MARSnet: Mission-aware Autonomous Radar Sensor Network for Future Combat Systems 12/8/06 to 12/31/09
Abstract
This ONR award has significantly helped the PI and his research group to survive and develop. Major achievements include students training, technology transfer to DoD product, and research accomplishments. Eight Ph.D students and eight M.S. students have been supported by this ONR project. Of these 16 Ph.D/M.S. students, 4 Ph.D students and 4 M.S. students are women. In this ONR project, we have systematically studied radar sensor networks, which include sense-through-foliage target detection using FOPEN radar and radar sensor network, UWB radar for Sense-through-foliage channel modeling and foliage clutter modeling, waveform design and diversity in radar sensor networks, multi-target detection in radar sensor networks, UWB noise radar for sense-through-wall channel modeling, and compressive sensing for radar and radar sensor networks, etc. Sixty-five papers have been produced during this project and are attached to this final technical report. Our research results on Foliage Penetration (FOPEN) radar and radar sensor networks have been transferred to US Air Force for their laser imaging through clouds product. The algorithms from this ONR project could be integrated into existing Navy and Marine Corps' radar sensor systems such as Tactical Remote Sensor System (TRSS), Joint Surveillance Target Attack Radar System (JSTARS), Tier II Pioneer Unmanned Aerial System (UAS), Expeditionary Tactical Area Surveillance System (ETASS), Critical Area Protection System (CAPS), etc. The research will directly benefit DoD netcentricity based programs and concepts including Navy FORCEnet, Distributed Common Ground System (DCGS), Transparent Urban Structures (TUS) program, etc.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jan 01, 2010
- Accession Number
- ADA513103
Entities
People
- Qilian Liang
Organizations
- University of Texas at Arlington