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Proceedings Paper

A radar data fusion method based on sparse component analysis
Author(s): Tao Zhao; Qingtan Sun; Sihui Wang; Chunzhu Dong; Xuan Chen
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Paper Abstract

Aiming at the need of multi-radar multi-view wide-band data fusion to improve imaging resolution, a data correlation and sparse component analysis method is proposed to analyze and coherently process multi-view multi-band broadband data in a small angle. The target characteristics of more viewing angles within the small angle range improve the target two-dimensional imaging quality. The simulation experiment analyzes the error of wideband data reconstruction and verifies the correctness and effectiveness of the data fusion method.

Paper Details

Date Published: 31 January 2020
PDF: 6 pages
Proc. SPIE 11427, Second Target Recognition and Artificial Intelligence Summit Forum, 114272J (31 January 2020); doi: 10.1117/12.2552358
Show Author Affiliations
Tao Zhao, Science and Technology on Electromagnetic Scattering Lab. (China)
Qingtan Sun, Science and Technology on Electromagnetic Scattering Lab. (China)
Sihui Wang, Science and Technology on Electromagnetic Scattering Lab. (China)
Chunzhu Dong, Science and Technology on Electromagnetic Scattering Lab. (China)
Xuan Chen, Science and Technology on Electromagnetic Scattering Lab. (China)


Published in SPIE Proceedings Vol. 11427:
Second Target Recognition and Artificial Intelligence Summit Forum
Tianran Wang; Tianyou Chai; Huitao Fan; Qifeng Yu, Editor(s)

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