Point Spread Function Engineering for 3D Imaging of Space Debris using a Continuous Exact l0 Penalty (CEL0) Based Algorithm

TL;DR

This paper introduces a novel 3D imaging method for space debris using a single 2D snapshot, leveraging PSF engineering and CEL0-based sparse inverse algorithms for accurate localization.

Contribution

It presents a new approach combining PSF engineering with CEL0 penalty for efficient 3D localization from a single image, specifically applied to space debris imaging.

Findings

The CEL0-based algorithm effectively localizes space debris in 3D from 2D images.

Numerical experiments demonstrate the method's efficiency and accuracy.

The approach outperforms existing techniques in sparse 3D inverse problems.

Abstract

We consider three-dimensional (3D) localization and imaging of space debris from only one two-dimensional (2D) snapshot image. The technique involves an optical imager that exploits off-center image rotation to encode both the lateral and depth coordinates of point sources, with the latter being encoded in the angle of rotation of the PSF. We formulate 3D localization into a large-scale sparse 3D inverse problem in the discretized form. A recently developed penalty called continuous exact l0 (CEL0) is applied in this problem for the Gaussian noise model. Numerical experiments and comparisons illustrate the efficiency of the algorithm.