Presence Of Motion Errors Research Articles

RPCA-AENet: Clutter Suppression and Simultaneous Stationary Scene and Moving Targets Imaging in the Presence of Motion Errors.

Clutter suppression and ground moving target imaging in synthetic aperture radar (SAR) system have been receiving increasing attention for both civilian and military applications. The problem of clutter suppression and ground moving target imaging in practical applications is much more challenging due to the motion error of the radar platform. In this article, we focus on the problems of clutter suppression and simultaneous stationary and moving target imaging in the presence of motion errors. Specifically, we propose a robust principal component analysis autoencoder network (RPCA-AENet) in a single-channel SAR system. In RPCA-AENet, the encoder transforms the SAR echo into imaging results of stationary scene and ground moving targets, and the decoder regenerates the SAR echo using the obtained imaging results. The encoder is designed by the unfolded robust principal component analysis (RPCA), while the decoder is formulated into two dense layers and one additional layer. Joint reconstruction loss, entropy loss, and measurement distance loss are utilized to guide the training of the RPCA-AENet. Notably, the algorithm operates in a totally self-supervised form and requires no other labeled SAR data. The methodology was tested on numerical SAR data. These tests show that the proposed architecture outperforms other state-of-the-art methods.

Nonsystematic Range Cell Migration Analysis and Autofocus Correction for Bistatic Forward-looking SAR

In general, autofocus methods integrated with frequency-domain imaging algorithms are instrumental to obtain a well-focused bistatic forward-looking synthetic aperture radar (BFSAR) image in the presence of motion errors. Nevertheless, before applying autofocus methods to correct the azimuth phase errors, range cell migration (RCM) should be eliminated by the RCM correction (RCMC) procedure in frequency-domain imaging algorithms. With motion errors being taken into account, there always exists some residual nonsystematic RCM (NsRCM), which refers to the residual migration components after the RCMC procedure. For the conventional side-looking SAR, NsRCM is caused by motion errors. On the other hand, NsRCM of BFSAR is originated from motion errors before RCMC and the NsRCM amplified by the RCMC procedure. In this paper, we analyze the different types of NsRCM in BFSAR imaging and their relationship. Based on the analyses, we propose an autofocus NsRCM correction scheme for BFSAR imagery using frequency-domain imaging algorithms that can eliminate the range-dependent NsRCM. The proposed scheme consists of three steps. First, for the BFSAR data after range compression and RCMC, a division procedure is carried out in the azimuth direction. The subblocks with the highest signal-to-clutter ratio along the range direction are selected after the azimuth segmentation procedure. Second, for the selected subblocks, the total NsRCM is estimated based on the minimum-entropy criterion. Based on the estimation results, different parts of the NsRCM are obtained by solving an ordinary differential equation. Third, a two-step compensation of the NsRCM is executed to reach the spatially variant correction. Simulations and experimental results are provided to demonstrate that our proposed scheme is effective for BFSAR imaging.

Interferometric height estimation of the seafloor via synthetic aperture sonar in the presence of motion errors

An end-to-end simulated processing chain related to an existing synthetic aperture sonar (SAS) system is developed and described, including motion compensation, efficient image formation and autofocus procedures. The processing is extended to include interferometric height estimation capability. It is the goal of the paper to study the application of interferometry to SAS systems in the presence of motion errors. The system is analysed with respect to motion errors and the subsequent damaging effects to both imaging and height estimation. Results using both measured and simulated data are presented. The problem is addressed with respect to both one-pass and two-pass imaging geometries, and it is hypothesised that for slowly varying target height, one-pass SAS interferometry may be a more robust imaging tool than conventional SAS alone. The simulated results suggest that height information is recoverable even in some situations in which the conventional SAS reflectivity image is completely ruined by phase error induced blur. High-resolution SAS imaging coupled with interferometric height estimation for seafloor imaging has military applicability in mine detection or classification and in topographic mapping in preparation for an amphibious assault. Civilian uses would include surveying of objects such as oil pipelines and seabed mapping.