An optical imager that exploits off-center image rotation to encode both the lateral and depth coordinates of point sources in a single snapshot can perform 3D localization and tracking of space debris. When actively illuminated, unresolved space debris, which can be regarded as a swarm of point sources, can scatter a fraction of laser irradiance back into the imaging sensor. Determining the source locations and fluxes is a large-scale sparse 3D inverse problem, for which we have developed efficient and effective algorithms based on sparse recovery using non-convex optimization. Numerical simulations illustrate the efficiency and stability of the algorithms.
@article{arxiv.1809.10541,
title = {Novel Sparse Recovery Algorithms for 3D Debris Localization using Rotating Point Spread Function Imagery},
author = {Chao Wang and Robert Plemmons and Sudhakar Prasad and Raymond Chan and Mila Nikolova},
journal= {arXiv preprint arXiv:1809.10541},
year = {2018}
}
Comments
16 pages. arXiv admin note: substantial text overlap with arXiv:1804.04000