ISAR imaging of space objects using encoded apertures

TL;DR

This paper introduces an encoded aperture method combined with compressive sensing techniques to efficiently image space debris and satellites with fewer snapshots, improving detection and imaging speed.

Contribution

It proposes a novel encoded aperture approach with compressive sensing for space object imaging, reducing the number of snapshots needed for accurate reconstruction.

Findings

Successful image recovery with fewer snapshots

Outperforms SBL and SL0 in MSE and SNR

Effective for both debris and satellite imaging

Abstract

A major threat to satellites is space debris with their low mass and high rotational speed. Accordingly, the short observation time of these objects is a major limitation in space research for appropriate detection and decision. As a result, these objects do not fully illuminated, leading to their incomplete images at any snapshot. In this paper, we propose a method to decrease the number of snapshots in a given observation time and using a limited number of spot beams per snapshot called the encoded aperture. To recover the space debris images, an inverse problem is defined based on compressive sensing methods. Also, we show that for satellite imaging the T V norm is more appropriate. We develop a procedure to recover space debris and satellites using L1 and T V norms. Using simulation results, we compare the results with the well-known SBL and SL0 norm in terms of the number of snapshots, MSE, SNR, and running time. It is shown that our proposed method can successfully recover the space objects images using a fewer number of snapshots.