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Measurement Matrix Design for Compressive Sensing–Based MIMO Radar

Author(s): Yu, Yao; Petropulu, Athina P; Poor, H Vincent

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Abstract: In colocated multiple-input multiple-output (MIMO) radar using compressive sensing (CS), a receive node compresses its received signal via a linear transformation, referred to as a measurement matrix. The samples are subsequently forwarded to a fusion center, where an l 1 -optimization problem is formulated and solved for target information. CS-based MIMO radar exploits target sparsity in the angle-Doppler-range space and thus achieves the high localization performance of traditional MIMO radar but with significantly fewer measurements. The measurement matrix affects the recovery performance. A random Gaussian measurement matrix, typically used in CS problems, does not necessarily result in the best possible detection performance for the basis matrix corresponding to the MIMO radar scenario. This paper considers optimal measurement matrix design with the optimality criterion depending on the coherence of the sensing matrix (CSM) and/or signal-to-interference ratio (SIR). Two approaches are proposed: the first one minimizes a linear combination of CSM and the inverse SIR, and the second one imposes a structure on the measurement matrix and determines the parameters involved so that the SIR is enhanced. Depending on the transmit waveforms, the second approach can significantly improve the SIR, while maintaining a CSM comparable to that of the Gaussian random measurement matrix (GRMM). Simulations indicate that the proposed measurement matrices can improve detection accuracy as compared to a GRMM.
Publication Date: 18-Nov-2011
Citation: Yu, Yao, Petropulu, Athina P, Poor, H Vincent. (2011). Measurement Matrix Design for Compressive Sensing–Based MIMO Radar. IEEE Transactions on Signal Processing, 59 (11), 5338 - 5352. doi:10.1109/TSP.2011.2162328
DOI: doi:10.1109/TSP.2011.2162328
ISSN: 1053-587X
EISSN: 1941-0476
Pages: 5338 - 5352
Type of Material: Journal Article
Journal/Proceeding Title: IEEE Transactions on Signal Processing
Version: Author's manuscript

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