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2012-03-07

Compressive Sensing Based Parameter Estimation for Monostatic MIMO Noise Radar

By Meng Yang and Gong Zhang
Progress In Electromagnetics Research Letters, Vol. 30, 133-143, 2012
doi:10.2528/PIERL12010702

Abstract

The novelty of this letter is that it capitalizes on noise waveform to construct measurement operator at the transmitter and presents a new method of how the analogue to digital converter (ADC) sampling rate in the monostatic multiple-input multiple-output (MIMO) noise radar can be reduced --- without reduction in waveform bandwidth --- through the use of compressive sensing (CS). The proposed method equivalently converts the measurement operator problems into radar waveform design problems. The architecture is particularly apropos for signals that are sparse in the target scene. In this letter, Estimates of both target directions and target amplitudes using CS for monostatic MIMO noise radar are presented. Sparse bases are constructed using array steering vectors. Orthogonal least squares (OLS) algorithm for reconstruction of both target directions and target amplitudes is implemented. Finally, the conclusions are all demonstrated by simulation experiments.

Citation


Meng Yang and Gong Zhang, "Compressive Sensing Based Parameter Estimation for Monostatic MIMO Noise Radar," Progress In Electromagnetics Research Letters, Vol. 30, 133-143, 2012.
doi:10.2528/PIERL12010702
http://jpier.org/PIERL/pier.php?paper=12010702

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