Analysis of Frequency Agile Radar via Compressed Sensing

Tianyao Huang; Yimin Liu; Xingyu Xu; Yonina C. Eldar; Xiqin Wang

doi:10.1109/TSP.2018.2876301

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Analysis of Frequency Agile Radar via Compressed Sensing

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Analysis of Frequency Agile Radar via Compressed Sensing

Tianyao Huang, Yimin Liu, Xingyu Xu, Yonina C. Eldar and Xiqin Wang

IEEE Transactions on Signal Processing, Vol.66(23), pp.6228-6240

01/Dec/2018

DOI: https://doi.org/10.1109/TSP.2018.2876301

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http://arxiv.org/abs/1808.09124View

Preprint (Author's original)https://arxiv.org/licenses/nonexclusive-distrib/1.0/license.htmlOther, Open Access

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https://doi.org/10.1109/TSP.2018.2876301View

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Abstract

Frequency agile radar (FAR) is known to have excellent electronic counter-countermeasures performance and the potential to realize spectrum sharing in dense electromagnetic environments. Many compressed sensing (CS) based algorithms have been developed for joint range andDoppler estimation in FAR. This paper considers theoretical analysis of FAR via CS algorithms. In particular, we analyze the properties of the sensing matrix, which is a highly structured random matrix. We then derive bounds on the number of recoverable targets. Numerical simulations and field experiments validate the theoretical findings and demonstrate the effectiveness of CS approaches to FAR.

Details

Title: Analysis of Frequency Agile Radar via Compressed Sensing
Creators: Tianyao Huang (null) - Tsinghua University
Yimin Liu (Corresponding Author) - Tsinghua University
Xingyu Xu (null) - Tsinghua University
Yonina C. Eldar (null) - Technion – Israel Institute of Technology
Xiqin Wang (null) - Tsinghua University
Resource Type: Journal article
Publication Details: IEEE Transactions on Signal Processing, Vol.66(23), pp.6228-6240; 01/Dec/2018
Number of pages: 13
Language: English
DOI: https://doi.org/10.1109/TSP.2018.2876301
Grant note: The associate editor coordinating the review of this manuscript and approving it for publication was Prof. Xin Wang. The work of T. Huang, Y. Liu, X. Xu, and X. Wang was supported by the National Natural Science Foundation of China under Grants 61801258 and 61571260. This paper was presented in part at the 2015 IEEE China Summit and International Conference on Signal and Information Processing, Chengdu, China, Sep. 2015. The authors would like to thank Mr. P. Li, Dr. H. Shi, and Mr. T. Zhao for providing insightful suggestions, and Mr. L. Wang for collecting data in the field experiments and performing some simulations.
Record Identifier: 993266136803596

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