Three-dimensional (3-D) reconstruction of multi-view synthetic aperture radar (SAR) can effectively correct geometric distortion and recover the target scene intuitively. However, due to the drastic changes in SAR images during the multi-view observation, it would appear many false estimation points in the traditional 3-D reconstruction algorithms. This paper proposes a new 3-D reconstruction algorithm based on semantic information of ship structure to improve the 3-D reconstruction results with multi-view SAR. The semantic information is used to construct the 3-D solution space of the ship target, which can greatly improve the reconstruction accuracy. Simulations verify the effectiveness of the proposed algorithm.

Medium-Earth-orbit (MEO) synthetic aperture radar (SAR) could provide a wide observable area and short revisit times while offering a moderate spatial resolution. The combination of maneuvering platform SAR receivers and MEO SAR transmitters has become a new research hotspot. However, the receiver often works in nonlinear trajectory with high maneuverability and highly squinted angle in practice. The curved trajectory of MEO SAR and the complex motion of the receiver would cause severe azimuth variance and range-Doppler coupling. The existing imaging algorithms mostly suffer from azimuth defocusing if applied to MEO/high maneuvering platform receiver bistatic SAR (MEO/HMP-BiSAR). To solve these problems, this article proposes a modified extended azimuth nonlinear chirp scaling (EANLCS) algorithm with a new perturbation function. A high-precision echo model is deduced for the modified EANLCS algorithm to describe the range history and echo phase. The modified EANLCS algorithm not only solves the problem of range cell migration and severe range-Doppler coupling, but it also equalizes the spatial variance of Doppler frequency modulation (FM) rates as well as high-order Doppler coefficients in MEO/HMP-BiSAR. The proposed algorithm markedly surpasses conventional algorithms in image quality. Simulations and real experiments are conducted to verify the effectiveness of the proposed algorithm.

Space-time adaptive processing (STAP) is widely used for clutter suppression[1]. The key of space-time adaptive processing is the accuracy of clutter covariance matrix estimation. In the airborne radar environment, besides the target of interest, there are many clutter and interference targets in different directions. The existence of these echoes makes the training samples used to estimate the clutter covariance matrix uneven. In this case, the paper proposes a sparse recovery STAP algorithm based on prior knowledge for sample selection to solve existing problems.

MEO spaceborne transmitter/missile-borne receiver (MEO/missile-borne) bistatic synthetic aperture radar (BiSAR) system has a number of advantages over other spaceborne bistatic SAR systems and monostatic missile-borne systems. It not only has wide coverage and short revisit time, but it can also achieve multi-missile guidance, small detection probability and forward-looking imaging. However, the imaging of the MEO/missile-born BiSAR is more difficult than other bistatic SAR modes due to the complex characteristics of spatial variance. In this paper, we develop a new BiSAR model with the MEO satellite transmitter and the missile receiver. The accurate geometric model for MEO/Missile-born BiSAR is established by using motion parameter vectors. Then we analyze the phase characteristics in MEO/missile-borne BiSAR with the highly squinted angle in the large scene. The paper lays a foundation for the imaging algorithm of MEO/missile -borne BiSAR system in large scene.

Multi-channel, DBF-based high-resolution wide swath SAR (HRWS-SAR) is dedicated to acquiring large observation width and high resolution in a single pass. However, the existing HRWS-SAR imaging modes are difficult to cover effectively for the coastline area not parallel to the satellite orbit. Combined with the beam direction changing, variable PRI and distance-oriented DBF techniques, the wide-swath range sweep SAR (WRS-SAR) can image the wide coastline area not parallel to the satellite orbit at high resolution in a single-pass. In this study, an extended wide nonlinear chirp scaling (E-WLNCS) algorithm is proposed, which mainly consists of: a time-domain blind range sample reconstruction algorithm combined with phase variation estimation, a non-uniform resampling algorithm combined with Doppler variation correction, and the effectiveness of the proposed modified E-WLNCS algorithm is demonstrated through point target and surface target simulations.

Synchronization error has great impact on bistatic SAR. In this paper, the influence of spatial synchronization error of azimuth-variant bistatic SAR was analyzed. The key problem of spatial synchronization is beam-steering error. Finally, the simulation of the influence of different synchronization error in SAR imaging of ship target results is presented, which lays a foundation for subsequent research and engineering problems.

Constant false alarm rate (CFAR) is the desired property for automatic target detection in unknown and nonstationary background. In this letter, an analysis of the experimental data shows that gamma (GM) distribution is a promising model for sea clutter. Furthermore, a modified cell-averaging (CA) detector for GM-distributed clutter is proposed by using the maximum likelihood estimation method. Theoretical analysis demonstrates that the proposed detector maintains the CFAR property with respect to the scale parameter of the GM-distributed background. The proposed detector is verified to be optimal in homogenous GM-distributed clutter with a known shape parameter when compared with CA, greatest of selection, ordered statistic (OS), and weighted amplitude iteration (WAI) detectors. At clutter edges, the proposed method attains a similar false alarm rate control compared with the CA, OS, and WAI detectors. In multiple-target scenario, the proposed method works effectively and robustly, whereas the competitors suffer performance degradation in varying degree. Simulation and experimental results demonstrate the superiority and generality of the proposed method.

Shipborne high-frequency surface wave radar (SHFSWR) has exhibited great advantages over onshore HFSWR (OHFSWR) in ocean remote sensing. Unlike OHFSWR, SHFSWR suffers the problem of Doppler spectrum spread owing to platform movement, which is a great challenge preventing the extraction of ocean surface parameters for SHFSWR. To address this challenge, in this letter, the mathematical model of ocean surface wind direction is first investigated based on the first-order SHFSWR cross section. Furthermore, a method for the wind direction inversion without ambiguity from the spread Doppler spectrum is proposed using a single receiving antenna. Meanwhile, the wind directions of the sea area covered by radar can be obtained by sequentially utilizing the proposed method, which is more appropriate for the application of SHFSWR with limited deck space and less cost. Experimental results of the real data collected in Taiwan Strait preliminarily verify the detection accuracy and the distance limit of the wind direction inversion, as the root-mean-square error and the detection range are 9.85° and 120 km, respectively.