Sparse Array Distributed Radar Imaging Based on TSVD for Moving Target

Abstract

Radar high resolution imaging becomes a research hotspot in recent years. Synthetic Aperture Radar (SAR) uses motion of single platform to obtain large aperture. However, it can only obtain a limited resolution at a specific perspective. Distributed radar, which utilize platforms to expand in space and form a larger aperture. It records echo from multiple signal channels which can achieve high resolution in all directions. The existing distributed radar system mainly realizes the imaging of static target with lots of platforms. In this paper, we studied moving target imaging of distributed radar in sparse array condition. In this system, all the array elements can work flexibly as transmitter or receiver. Some methods of spectrum estimation are used to solve distributed radar imaging model. But they are all applied to static target and it is difficult to estimate the number of scattered points accurately, especially for moving target. We established the signal model of moving target in a period of observation time and solved it by using truncated singular value decomposition (TSVD) method. Simulation results verified the feasibility of the imaging model and excellent performance of proposed method.