Publication Date:
2014-12-06
Description:
Sparse recovery algorithms with application to multiple-input–multiple-output (MIMO) radar imaging could lose their advantage under a phase mismatch among transmitter–receiver pairs. In this letter, we identify that the impact of a random phase mismatch on the imaging problem can come to a scale-down factor on the amplitude of the MIMO point spread function. We thereby establish the conditions of successful support recovery and the performance measure for the orthogonal matching pursuit (OMP) algorithm for the involved problem, both of which are functions of the scale-down factor. Meanwhile, sparse imaging via expectation–maximization (SIEM) is proposed to alleviate OMP performance loss in the face of a phase mismatch. Numerical results corroborate the analysis and illustrate the effectiveness of the SIEM algorithm.
Print ISSN:
1545-598X
Electronic ISSN:
1558-0571
Topics:
Architecture, Civil Engineering, Surveying
,
Geography
,
Geosciences
