Translational motion estimation and compensation in distributed inverse synthetic aperture radar imaging of ship target with complex motion

Abstract

A translational motion estimation and compensation method is proposed based on the parametric method by multiple stations in the distributed inverse synthetic aperture radar (ISAR) imaging. For ship targets with complex motion, the distributed ISAR increases the cross-range resolution of the image by expanding the observation angle. However, the translation compensation methods by a single station will destroy the correlation between the echoes, which reduces the image quality, and a more accurate joint translation compensation method is required. Multi-static observation is obtained in the Distributed system, which we can utilise in the parameter estimation: 1) joint Doppler estimation, 2) station angle estimation, and 3) rotation velocity estimation. Based on the above estimations, the velocity vector and the acceleration vector of the target can be obtained, and then the translational motion compensation can be realised parametrically. The algorithm processing chain is presented in this paper. Finally, the numerical simulations with four stations are presented to verify the effectiveness and the robustness of the proposed algorithm.

Novel approach for sparse aperture inverse synthetic aperture radar imaging via improved alternating direction method of multipliers algorithm

“…The inverse synthetic aperture radar (ISAR) has received lots of attention in many areas such as defence, for the reason that it can obtain the image of non-cooperative moving targets regardless of the weather and time [1][2][3]. The high azimuth resolution in the ISAR image is based on the target motion and the coherent processing interval (CPI), while the high range resolution of the ISAR image is obtained by processing the transmitted wide band signal [4].…”

“…All the ADMM based ISAR imaging algorithms mentioned above have the following problems: (1) The parameters of the ADMM are determined either artificially or time-consumingly like [19]. (2) The target and non-target components in the ISAR image share the same model parameters which means that these algorithms do not discriminate the target and non-target components.…”