A Novel Spectrum Reconstruction and Imaging Processing Method for Squint Multichannel SAR

Along a roughly chronological order, the azimuth signals undersampled from the multichannel synthetic aperture radar (SAR) for high-resolution wide-swath (HRWS) imaging correspond to recurrent nonuniform sampling. Only a finite-duration sequence of samples of the azimuth signal can be obtained in practical applications. A new recurrent nonuniform sampling scheme can be generated by extending these samples periodically across the boundaries provided that the azimuth signal is bandlimited. Thus, from the perspective of reconstructing recurrent nonuniform sampling, an innovative reconstruction algorithm for suppressing azimuth ambiguities of multichannel HRWS SAR is proposed, which is suitable to be implemented on digital computers. Furthermore, the presented algorithm acquires the filter weights without matrix inversion reducing tremendously the computational load.

For azimuth multi-channel synthetic aperture radar (SAR), unavoidable inconsistency errors between channels can degrade SAR image quality severely, leading to possible ghost targets and image defocusing, etc. To address this issue, a novel channel inconsistency estimation method is proposed based on maximum normalized image sharpness. First, channel amplitude and time delay errors are corrected in the coarse compensation step. Then images of each channel are attained by azimuth spectrum recovery and imaging processing. Next, range-variant channel phase errors are estimated via optimizing normalized image sharpness, which reaches the maximum value when the image is focused well or ghost targets are suppressed completely. The Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm is employed to get the optimal solution based on the derived gradient of objective function. Finally, the ultimate image is formed through adding up phase compensated images of each channel. By optimizing the focused image quality, the proposed algorithm achieves high estimation accuracy. Simulated data and real multi-channel SAR data are processed to demonstrate the effectiveness of the proposed method.

The azimuth multichannel synthetic aperture radar (SAR) system is used in ground moving target indication (GMTI). But for Ka-band SAR, the conflicts between high gain and wide swath coverage are very strict. The digital beamforming (DBF) scan-on-receive (SCORE) algorithm can solve this problem very well. This letter introduces a multichannel SAR system with three receiving antennas in the azimuth direction. For each azimuth antenna, eight subapertures are arranged in the elevation direction in order to obtain higher gain and a lower data rate through the DBF-SCORE algorithm. Airborne flight experiments with this system are accomplished successfully and quantities of experimental data are acquired. In this letter, we first derive the signal forms and weighting coefficients in the DBF-SCORE procedures. Then, different GMTI methods including along-track interferometry and displaced phase center antenna are introduced for azimuth multichannel SAR–GMTI based on the DBF-SCORE technology. Finally, airborne raw data with cooperating moving targets are processed successfully, and the estimation errors of the radial velocities meet the expected accuracy requirements.

High-resolution wide-swath (HRWS) imaging in azimuth multichannel synthetic aperture radar (MC-SAR) is critical for remote sensing, yet electromagnetic jamming severely degrades image quality. Conventional multichannel jamming suppression techniques, such as multichannel cancellation methods, which require precise jammer localization and high pulse repetition frequency (PRF), conflict with HRWS requirements and often leave residual artifacts. This article proposes a jamming suppression method for MC-SAR systems. The received MC-SAR signals are processed via spatial beamforming to generate directional beams, enabling identification of the jamming-dominated beam through power analysis. Multichannel correlation filtering suppresses jamming, and via inverse spatial beamforming to recover residual signals, followed by a reconstruction filter to restore the SAR Doppler spectrum. Simulations and experiments on measured SAR data demonstrate effective jamming suppression, minimal artifacts, and reduced PRF requirements compared to multichannel cancellation methods, ensuring high-quality HRWS imagery.

High-resolution and wide-swath synthetic aperture radar (SAR) images can be obtained by multichannel sampling. However, a nonoptimum pulse-repetition frequency is associated with a nonuniform spatial sampling in azimuth. A spectrum reconstruction algorithm and a filter group algorithm can be used to reconstruct the spectrum in azimuth with a nonuniform sampling. In this letter, a comparison of spectrum reconstruction algorithm and filter group algorithm is given. Through a transformation matrix, the relationship between out-of-band signals and the out-of-band signals after reconstruction is built. Furthermore, an equivalent spectrum after reconstruction is obtained, and simulation results proved that it is precise. From the equivalent spectrum, it shows that multichannel SAR can be seen as uniform sampling system but with a different original signal. Finally, channel imbalance is discussed. Simulation results have proved that the imbalance targets have the same location with corresponding ambiguous targets.

When combined with digital beam-forming (DBF) techniques, multichannel synthetic aperture radar (SAR) systems can achieve high-resolution and wide-swath SAR imaging. However, inevitable channel biases will degrade the performance of DBF in practice. To address this problem, a novel channel phase bias estimation algorithm is proposed in this letter. Theoretical analysis reveals that the signal of the first channel, which is considered as the reference channel, can be reconstructed from the signals of other channels, regardless of noise and signals outside the Doppler bandwidth. In the presence of phase biases, there is a reconstruction error after the cancellation by subtracting this reconstructed signal from the original signal. However, by minimizing the reconstruction error, the channel phase biases can be precisely estimated. The effectiveness of the proposed algorithm is validated by the experimental results.

The azimuth multichannel synthetic aperture radar (MC-SAR) is an effective means of earth observation due to its high-resolution and wide-swath (HRWS) imaging capability. Compared with the traditional MC-SAR, the two-dimensional (2D) spectrum of the squint multichannel synthetic aperture radar (SMC-SAR) is skewed, leading to the severe coupling between azimuth signals and range signals. Therefore, the traditional imaging algorithms are inapplicable to SMC-SAR. Currently, the existing imaging algorithms for SMC-SAR need interpolation or sub-aperture processing, which results in low efficiency. This paper proposes a novel imaging scheme for spaceborne SMC-SAR to handle this issue. With the squint angle known, the Doppler centroid can be compensated for by the spectrum shift function. Additionally, the frequency correlation method (FCM) is utilized to estimate the channel phase imbalance. After that, the azimuth multichannel data are reconstructed by the filter banks to eliminate the Doppler spectrum aliasing. Finally, the data are imaged based on the modified equivalent slant range model (MESRM). Both the simulation and Gaofen-3 (GF-3) data experiments demonstrate the effectiveness and efficiency of the proposed method.

Terrain Observation by Progressive Scans (TOPS) synthetic aperture radar (SAR) and spotlight SAR are advanced SAR imaging modes for wide range swath and high resolution. In order to obtain a wider range coverage, azimuth multichannel is introduced in the literature. Since the azimuth bandwidth of beam steering SAR (BS-SAR; spotlight SAR, sliding spotlight SAR, or TOPS SAR) is much greater than that of a stripmap SAR, a signal reconstruction algorithm used for multichannel stripmap SAR may not be effective for multichannel BS-SAR. In this paper, a multichannel full-aperture azimuth processing algorithm is proposed for a BS-SAR. The key of this algorithm lies in the beam and the azimuth bandwidth compressions of multichannel signals in the Doppler-array and slow time-angle planes, respectively. Through compression processing, the beamwidth and the azimuth bandwidth are smaller than the available angle and equivalent pulse repeating frequency , respectively. Then, an improved post-Doppler STAP method is proposed to recover a 2-D spectrum. With the recovered signal, further processing can be utilized to focus the multichannel signal. Simulation and real data results show the effectiveness of the proposed algorithm.

In this paper, a fast algorithm to reconstruct the spectrum of non-uniformly sampled signals is proposed. Compared with the original algorithm, the fast algorithm has a higher computational efficiency, especially when sampling sequence is long. Particularly, a transformation matrix is built, and the reconstructed spectrum is perfectly synthesized from the spectrum of every sampling channel. The fast algorithm has solved efficiency issues of spectrum reconstruction algorithm, and making it possible for the actual application of spectrum reconstruction algorithm in multi-channel Synthetic Aperture Radar (SAR).

In this paper, a ground-based phased-array radar is used to investigate the ability of a multichannel synthetic aperture radar (MSAR) to produce high-fidelity images of dynamic ocean scenes by correcting the distortions caused by the motion of the water surface itself. The ground-based system, the Naval Research Laboratory Focused Phased Array Imaging Radar (FOPAIR), mimics an MSAR with multiple apertures arrayed in the flight direction by rapidly and repeatedly scanning across a linear array of 64 antenna elements. This generates a virtually unlimited time stack of coherent images in the same way that an airborne MSAR generates multiple images as the antennas fly past the scene. By manipulating a single FOPAIR data set, both undistorted "benchmark" imagery and distorted images corresponding to an airborne MSAR can be generated. More significantly, the time stack of emulated MSAR images can be processed further using the velocity synthetic aperture radar (VSAR) technique to significantly reduce the well-known but seemingly unavoidable distortions caused by surface wave motion. In this paper, VSAR is demonstrated experimentally for the first time using FOPAIR imagery of a small boat. MSAR systems with a wide range of aperture numbers are emulated, including the special case of a two-aperture system, commonly known as an along-track interferometric SAR. The results emphasize that VSAR processing does not require a long surface coherence time to produce fine-resolution imagery, unlike a single-channel SAR. The results also illustrate some limitations of VSAR as a means to measure velocity and produce high-fidelity imagery of dynamic ocean scenes.

A new method for processing multichannel synthetic aperture radar (SAR) data to achieve desirable image characteristics is presented. The method is optimal because it is derived by minimizing a mean-square-error cost function and generalizes current methods for high-resolution wide-swath SAR signal processing. The proposed method is easily implementable, can support a wide range in the pulse repetition frequency (PRF), including cases with highly nonuniform spatial sampling, and is robust against PRFs where current projection techniques fail, cases where the PRF is ideally suited to clutter suppression. Point spread functions for the proposed algorithms are presented, and the theory and simulations are further corroborated by results using multichannel SAR data measured by RADARSAT-2. We demonstrate that, if RADARSAT-2 were able to illuminate a 250-km swath (300 km ground range), then, conceptually, the new method would be able to process the highly nonuniformly sampled data to provide an extremely wide mode at approximately 5-m azimuth resolution.

Although Synthetic Aperture Radar (SAR) can capture rich land cover information as a most important advanced technique in the field of international earth observation, the application effects still limited significantly. The reason is that the study of SAR imaging processing, SAR image processing and SAR applications are conducted respectively, the integrated study are lacked for parameter selection of SAR imaging processing and SAR image processing and targets identification of SAR application. Focusing on above science problems, the study for phase high fidelity model of high precision interferometric SAR, SAR non-stationary backscattering characteristics and cognition, SAR three-dimensional electromagnetic scattering modeling and its scattering mechanism and SAR multi-parameters optimization information extraction has been conducted. The typical natural distributed targets and man-made targets such as surface deformation, sea ice, building complex and collapsed building are selected, the method and application study oriented to SAR environmental parameters inversion are conduced, the main result and conclusion are as follows: (1) The overall theoretical frames of SAR information integrated processing was proposed; The simulation and ground validation system used to assess the effects of SAR information integrated processing was created; furthermore, the spaceborne SAR imaging algorithm with three steps focusing processing was proposed and realized the multi-modal integrated imaging processing and improved the imaging processing precision. (2) In terms of SAR information integrated processing of natural targets, focusing on phase high fidelity imaging processing of interferometric SAR surface deformation monitoring, an novel spaceborne SAR high fidelity simulation method based on stationary RCS and improved Goldstein SAR interferogram filter based on empirical mode decomposition were proposed. Focusing on multi-parameters optimization processing of sea ice types classification, the multi-channel spaceborne SAR sparse imaging method based on compressive sensing, Kalman filter for removal of scalloping and inter-scan banding in ScanSAR images and SVM sea ice classification method combined with sea ice concentration were proposed. (3) In terms of SAR information integrated processing of man-made targets, focusing on non-stationary backscattering from building complex, mitigation of azimuth ambiguities in spaceborne stripmap SAR iamges using selective restoration, SAR image despeckling by selective 3D filtering of multiple compressive reconstructed images and man-made target detection in urban areas based on a new azimuth stationary extraction method were proposed. Focusing on three-dimensional modeling and fast extraction of collapsed building, H-a-p method used for collapsed building extraction was proposed.

The azimuth multi-channel synthetic aperture radar (SAR) is widely used in marine observation, because of its excellent imaging ability of high-resolution and wide-swath (HRWS) signals. Different from the static targets, the azimuth ambiguity of the ships on the open sea resulting from the radial motion seriously affects the SAR image quality and ship detection probability. As a result, two methods of azimuth ambiguity suppression for moving ships based on motion phase compensation are proposed to apply to different practical application conditions. The simulation and real measured data experiments verify the ability of image quality improvement by proposed methods.

This paper investigates different metrics for ground moving target indication (GMTI) with a multichannel synthetic aperture radar (SAR). These metrics are especially sensitive to targets that have an across-track component of velocity, v/sub y/, although they can also detect targets with an along track velocity component, v/sub x/. Not only are the metrics suitable for fully SAR compressed data, they are also meaningful when computed for range (pulse) compressed but Doppler uncompressed data (raw data). The use of both data domains allows for target detection over a larger v/sub y/ range than either used individually. For large v/sub y/, side-lobe suppression in fully SAR compressed data simultaneously suppresses the targets, giving an advantage to the raw data domain. For low v/sub y/, and especially with low RCS targets, the SAR compression gain facilitates detection, giving an advantage to the SAR compressed domain. By viewing the SAR compression as the application of a linear filter, the metrics are shown to be suitable for target detection after any linear filtering of the raw data, such as a linear time-frequency filter, or a simple transformation into the Doppler domain using an FFT filter. The metrics have in common that they are all based on the eigenvector decomposition of the sample covariance matrix. Their statistical properties are analytically compared and their detection capabilities are demonstrated on measured two-channel airborne SAR data in a variety of data domains. Some metrics are shown to allow target detection with low false alarm rates even in heterogeneous terrain, such as in urban areas, without compromising the probability of detection.

Multi-channel synthetic aperture radar (SAR) systems enable high-resolution wide-swath imagery thus overcoming the inherent limitation of conventional SAR. A possible realization based on the combination of multi-aperture SAR signal reconstruction in azimuth with digital beamforming on receive in elevation is given in [1]. The present paper turns focus to advanced concepts for the imaging of even wider swaths while still providing high azimuth resolution [2]. In this regard, the operation of multi-channel SAR systems in burst modes like ScanSAR or TOPS is introduced and aspects of applying the multi-aperture reconstruction algorithm to burst mode data are analyzed. The influence of the digital processing network on performance parameters as signal-to-noise-ratio and azimuth ambiguity-to-signal-ratio in multi-channel burst mode systems is considered and embedded in the design example of a ScanSAR system that allows for the imaging of a 400 km wide swath with a geometric resolution of 5 m. Finally, first results for a multi-channel TOPS system are presented and an optimized TOPS processing approach is introduced.