Algorithm to overcome atmospheric phase errors in SAL data
Abstract
Synthetic aperture ladar is an emerging sensor technology providing high-resolution imagery of targets from long standoff ranges. Atmospheric turbulence corrupts the collected phase history data with spatially variant phase perturbations, impacting resolution and contrast of reconstructed imagery. We explore the efficacy of model-based reconstruction algorithms with model error corrections to mitigate the deleterious effects of atmospheric turbulence and restore image quality. We present results from model error correction techniques utilizing spatially invariant, spatially variant, and a model-based atmospheric phase error correction. We quantify the performance of all algorithms using an atmospheric ray-trace simulation.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Dec 23, 2019
- Source ID
- 10.1364/ao.59.000140
Entities
People
- Arnab K. Shaw
- Randy S. Depoy
Organizations
- Air Force Research Laboratory