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The Scientific World Journal - Volume 2015 2015, Article ID 397878, 10 pages -

Research ArticleDepartment of Mathematics, Drexel University, Philadelphia, PA 19104-0250, USA

Received 27 July 2015; Accepted 31 August 2015

Academic Editor: Sandra Costanzo

Copyright © 2015 Michael F. Minner. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The accurate detection of targets is a significant problem in multiple-input multiple-output MIMO radar. Recent advances of Compressive Sensing offer a means of efficiently accomplishing this task. The sparsity constraints needed to apply the techniques of Compressive Sensing to problems in radar systems have led to discretizations of the target scene in various domains, such as azimuth, time delay, and Doppler. Building upon recent work, we investigate the feasibility of on-grid Compressive Sensing-based MIMO radar via a threefold azimuth-delay-Doppler discretization for target detection and parameter estimation. We utilize a colocated random sensor array and transmit distinct linear chirps to a small scene with few, slowly moving targets. Relying upon standard far-field and narrowband assumptions, we analyze the efficacy of various recovery algorithms in determining the parameters of the scene through numerical simulations, with particular focus on the -squared Nonnegative Regularization method.

Autor: Michael F. Minner



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