TR2016-092
Coherent Distributed Array Imaging under Unknown Position Perturbations
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- "Coherent Distributed Array Imaging under Unknown Position Perturbations", International Workshop on Compressed Sensing Theory and its Applications to Radar, Sonar, and Remote Sensing (CoSeRa), DOI: 10.1109/CoSeRa.2016.7745709, September 2016, pp. 105-109.BibTeX TR2016-092 PDF
- @inproceedings{Liu2016sep2,
- author = {Liu, Dehong and Kamilov, Ulugbek and Boufounos, Petros T.},
- title = {Coherent Distributed Array Imaging under Unknown Position Perturbations},
- booktitle = {International Workshop on Compressed Sensing Theory and its Applications to Radar, Sonar, and Remote Sensing (CoSeRa)},
- year = 2016,
- pages = {105--109},
- month = sep,
- doi = {10.1109/CoSeRa.2016.7745709},
- url = {https://www.merl.com/publications/TR2016-092}
- }
,
- "Coherent Distributed Array Imaging under Unknown Position Perturbations", International Workshop on Compressed Sensing Theory and its Applications to Radar, Sonar, and Remote Sensing (CoSeRa), DOI: 10.1109/CoSeRa.2016.7745709, September 2016, pp. 105-109.
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Abstract:
We consider a distributed array imaging problem for detecting targets in a region of interest (ROI), where the radar sensors are perturbed with location errors corresponding to several wavelengths. In order to improve the imaging performance, we propose a method based on compressive sensing that can simultaneously compensate for position-induced phase errors and perform focused imaging. Compared to existing autofocusing methods that typically exhibit poor performance for large position errors, our method can form sharp images of targets situated in the ROI even for position errors that are ten wavelengths large. We validate our method on simulated noisy data.