Azimuth ambiguity degrades the quality of synthetic aperture radar (SAR) images and leads to the increase of false alarm rate in ground moving target indication (GMTI). Due to the existing azimuth ambiguity, suppression methods do not remove the first-order ambiguity completely and ignore the ambiguity above first order as well, moving target detection is affected by residual ambiguity. Hence, a novel method to suppress first-order and higher order azimuth ambiguities for the dual-channel SAR/GMTI is proposed in this letter. First, the displaced phase center antenna (DPCA) technique is applied to suppress clutter. Then, estimate the local azimuth ambiguity-to-signal ratio (LAASR) to find out the area affected by ambiguity. Finally, an inpainting algorithm is improved to patch the ambiguity area. The proposed method can remove the ambiguity almost completely. Moreover, the method is verified using the GaoFen-3 SAR dual-channel complex image data, and the result shows that the false alarm of moving target detection is degraded without reducing the detection rate.

In azimuth multichannel high-resolution and wide-swath (AMC-HRWS) synthetic aperture radar (SAR) system, undersampling of azimuth signal results in the failure of the single-channel echo imaging, so the echoes of all the channels should be reconstructed to obtain the unambiguous SAR image. Many methods have been proposed to reconstruct the stationary scene echoes. However, moving targets (MTs) will cause false targets in the reconstructed SAR image, which has a great influence on SAR image interpretation and moving target detection, especially in maritime scenes. Hence, we propose an unambiguous imaging method of the moving target for maritime scenes with AMC-HRWS SAR. First, azimuth deramp processing is introduced to obtain coarse-focused moving targets, and then their echoes can be extracted from the sea clutter. Based on the extracted data, a radial velocity estimation method is proposed, which is high efficiency and does not require redundant channels. In addition, based on the estimated radial velocity and the characteristics of the coarse-focused signal, a novel signal reconstruction method of moving target is presented. The reconstruction performance of this method is not affected by channel imbalance, and false targets can be removed even if there is radial velocity error. Besides, the effectiveness of this scheme is verified by the simulation data and GaoFen-3 SAR real data. The estimated radial velocities of ships are verified by automatic identification system (AIS) information. The imaging results show that false targets are effectively suppressed, and moving targets are located in correct positions.

In spaceborne synthetic aperture radar (SAR), moving targets are almost buried in ground clutter due to the wide clutter Doppler spectrum and the restricted pulse repetition frequency (PRF), which increases the difficulty of moving target detection. Clutter suppression is one of the key issues in the spaceborne SAR moving target indicator operation. In this paper, we describe the clutter suppression principle and analyze the influence of amplitude and phase error on clutter suppression. In the following, a novel dual-channel SAR clutter suppression algorithm is proposed, which is suitable for the Gaofen-3(GF-3) SAR sensor. The proposed algorithm consists of three technique steps, namely adaptive two-dimensional (2D) channel calibration, refined amplitude error correction and refined phase error correction. After channel error is corrected by these procedures, the clutter component, especially a strong clutter component, can be well suppressed. The validity of the proposed algorithm is verified by GF-3 SAR real data which demonstrates the ground moving-target indication (GMTI) capability of GF-3 SAR sensor.

Multibaseline (MB) synthetic aperture radar inter-ferometry (InSAR) is capable of reconstructing steep terrain height profiles, and MB phase unwrapping (PU) is one of the most critical and challenging steps in its processing chain. Existing MB PU algorithms usually suffer from poor noise robustness or low computational efficiency. In this work, we propose a fast and robust MB PU algorithm, including three main steps: 1) construct the triangulation network guided by the quality map; 2) obtain robust estimation of ambiguity number gradients based on the intrinsic relationship between interferograms and gradient regularization; 3) solve minimum cost flow problem with modified weights. The mean absolute errors of the height profiles constructed by the proposed method are 1.6m and 1.3m for simulated data and real data experiments respectively, verifying the effectiveness of the proposed method.

Ground moving target indication (GMTI) is one of the important applications of synthetic aperture radar (SAR). Due to the finite pulse sampling rate in azimuth, the azimuth ambiguity appears in spaceborne SAR systems, which not only reduces the image quality, but also affects the accuracy of moving target detection. The existing ambiguity suppression methods cannot retain moving targets which are overlapped with ambiguity, or cannot suppress the ambiguity in SAR-GMTI. In order to overcome the shortcomings of existing methods, this letter proposes an effective azimuth ambiguity suppression method based on local azimuth ambiguity-to-signal ratio (AASR) estimation and ambiguity focusing for SAR-GMTI. This method can effectively suppress the ambiguity, and is applicable to the situations where the moving target is overlapped with the ambiguity, large scenes and higher order ambiguity. Finally, the effectiveness of the proposed method is verified and demonstrated by the experimental results on GaoFen-3 SAR.

This article investigates channel phase mismatch calibration during the application of displaced-phase-center antenna (DPCA) in dual-channel sliding spotlight synthetic aperture radar (SAR) for ground moving target indication (GMTI). In sliding spotlight SAR, the utilization of beam progressive sweeping in azimuth causes antenna phase centers to be misaligned from the sensor path, resulting in the phase mismatch between channels. Then, spatial channel co-registration required in the DPCA cannot be achieved directly by an azimuth time shift. In this study, a calibration method based on scanning geometry of the dual-channel sliding spotlight SAR is developed to address this issue. Moreover, the effect of the phase mismatch calibration on the estimation of azimuth time difference between the two channels is derived and analyzed in depth. The clutter suppression results processed from experimental data acquired by a C-band dual-channel SAR system (Gaofen-3) operated in sliding spotlight mode are shown for the first time to demonstrate the effective phase mismatch calibration.