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In forward‐looking imaging, left‐right Doppler is ambiguous and cross‐range resolution is limited by real aperture, which result in traditional synthetic aperture radar imaging methods no longer applicable. Besides, the impact of three‐dimensional acceleration on an over‐complete dictionary matrix and sparse reconstruction kernel is not considered in conventional super‐resolution forward‐looking imaging methods. To solve these problems, a super‐resolution forward‐looking imaging method for manoeuvering platforms is proposed. First, the range walk caused by forward‐looking geometry and higher‐order phase introduced by three‐dimensional acceleration are eliminated by compensating a pre‐processing function. Subsequently, according to beam steering‐based geometry and linear regression model, the over‐complete dictionary matrix is optimised to more accurately describe the complicated forward‐looking geometry with curved trajectory. Finally, sparsity adaptive matching pursuit kernel with an improved halting condition is adopted to reconstruct the forward‐looking scene. The proposed method is supported by point target simulation and surface target simulation. [ABSTRACT FROM AUTHOR]

Spaceborne bistatic multichannel synthetic aperture radar (MC-SAR) system employed inclined geosynchronous Earth orbit (GEO) transmitter and low-Earth-orbit (LEO) receiver can provide fine spatial resolution and a vast area of surveillance, which presents great potentials for future Earth observation. Nevertheless, owing to special geometry and big differences of orbital characteristics, the conventional effective phase centre (EPC) operation for unambiguous SAR signal reconstruction cannot be directly used. To address the issue, starting from geometry model of GEO-LEO bistatic MC-SAR, the new effective positions of the receiving channels are obtained. Then, the time-variant characteristics of residual phase error after the presented EPC processing is analysed. Finally, the method of reconstructing unambiguous SAR signal is presented. Simulation results show the validity of the proposed method, which can efficiently reconstruct the unambiguous signal for GEO-LEO bistatic SAR. [ABSTRACT FROM AUTHOR]

In multi‐channel high‐resolution and wide‐swath (HRWS) synthetic aperture radar (SAR) processing, range sampling time errors and phase mismatches severely degrade the reconstruction performance of unambiguous Doppler spectrum. To address this problem, an improved channel mismatch estimation algorithm for multi‐channel HRWS SAR is presented in this Letter. The technique of combining phase wrapping and weighted least‐squares fitting is capable of realising a robust estimation of range sampling time errors and constant phases between adjacent channels. Then, Doppler centroid as well as channel phase mismatches can be estimated from these constant phases based on the theory of spatial cross‐correlation coefficient (SCCC). Compared to the conventional algorithm, the improved performance can be achieved by using the proposed two‐step procedure. The effectiveness of the proposed algorithm is confirmed by experimental results based on airborne real data. [ABSTRACT FROM AUTHOR]

This Letter proposes a high‐precision and non‐iterative polarimetric synthetic aperture radar (SAR) (PolSAR) calibration algorithm. By solving a system of non‐linear equations, the distortion parameters can be obtained directly. The proposed algorithm is assessed by the simulated PolSAR data. The experimental results show that the algorithm can accurately solve all distortion parameters even though the crosstalk is high and has a better estimation performance compared with the widely used non‐iterative Quegan algorithm. [ABSTRACT FROM AUTHOR]

By applying digital beam‐forming (DBF) technique, the along‐track multi‐channel synthetic aperture radar (SAR) system can simultaneously achieve high‐resolution and wide‐swath (HRWS) imaging. However, the presence of unavoidable phase biases tends to degrade the DBF performance. To address this issue, a novel phase bias estimation algorithm based on Doppler spectrum optimisation is proposed. By exploiting the fact that phase bias would cause Doppler spectrum broadened, the phase biases can be successfully estimated by maximising a sharpness optimisation of the Doppler spectrum. The effectiveness of the algorithm is validated by experimental result carried out on the SAR data collected by an air‐borne multi‐channel system. [ABSTRACT FROM AUTHOR]

3D scene reconstruction from single‐pass circular synthetic aperture radar (CSAR) data has been a research hot spot in various remote sensing applications. Among existing literature, radargrammetry techniques and model assistant methods are two dominant approaches. However, the performance of these methods is limited in practical applications: radargrammetry techniques obtain merely one height value along vertical; model assistant approaches only work when valid models are given. A single‐pass CSAR 3D scene point cloud reconstruction method is proposed. First, the connection between an object and its projections in multi‐aspect SAR images is established with no auxiliary model. On the basis of the connection, voxels are classified into inner voxels (voxels beneath the target profile) and outside voxels (voxels outside of the target profile). Discarded all the outside voxels, the remained inner voxels are combined to form the 3D point cloud of the target. It is similar to the sculpturing process from a raw material to a piece of craft. Finally, a 3D scene is retrieved through assembling all reconstructed targets into a unified coordinate system. The feasibility of the proposed method is validated by the Gotcha Volumetric SAR Data Set. [ABSTRACT FROM AUTHOR]