A Compressive Sensing Approach to Multistatic Radar Change Imaging
| Autor: | Mike Brennan, Chris Kreucher |
|---|---|
| Rok vydání: | 2014 |
| Předmět: |
Pulse-Doppler radar
business.industry Computer science Side looking airborne radar Continuous-wave radar Bistatic radar Compressed sensing Radar engineering details Computer Science::Computer Vision and Pattern Recognition Radar imaging Multistatic radar General Earth and Planetary Sciences Computer vision Artificial intelligence Electrical and Electronic Engineering business |
| Zdroj: | IEEE Transactions on Geoscience and Remote Sensing. 52:1107-1112 |
| ISSN: | 1558-0644 0196-2892 |
| DOI: | 10.1109/tgrs.2013.2247408 |
| Popis: | This paper describes a new approach for forming change images from multistatic radar data based on compressive sensing (CS). Broadly speaking, change images are naturally sparse in the raw image domain, which suggests a CS reconstruction method. Recent results show that the sparsity of the estimand dictates the number of samples required for faithful reconstruction, meaning a change image can be formed with far fewer measurements than used for conventional radar imaging. Our application has a small number of antennas arranged around the perimeter of a surveillance region, which provide large angular diversity but very poor angular sampling. Furthermore, due to application constraints, the scene is interrogated with limited frequency diversity. We aim to construct a high-resolution change image from the measurements, which are sub-Nyquist both spatially and in frequency. This paper first develops a radar imaging model in the context of CS, and then shows with collected data that a sparseness model improves image utility over conventional methods in our setting. |
| Databáze: | OpenAIRE |
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