Compressive Sensing for Radar and Radar Sensor Networks
Abstract
In this project, compressive sensing for radar and radar sensor networks were studied. Significant results have been achieved in the following aspects: Compressive Sensing in Radar Sensor Networks Using Pulse Compression Waveforms; Theoretical Performance Bounds for Compressive Sensing with Random Noise; Compressive Sensing in Radar Sensor Networks for Target RCS Value Estimation; Rate Distortion Performance Analysis of Compressive Sensing; etc. Three PhD students were directly supported by this project, and have graduated. Major recognitions and awards associated with the sponsored research were conferred to the PI. 21 journal papers and 30 conferences papers were published or presented, and a complete list is attached in this report.
Document Details
- Document Type
- Technical Report
- Publication Date
- Dec 02, 2013
- Accession Number
- ADA594976
Entities
People
- Qilian Liang
Organizations
- University of Texas at Arlington