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High-resolution wide-swath (HRWS) imaging is the research focus of the modern spaceborne synthetic-aperture radar (SAR) imaging field, with significant relevance and vast application potential. Staggered SAR, as an innovative imaging system, mitigates blind areas across the entire swath by periodically altering the radar pulse repetition interval (PRI), thereby extending the swath width to multiples of that achievable by conventional systems. However, the staggered mode introduces inherent challenges, such as nonuniform azimuth sampling and echo data loss, leading to azimuth ambiguities and substantially impacting image quality. This paper proposes a sparse SAR imaging method for the low-oversampled staggered mode via compound regularization. The proposed method not only effectively suppresses azimuth ambiguities arising from nonuniform sampling without necessitating the restoration of missing echo data, but also incorporates total variation (TV) regularization into the sparse reconstruction model. This enhances the accurate reconstruction of distributed targets within the scene. The efficacy of the proposed method is substantiated through simulations and real data experiments from spaceborne missions. [ABSTRACT FROM AUTHOR]

The LuTan-1(LT-1), known as the L-band differential interferometric synthetic aperture radar (SAR) satellite system, is an essential piece of civil infrastructure in China, providing extensive applications such as surface deformation monitoring and topographic mapping. To achieve high-resolution and wide-swath (HRWS) observation abilities, the LT-1 takes the dual receiving antenna (DRA) imaging mode as its working mode. However, amplitude and phase errors between channels lead to a mismatch between the reconstruction filter and the multichannel echo signal, worsen the reconstructed azimuth spectrum, and introduce ambiguity targets in the final imaging results, seriously affecting the final imaging quality. In order to better evaluate the channel error and azimuth ambiguity performance of the LT-1 system, this paper proposed an advanced channel consistency correction method and conducted many measured data experiments. The experimental results show that the proposed method is effective, and the LT-1 system has excellent channel error control and azimuth ambiguity performance. [ABSTRACT FROM AUTHOR]

Azimuth multichannel (AMC) technology is one of the mainstream technical approaches to realize high-resolution wide-swath (HRWS) imaging. It has been successfully applied to several synthetic aperture radar (SAR) satellites in orbit. However, the inevitable imbalance between channels can seriously affect the azimuth reconstruction spectrum, introducing ghost targets into the final imaging results and degrading the SAR image quality. In order to address this issue, this paper proposes a channel imbalance estimation method based on minimizing the sum of the sub-band norm (MSSBN) for the reconstructed azimuth spectrum. First, the amplitude imbalance is calibrated in the range-Doppler domain. Then, the echo in each channel with phase imbalances is reconstructed by filters separately and converted to the range-Doppler domain. Finally, the global optimization algorithm is used to find the phase error of each channel so that the reconstructed postcompensation spectrum has the smallest sub-band spectrum norm sum. By two-dimensional blocking, this method can also estimate the space-varying phase imbalance in the range dimension and the time-varying phase imbalance in the azimuth dimension. Experimental results using simulated and actual AMC SAR data from the GF-3 system validate the proposed algorithm's high estimation accuracy and excellent computational efficiency. [ABSTRACT FROM AUTHOR]

Spotlight synthetic aperture radar (SAR) achieves very high-resolution (VHR) images by steering the azimuth beam during the formation of the synthetic aperture. In practice, the steering is implemented through discrete azimuth beam switching. Then, phase shifts can occur between the adjacent beams due to the error of the antenna pattern. In addition, the troposphere introduces a beam-angle-dependent delay to the echo. Those undesired phase shifts and delays cause phase errors in the received echo and result in image quality deterioration. In this letter, an algorithm, called the Newton entropy minimization (N-EM), is proposed to estimate and compensate the phase errors caused by the discrete azimuth beam steering for the spotlight SAR data. Combining with the subaperture imaging approach of the spotlight SAR, the algorithm estimates the phase offsets between each couple of the adjacent beams based on the minimum entropy criterion. The analytic expression, which is a nonlinear equation, is developed for the optimal estimation. Then, the Newton’s method is employed to solve the equation. The real spaceborne SAR (both the staring and sliding spotlight modes) data processing results demonstrate the efficiency and accuracy of the proposed algorithm. [ABSTRACT FROM AUTHOR]

The displaced phase center antenna (DPCA) technique is a classical method for achieving high-resolution wide-swath synthetic aperture radar (SAR) imaging. For optimum performance, the pulse repetition frequency (PRF) of DPCA SAR systems should satisfy the azimuth uniform sampling condition as far as possible. However, this rigid PRF selection may conflict with the timing diagram for some incidence angles, which usually results in a nonuniform sampling of the synthetic aperture. According to the sparse signal processing theory, this letter proposes a novel DPCA imaging algorithm for the nonuniform displaced phase center sampling. By combining the DPCA data processing operator based on a filter bank with the \ellq regularization scheme, the algorithm can efficiently recover the backscattering coefficients of the observed scene. The experimental results have shown that it is capable of resolving ambiguity and suppressing clutter effectively and is meanwhile insensitive to additive noise. [ABSTRACT FROM PUBLISHER]

Due to the great computation load and memory cost of the matrix-vector multiplication, the sparse reconstruction algorithms are severely limited in the applications of radar imaging with real data. In order to solve this problem, we construct a backprojection-based range–azimuth decoupled operator (BP-RADOp) and combine the complex approximate message passing algorithm (CAMP) with it. We call this algorithm BP-CAMP in this letter. Since BP-RADOp retains the merits of the backprojection method entirely (i.e., perfect motion compensation for any flight path, precise focus for arbitrarily wide bandwidths and integration angles, low artifact levels, unlimited scene size, and strictly local processing), it has universal applicability in comparison with the other decoupled operators deduced from the fast Fourier transform-based image formation algorithms. The theoretical analysis indicates when BP-CAMP and CAMP are both used to reconstruct large-scale observed scenes; the former has lower computation load and memory cost than the latter. Meanwhile, it is demonstrated that BP-CAMP achieves high-quality synthetic aperture radar imaging with undersampled echo data, and it is as robust as CAMP to additive noise by the simulations and real data processing. [ABSTRACT FROM PUBLISHER]

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. [ABSTRACT FROM AUTHOR]

For different applications with different requirements, many synthetic aperture radar (SAR) modes have been developed in the literature, such as, Terrain Observation by Progressive Scans (TOPS) SAR and sliding spotlight SAR. In this paper, we call TOPS SAR, sliding spotlight SAR, and spotlight SAR as beam steering SAR (BS-SAR for short). Comparing with stripmap SAR, BS-SAR can obtain a wide diversity of resolutions by increasing or reducing the azimuth synthetic time. Traditional polar formation algorithm (PFA) is an efficient algorithm which is mainly developed for spotlight SAR. The PFA has been validated to obtain well-focused results of raw data. In this paper, we extend the traditional PFA to process sliding spotlight SAR and TOPS SAR data, and we call it generalized PFA (GPFA). Comparing with the traditional PFA, GPFA contains a different azimuth deramping function and an additional azimuth scaling operation. The simulated and real data are used to validate the effectiveness of this method. [ABSTRACT FROM AUTHOR]

Many imaging algorithms for different modes, such as, stripmap synthetic aperture radar (SAR), spotlight SAR, sliding spotlight SAR, and terrain observation by progressive scans (TOPS) SAR, of SAR have been studied. This paper is to obtain a unified focusing algorithm (UFA) for these SAR modes based on fractional Fourier transform. By defining the rotation-center range, the stripmap SAR and spotlight SAR can be treated as special cases of sliding spotlight SAR or TOPS SAR. Then, a parameterized focusing algorithm determined by the rotation-center range is presented. Data of each mode can be focused by utilizing UFA and selecting parameters or rotation angles. Some application aspects of UFA are also analyzed. Simulation and real data results are presented to validate the analysis and the proposed method. [ABSTRACT FROM PUBLISHER]

Range cell migration (RCM) correction and azimuth spectrum being contained entirely in baseband are critical for ground moving-target imaging (GMTIm). Without the azimuth spectrum entirely contained within baseband and a proper RCM correction, the image will be defocused, or artifacts may appear in the image. An instantaneous-range-Doppler algorithm of GMTIm based on deramp–keystone processing is proposed. The main idea is to focus all the targets in the scene at an arbitrarily chosen azimuth time. With our proposed algorithm, RCMs of all targets in the scene are removed without a priori knowledge of their accurate motion parameters. The targets with azimuth spectrum not entirely in baseband, i.e., azimuth spectrum within an ambiguous pulse repeating frequency (PRF) band or spanning neighboring PRF bands, can also be effectively dealt with simultaneously. Theoretical analysis shows that no interpolation is needed. The simulated and real data are used to validate the effectiveness of this method. [ABSTRACT FROM PUBLISHER]

During the data acquisition of a sliding spotlight or terrain observation by progressive scan (TOPS) synthetic aperture radar (SAR), the steering of the antenna main beam increases the azimuth bandwidth but could result in the azimuth signal aliasing in the Doppler domain. To remove the aliasing, one has used a subaperture method. In this letter, we show a focusing scheme without the use of the subaperture for both sliding spotlight and TOPS SARs. In doing so, we eliminated the obvious increase in data volume or the subaperture division by choosing the pulse repetition frequency that is only 20% greater than the instantaneous bandwidth. The method was incorporated with an available imaging algorithm and then used to process simulated and collected data of the sliding spotlight and TOPS SARs. Well-focused results without aliasing were obtained. [ABSTRACT FROM PUBLISHER]

In the case of high range resolution and squint angle, current chirp scaling algorithm (CSA) and nonlinear CSA (NCSA) have a finite ability to achieve high-quality images. The problem stems from a range-dependent (i.e., space-variant) cubic- and higher order terms of range frequency, which require sufficient compensation or space-variant filtering, in the phase of the synthetic aperture radar transfer function, and this letter aims at dealing with this problem. First, an inequation is introduced to evaluate the highest order of range frequency terms whose space-variant coefficient has to be taken into account. Then, based on the method of series reversion, this letter proposes the extended NCS which can weaken the range dependence of the considered range frequency terms and achieve accurate range cell migration correction and range compression. Simulation results are presented to validate the proposed method. [ABSTRACT FROM PUBLISHER]

Since synthetic aperture technology was employed in radar signal processing, the information capability of radar has greatly been enhanced. A lot of imaging algorithms have also been developed. However, the high-resolution imaging for highly squinted synthetic aperture radar data is still a difficult issue due to large range migration and strong range dependence on the secondary range compression term that is relatively large and cubic with high focusing sensibilities for high resolution. To accommodate for this problem, the “squint-minimization” operation and azimuth nonlinear chirp scaling (CS) (ANCS) operation are studied in this paper. On the basis of these operations, we propose new imaging algorithms and analyze the characteristic of highly squinted data and the difficulty in focusing these data as well as discussing the principle of ANCS. We also introduce a new CS algorithm, and numerical examples show that the proposed algorithm is able to achieve 0.1 m of resolution under a squint angle as large as 70^\circs. [ABSTRACT FROM PUBLISHER]

Synthetic Aperture Ladar (SAL) has the ability to achieve fast high-resolution imaging due to the characteristics of ultra-high resolution and ultra-short synthetic aperture time. However, because synthetic aperture ladar operates in the near-infrared band and the operating wavelength is extremely short, small variations in flightpath can produce artifacts in the phase history that corrupt SAL image generation. This work proposes a motion compensation method based on symmetrical triangular linear frequency modulation continuous wave (T-FMCW) combining with Phase Gradient Autofocus (PGA). Firstly, the ambiguity function of T-FMCW is deduced and its characteristics are analyzed. Then the principle of velocity measurement and Cramer–Rao lower bound of speed estimation error based on this waveform are given. T-FMCW is used to estimate the radial velocity error of the platform in SAL system, and then the radial motion error is estimated by integration along azimuth to realize coarsely focused SAL image. For the coarsely focused SAL image, the residual motion error is extracted to improve the image quality by using PGA. The effectiveness and accuracy of the method is verified by simulation experiments. [ABSTRACT FROM AUTHOR]