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Sensing Matrix Restriction Method for Compressed Sensing Radar

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Abstract

To improve the robustness of target scene extraction for compressed sensing radar, an sensing matrix orthogonal restriction method is proposed through solving the matrix nearness problem between the complex Gram matrix and the target matrix. First, we introduce a target matrix maintaining the character of any subset in sensing matrix and minimizing mutual-coherence of sensing matrix. Then least square method and properties of Kronecker product and vector operator are employed to solve the matrix nearness problem with fixed transmission waveform or measurement matrix. The restricted sensing matrix can be achieved through optimizing the transmission waveform and measurement matrix separately or simultaneously. Our approach can effectively reduce the sensing matrix mutual-coherence and improve the performance of target scene recovery. Lastly, numerical simulations are performed to illustrate the priority of the proposed restriction method.

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Dai, L., Cui, C., Yu, J. et al. Sensing Matrix Restriction Method for Compressed Sensing Radar. Wireless Pers Commun 84, 605–621 (2015). https://doi.org/10.1007/s11277-015-2652-3

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