channel HRWS SAR system are employed to validate the theoretical investigations and the proposed approach.
14 citations
TL;DR: A new fast factorized back projection based on orthogonal elliptical polar (OEP) coordinate is proposed for BFSAR imaging, and a new wavenumber decomposition-based strategy is presented to reveal two-dimensional Nyquist sample requirement without complicated calculation and mathematical derivation, which makes the FFBP process much more easier to design.
Abstract: Due to the flexible bistatic configuration and complicated moving trajectory of radar platform, time-domain algorithms have significant focusing performance advantages for bistatic forward-looking synthetic aperture radar (BFSAR) applications. In this paper, a new fast factorized back projection (FFBP) based on orthogonal elliptical polar (OEP) coordinate is proposed for BFSAR imaging. Owing to the orthogonality of OEP system, the spectrum of BFSAR subimages can be compacted into the narrowest range and very low Nyquist sampling rate can be utilized in FFBP recursion. Comparing with the conventional FFBP based on original elliptical polar coordinate, the proposed OEP-based algorithm has prominently reduced burden in computation, especially for the BFSAR cases with large baseline geometry. Moreover, a new wavenumber decomposition-based strategy is presented to reveal two-dimensional Nyquist sample requirement without complicated calculation and mathematical derivation, which makes the FFBP process much more easier to design. Promising results from simulations and raw data experiments are presented to validate the advantages of the proposed algorithm.
10 citations
TL;DR: This paper investigates the imaging problems in squint beam-steering synthetic aperture radar (SBS-SAR) mounted on high-speed platforms with constant acceleration by derotation and phase compensation, and finds that the KT of Doppler folded signal is achieved without zero-padding.
Abstract: This paper investigates the imaging problems in squint beam-steering synthetic aperture radar (SBS-SAR) mounted on high-speed platforms with constant acceleration. The cross-range-dependent range cell migration (RCM) is compensated by keystone transform (KT) and time domain RCM correction (RCMC). By derotation and phase compensation, the KT of Doppler folded signal is achieved without zero-padding. For azimuth processing, the signal is reconstructed by the nonlinear phase and range-dependent derotation. Then, the space-variant (SV) Doppler chirp rate is corrected by time domain azimuth nonlinear chirp scaling (ANCS). After frequency domain matched filtering, the full aperture signal is focused in the 2-D time domain. The algorithm is validated by simulated SAR data, including the evaluation of RCMC with KT, geometric correction, and the focusing performance.
10 citations
TL;DR: A fast time-domain imaging and corresponding autofocus method based on the hybrid coordinate (HC) system is proposed that has good robustness and universality, and a 3-D trajectory deviation estimation methodbased on Gauss–Newton iteration is investigated for the motion compensation in the HC system.
Abstract: Compared with frequency-domain algorithms, time-domain algorithms (TDAs) can achieve image focusing under the conditions of arbitrary trajectories and large integration angles. However, the interpolations in both range and bearing angle directions are required in the coordinate transformation of fast TDAs, which inevitably increases the computational load and introduces interpolation errors. In this paper, a fast time-domain imaging and corresponding autofocus method based on the hybrid coordinate (HC) system is proposed. First, the interpolation operation is optimized in the process of fast TDAs. It transforms the 2-D interpolation into 1-D interpolation only in the bearing angle direction, which improves the execution efficiency and reduces the interpolation error. Next, a 3-D trajectory deviation estimation method based on Gauss–Newton iteration is investigated for the motion compensation in the HC system. By iterative optimization, the 3-D motion errors during the flight are estimated accurately, and the space-variant phase error is compensated precisely. This method has good robustness and universality. Simulation results and real data processing demonstrate the effectiveness and the practicability of the method presented in this paper.
10 citations
01 Jul 2019
TL;DR: CCFLS uses the clustering phenomenon of the MB residues to generate the convex hull of residues set with balance polarity, and avoids spending the computation resources on the area within the conveX hull, so that the high-precision PU solution can be quickly obtained.
Abstract: For the multibaseline (MB) synthetic aperture radar (SAR) interferometry (InSAR), MB phase unwrapping (PU) is an important step. With the rapid development of MB InSAR, the size of the datasets from the MB InSAR system is becoming increasingly larger. Under the situation of "bigdata", MB PU may face new problems with insufficient computing resources, or take too much running time to get the PU result. In order to deal with such case, we propose a convex hull and cluster-analysis based fast large-scale MB PU method (CCFLS) with enlightened by the single baseline (SB) PU method (CHFLS) from H. Yu [1]. CCFLS uses the clustering phenomenon of the MB residues to generate the convex hull of residues set with balance polarity, and avoids spending the computation resources on the area within the convex hull, so that the high-precision PU solution can be quickly obtained. The theoretical analysis and experiment results indicate that CCFLS can effectively reduce memory consumption and calculation time.
7 citations
01 Nov 2019
TL;DR: A imaging passive localization method for wideband signal by introducing synthetic aperture radar (SAR) imaging method, the location of the signal emitter is directly given in SAR image to focus unknown wideband data in range and azimuth domain.
Abstract: A imaging passive localization method for wideband signal is proposed in this paper. By introducing synthetic aperture radar (SAR) imaging method, the location of the signal emitter is directly given in SAR image. The key of this method is to focus unknown wideband data in range and azimuth domain. To focus the data in range domain without signal parameter, a new pulse compress method is proposed by constructing reference signal from raw data. To focus the data in azimuth domain without knowing range, a range-searching azimuth focus method is proposed by constructing azimuth focus functions with different range. Simulation result validate the effectiveness of the proposed method.
TL;DR: A novel sidelobe-suppression algorithm based on modified Spatial Variant Apodization (SVA) technique connected with CS theory is proposed and the simulation shows that the sidelobes of the signal can be suppressed as low as −34 dB without losing resolution.
Abstract: A novel sidelobe-suppression algorithm is proposed according to the problem of sidelobe in the real data of airborne Synthetic Aperture Ladar (SAL) imaging. Compression Sensing (CS) theory is proposed to recover a sparse signal as well as to suppress the sidelobe of the signal. However, the SAL images are not sparse in a general way. To solve such a problem, a novel sidelobe-suppression algorithm based on modified Spatial Variant Apodization (SVA) technique connected with CS theory is proposed. Firstly, the sparsification of SAL images can be achieved by using the modified SVA algorithm, which deals with not only the linear but also the non-linear sampling situations. And then, the sidelobe-suppression can be achieved by recovery processing using the CS algorithm. Finally, the simulation shows that the sidelobes of the signal can be suppressed as low as −34 dB without losing resolution. Meanwhile, the real data result proves the validity of the proposed algorithm.
TL;DR: This paper proposes a new method for multi-perspective 3D reconstruction and single perspective instantaneous target attitude estimation and results have proved the effectiveness and robustness of the proposed method.
Abstract: Due to the limited information of two-dimensional (2D) radar images, the study of three-dimensional (3D) radar image reconstruction has received significant attention. However, the target attitude obtained by the existing 3D reconstruction methods is unknown. In addition, using a single perspective, one can only get 3D reconstruction result of a simple target. For a complex target, due to occlusion and scattering characteristics, 3D reconstruction information obtained from a single perspective is limited. To tackle the above two problems, this paper proposes a new method for multi-perspective 3D reconstruction and single perspective instantaneous target attitude estimation. This method consists of three steps. First, the result of 3D reconstruction with unknown attitude is obtained by the traditional matrix factorization method. Then, in order to obtain the attitude of a target 3D reconstruction, additional constraints are added to the projection vectors which are computed from the matrix factorization method. Finally, the information from different perspectives are merged into a single layer information according to certain rules. After the information fusion, a multi-perspective 3D reconstruction structure with better visibility and more information is obtained. Simulation results have proved the effectiveness and robustness of the proposed method.
TL;DR: The 3D reconstruction of high-rise buildings using the wrapped InSAR phase image was studied, referring to the geometric modulation in very high resolution (VHR) SAR images, such as serious layover cause by high- rise buildings.
Abstract: The great development of high-resolution SAR system gives more opportunities to observe building structures in detail, especially the advanced interferometric SAR (InSAR), which techniques attract more attention on exploiting useful information on urban infrastructures. Considering that the high-rise buildings in urban areas are quite common in big cities, it is of great importance to retrieve the three-dimension (3D) information of the urban high-rise buildings in urban remote sensing applications. In this paper, the 3D reconstruction of high-rise buildings using the wrapped InSAR phase image was studied, referring to the geometric modulation in very high resolution (VHR) SAR images, such as serious layover cause by high-rise buildings. Under the assumption of a rectangular shape, the high-rise buildings were detected and building facades were extracted based on the local frequency analysis of the layover fringe patterns. Then 3D information of buildings were finally extracted according to the detected facade geometry. Except for testing on a small urban area from the TanDEM-X data, the experiment carried on the single-pass InSAR wrapped phase in the wide urban scene, which was collected by the Chinese airborne N-SAR system, also demonstrated the possibility and applicability of the approach.
TL;DR: In this article, a joint scheme to reconstruct the high-resolution images and estimate the rotational parameters for non-uniformly rotating targets was proposed, which not only improves the image resolution but also reduces the noise.
Abstract: Generally, the inverse synthetic aperture radar images can be generated under the supposition that the targets rotate uniformly during a short observation. Some common methods functioning in this paper are then limited on image resolution and even have utter failure when the targets have more complex motions. In practical applications, it is difficult but significant to develop effective techniques of imaging and identification for maneuvering targets. To this end, this paper proposes a joint scheme to reconstruct the high-resolution images and estimate the rotational parameters for non-uniformly rotating targets. The electromagnetic images can be retrieved in the matched Fourier transform domain rather than Fourier plane, which also present great sparsity. Under the frame of compressive sensing, the rotational parameters and high-resolution image are solved alternately, during which the basis is determined by the parameters. This approach not only improves the image resolution but also reduces the noise. In addition, the enhanced image can further be cross-range scaled with the estimated rotational rate. The numerical results confirm the performance of the proposed method.
TL;DR: Simulation results validate the effectiveness of the proposed range model together with the imaging algorithm, and the modified Omega-K algorithm with improved range model with range-independent error compensation is proposed.
TL;DR: A new robust SAR platform positioning method based on the improved Gauss–Newton–genetic hybrid (GNGH) algorithm that can reduce the computation load and positioning error dramatically and is confirmed and demonstrated via simulation and experimental results.
Abstract: The traditional synthetic aperture radar (SAR) platform positioning methods based on the range-Doppler domain data, velocity and altitude information of the platform exist a large approximation error, which will not satisfy the requirement of accurate navigation. Additionally, the traditional positioning methods for solving non-linear equations are challenging due to the risk of falling into local optimal solution. In order to solve these problems, a new robust SAR platform positioning method based on the improved Gauss–Newton–genetic hybrid (GNGH) algorithm is proposed in this study. First, the position information of multi-feature points in geographic and imaging coordinate systems is acquired by adopting the image matching. Furthermore, the coordinate transformation is introduced to realise the uniform of feature point coordinates between the different coordinate systems. Finally, the accurate position of the platform is calculated through introducing GNGH algorithm to solve the non-linear equations constructed by the corresponding slant range information. So the trajectory deviation can be corrected effectively. Moreover, the proposed method can reduce the computation load and positioning error dramatically. The effectiveness of the proposed approach is confirmed and demonstrated via simulation and experimental results.
01 Nov 2019
TL;DR: A method to extract moving target signal in time-frequency domain is proposed and the moving target's signature will be isolated by the different frequency characteristics between clutter and target.
Abstract: Moving target detection is still a challenge in single channel synthetic aperture radar (SAR). Clutter suppression is the key to detect moving target in SAR image. To achieve good performance of clutter suppression, we propose a method to extract moving target signal in time-frequency domain. Firstly, the signal after range compression is transformed into time-frequency domain. Secondly, moving target's signature will be isolated by the different frequency characteristics between clutter and target. Finally, the moving target signal in range compressed and azimuth time domain can be obtained. The experiment in this paper is used to validate the effectiveness of proposed method.
01 Jul 2019
TL;DR: It’s found that scatters distributed on a 3D oscillatory target cannot be focused uniformly on a predefined imaging plane (IP), and the projection relationship of the target focusing positions on the slant-range plane (SRP) and the IP are derived.
Abstract: Ship oscillatory motions with long coherence processing interval (CPI) are complex and hard to accurately estimate. The traditional ship imaging methods usually avoid long-CPI focusing by dealing with a short observation time interval, which may make it hard to obtain a high-resolution and high-SNR image. In this paper, the mechanisms and challenges of long CPI imaging of oscillatory targets are investigated. The properties of wavenumber domain support (WDS) and point spreading function (PSF) of oscillatory targets are analyzed. It’s found that the WDS spreads as a three-dimensional (3D) thin and curved sweep surface, with time-variant energy density, non-parallel boundaries and a complex structure. The PSF of an oscillatory target has a 3D resolution, but also multiple side-lobes with high level. We inspect the relationships between the properties of the WDS and the non-ideal PSF. Moreover, it’s found that scatters distributed on a 3D oscillatory target cannot be focused uniformly on a predefined imaging plane (IP). The projection relationship of the target focusing positions on the slant-range plane (SRP) and the IP are also derived. The simulation results can well validate the proposed method.
TL;DR: A novel method to estimate the scaling factor by optimizing the image quality by using Matching Fourier Transform (MFT), which coincides with the non-uniform rotation model or the variant Doppler.
TL;DR: An effective method combining correlation matching and beam pointing is proposed and the effectiveness of the proposed method is verified by using mooring test-fly and real flight data.
Abstract: Target identification is a challenging task under land backgrounds for the millimeter wave (MMW) seeker, especially under complex backgrounds. Focusing on the problem, an effective method combining correlation matching and beam pointing is proposed in this paper. In the beginning, seeker scanning for target detection is conducted in two rounds, and target information of the detected targets is stored for correlation matching. Point or body feature judgment is implemented by using high resolution range profile (HRRP). Then, the error distribution zone is constructed with the beam pointing as the origin. In the end, we identify the target by searching the one which lies in the closest error distribution from the beam pointing center. The effectiveness of the proposed method is verified by using mooring test-fly and real flight data.
TL;DR: A modified RCMC method is proposed which removes the space-variant range cell migration (RCM) components by deramp-keystone transform and then compensates the unified RCM terms in the time domain and can avoid zero-padding.
Abstract: The focusing of squint beam-steering synthetic aperture radar (SAR) data is a challenging task for the technical difficulty of space-variant range cell migration correction (RCMC). It is more complicated when considering the manoeuver of high-speed platforms. The conventional Doppler domain RCMC method is with low performance and requires a large amount of zero-padding. This Letter proposes a modified RCMC method which removes the space-variant range cell migration (RCM) components by deramp-keystone transform and then compensates the unified RCM terms in the time domain. Compared with the conventional method, the proposed one is with high performance and can avoid zero-padding. This method is validated by the simulated SAR data.
01 Jul 2019
TL;DR: The Homotopy re-weighted ℓ1-norm minimization is applied to ISAR imaging and is able to choose the accurate regularization parameter for each point in ISAR image with high efficiency.
Abstract: A suitable regularization parameter plays an important role in sparse ISAR imaging algorithms. With a proper regularization parameter, the quality of ISAR images improves. In this paper, the Homotopy re-weighted l1-norm minimization is applied to ISAR imaging. This method is able to choose the accurate regularization parameter for each point in ISAR image with high efficiency. As a result, the imaging results processed by this method contain more details of the target and less artificial points. Both simulated and real data experiments validate the feasibility of the proposed method.
01 Nov 2019
TL;DR: A new nonlinear chirp scaling (NCS) imaging algorithm that using frequency focusing position to remove spatially variability of Doppler parameters is proposed.
Abstract: With more flexibility and higher generality, translational variant BFSAR has extensive potential applications in self-handing and navigation. However, the current BFSAR imaging algorithms mostly focus on bistatic configuration without velocity of altitude which would product azimuth position error. In this paper, we propose a new nonlinear chirp scaling (NCS) imaging algorithm that using frequency focusing position to remove spatially variability of Doppler parameters. Finally, simulation results further validate the effectiveness of the method.
01 Jul 2019
TL;DR: A novel ionospheric TEC estimation method base on L-band inverse synthetic aperture radar (ISAR) signal processing, which is a two-step strategy, validates the robustness and effectiveness of the proposed method.
Abstract: The refraction, dispersion and reflection will occur when electromagnetic wave passing through the ionosphere, which affects the human activities of aerospace investigation and the earth environmental remote sensing severely. The total electron content (TEC) is a key to evaluate the ionosphere. This paper proposes a novel ionospheric TEC estimation method base on L-band inverse synthetic aperture radar (ISAR) signal processing, which is a two-step strategy. The coarse estimation of the first step is achieved by coherently integrated modified cubic phase function and the accurate estimation of the second step is accomplished by a minimum entropy optimization function solved by particle swarm optimization. The results of processing the simulated and measured data validate the robustness and effectiveness of the proposed method.
01 Nov 2019
TL;DR: In this article, a new optimized selection method of beam position parameters for spaceborne synthetic aperture radar (SAR) is proposed, which meets the principles of PRF restriction and maximum observation band width.
Abstract: In this paper, a new optimized selection method of beam position parameters for spaceborne synthetic aperture radar(SAR) is proposed. Aiming at the difficulty in selecting pulse repeatition frequency (PRF) and observation band width in spaceborne SAR beam position design, this paper deduces the iterative relationship between adjacent beam positions in detail from the spaceborne SAR beam geometry, and proposes an automatic optimization and selection method for beam position parameters. The proposed method meets the principles of PRF restriction and maximum observation band width. The PRF and observation band width of one beam position can be optimized and selected at the same time, and the next beam position parameters can be automatically iteratively selected according to the current selection result. Simulation results validate the effectiveness of the proposed method.
01 Jul 2019
TL;DR: This paper proposes an imaging algorithm for high squint beam steering (HS-BS) SAR platforms with constant acceleration with good performance and high efficiency using the baseband azimuth scaling (BAS) method.
Abstract: To meet the demand for large area environment monitoring during short synthetic aperture time, this paper proposes an imaging algorithm for high squint beam steering (HS-BS) SAR platforms with constant acceleration. To achieve a good performance and high efficiency, the baseband azimuth scaling (BAS) method cannot be directly applied for the azimuth focusing. The signal is calculated based on high squint concentric circle (HS-CC) range model. The conventional derotation operation is modified by nonlinear phase and range-dependent derotation. Then the space-variant (SV) Doppler chirp rate is corrected by BAS method without sub-aperture processing.