In this paper, we present a sparse spatial spectrum estimation method which provides superresolution direction-finding performance and accurate signal power estimation simultaneously. Compressive sensing ideas are used in conjunction with a postulated model for the covariance matrix of the array output instead of the output itself. Following a preliminary analysis of the method and a geometric interpretation of the estimation process, simulation examples are presented to illustrate several performance characteristics of the technique.
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Zheng et al. (2009) studied this question.
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