Sparse Aperture Three-dimensional Reconstruction of Precession Target Based on Compressed Sensing

Abstract

As a kind of high speed rotation object, precession target is faced with migration through resolution cell (MTRC) in long synthetic aperture while using translational inverse synthetic aperture radar (ISAR) imaging algorithm. Compressed sensing (CS), by which we can exact recovery sparse signal from very limited samples, suggests that sparse aperture imaging of precession target maybe achievable. A cyclic shift algorithm based on CS is proposed in this paper to exploit the sparse apertures data for high-resolution ISAR imaging. The sparse signal recovery and imaging of precession target is achieved coupled with FOCUSS (focal undetermined system solver) algorithm. A conventional ISAR imaging is a two-dimensional (2-D) range-Doppler projection of a target and does not provide three-dimensional (3-D) information which is more reliable. For missile shaped like a flat-bottom cone, multistatic ISAR geometry model is built, and a 3-D reconstruction method, which is featured with stable structure characteristics, is proposed based on multistatic ISAR images. Simulation and real data results verify the validity and superiority of the proposed method.