Target Estimation Using Sparse Modeling for Distributed MIMO Radar

Authors:
Sandeep Gogineni;Arye Nehorai
Affiliations:
Department of Electrical and Systems Engineering, Washington University in St. Louis, St. Louis, MO, USA;Department of Electrical and Systems Engineering, Washington University in St. Louis, St. Louis, MO, USA
Venue:
IEEE Transactions on Signal Processing
Year:
2011

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Abstract

Multiple-input multiple-output (MIMO) radar systems with widely separated antennas provide spatial diversity by viewing the targets from different angles. In this paper, we use a novel approach to accurately estimate properties (position, velocity) of multiple targets using such systems by employing sparse modeling. We also introduce a new metric to analyze the performance of the radar system. We propose an adaptive mechanism for optimal energy allocation at the different transmit antennas. We show that this adaptive energy allocation mechanism significantly improves in performance over MIMO radar systems that transmit fixed equal energy across all the antennas. We also demonstrate accurate reconstruction from very few samples by using compressive sensing at the receivers.