Estimation of Ship Dynamics with a Multiplatform Radar Imaging System

Abstract

Distributed inverse synthetic aperture radar (ISAR) exploits the data acquired by multiple radar sensors carried by multiple platforms working in formation to increase the cross range resolution with respect to the value achievable by single platform systems. In this frame, the paper addresses the problem of the estimation of the ship dynamics, i.e., yaw, pitch, and roll rotation motions, exploiting the signals collected by such multiplatform radar imaging systems providing angular diversity in order to enable the focusing of the distributed ISAR images. Specifically, in this work a multi-angle formation of sensors is considered and the corresponding maximum likelihood estimator and Cramer Rao bound are derived. Then, a new Doppler matching based technique is proposed as a suboptimal approach exploiting only the linear component of the phase of the received signals. The performance analysis proves the effectiveness of the proposed techniques to separately estimate the horizontal, radial, and vertical components of the rotation vector, therefore making possible both the focusing and accurate cross-range scaling of the distributed ISAR products (as well as of the low-resolution ISAR images regarding the different sensors) and, as a further advantage, providing knowledge of the orientation of the corresponding image projection planes. The analysis of experimental multisensor datasets confirms the feasibility of the proposed techniques.