Along-Track Swarm SAR: Echo Modeling and Sub-Aperture Collaboration Imaging Based on Sparse Constraints

Abstract

This article proposes an along-track swarm synthetic aperture radar (ATS-SAR) system to accomplish the high frame rate and enhance imaging resolution simultaneously. Unlike the current along-track multistatic SAR (Multi-SAR), each platform of the proposed ATS-SAR only collects part of the aperture data. Then, the bistatic pair acquisitions of ATS-SAR are transformed into virtual monostatic subapertures, and a large aperture is combined in a short time. Considering the practical motion state difference of each individual platform, various ATS-SAR echo models are thoroughly investigated and established. Furthermore, a subaperture collaboration imaging algorithm for ATS-SAR (SACIm-ATS) based on sparse constraints is also proposed. An effective phase compensation function is designed to improve echo sparsity by homogenizing the ATS-SAR echo. Then, the compressed sensing method can be utilized to accurately estimate more azimuth data, obtaining a higher azimuth resolution. Simulations and a real measured experiment are carried out to verify the effectiveness of the proposed ATS-SAR and the SACIm-ATS algorithm. Compared with the state-of-the-art imaging algorithms, the proposed SACIm-ATS algorithm can significantly enhance the ATS-SAR imaging performance.

Keywords

• Along-track swarm SAR
• compressed sensing
• echo modeling
• multistatic SAR (Multi-SAR)
• subaperture collaboration imaging