Improving robustness, efficiency and accuracy of synthetic aperture radar (SAR) imaging techniques using multi-measurement vectors
Abstract
The proposed research will develop numerical algorithms that effectively use multi-measurementdata collections to extract actionable information from acquired sensing data. Much research hasrecently been devoted to sparse signal and image recovery from multiple measurement vectors.Sometimes, as in synthetic aperture radar (SAR) over a small aperture, the collected data may notvary much. In other cases, such as MIMO SAR, the data can vary significantly. The PI will focus onthese applications as prototypical sensing models.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- May 30, 2018
- Source ID
- FA95501810316
Entities
People
- Anne Gelb
Organizations
- Air Force Office of Scientific Research
- Board of Trustees of Dartmouth College
- United States Air Force