Abstract
Distributed compressive sensing (DCS) has been used in multiple-input multiple-output (MIMO) radar system. This application has led to substantial improvements over existing methods in MIMO radar. But there are also some challenges that should be resolved in order to benefit the most from DCS-based MIMO radar, such as radar signal with low signal to noise ratio and optimizing measurement matrix design. In distributed DCS-based MIMO radar context, this paper presents a cognitive mechanism for optimizing transmit and receive gain by applying the optimization guideline which based on the coherence of the sensing matrix (CSM) and signal-to-noise ratio. This paper proposed two kinds of method: the first one is to optimize transmit gain with the aim to maximize SNR, and the second one is to minimize CSM by adjusting receive gain. Simulations show that the proposed methods obtain significant better recovery performance than traditional DCS-based MIMO radar systems.
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Acknowledgments
This work is supported by China NSF Grants (61071163, 61271327,61071164, 61201367 and 61471191), the Fundamental Research Funds for the Central Universities (3082015NP2015504), and partly funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions (PADA) and the Natural Science Foundation of Jiangsu Province under Grant BK2012382 and Funding of Jiangsu Innovation Program for Graduate Education and the Fundamental Research Funds for the Central Universities under Grant CXZZ12-0155.
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Liu, S., Zhang, G., Zhang, JD. et al. Transmit and Receive Gain Optimization for Distributed MIMO Radar. Wireless Pers Commun 85, 1969–1986 (2015). https://doi.org/10.1007/s11277-015-2885-1
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DOI: https://doi.org/10.1007/s11277-015-2885-1