Title :
Iterative Generalized-Likelihood Ratio Test for MIMO Radar
Author :
Xu, Luzhou ; Li, Jian
Author_Institution :
Dept. of Electr. & Comput. Eng., Florida Univ., Gainesville, FL
fDate :
6/1/2007 12:00:00 AM
Abstract :
We consider a multiple-input multiple-output (MIMO) radar system where both the transmitter and receiver have multiple well-separated subarrays with each subarray containing closely spaced antennas. Because of this general antenna configuration, both the coherent processing gain and the spatial diversity gain can be simultaneously achieved. We compare several spatial spectral estimators, including Capon and APES, for target detection and parameter estimation. We introduce a generalized-likelihood ratio test (GLRT) and a conditional generalized-likelihood ratio test (cGLRT) for the general antenna configuration. Based on GLRT and cGLRT, we then propose an iterative GLRT (iGLRT) procedure for target detection and parameter estimation. Via several numerical examples, we show that iGLRT can provide excellent detection and estimation performance at a low computational cost
Keywords :
MIMO systems; antenna arrays; iterative methods; radar antennas; MIMO radar; antenna configuration; closely spaced antennas; iterative GLRT; iterative generalized-likelihood ratio test; receiver; spatial diversity gain; spatial spectral estimators; target detection; transmitter; Diversity methods; MIMO; Object detection; Parameter estimation; Radar antennas; Receiving antennas; Spaceborne radar; Testing; Transmitters; Transmitting antennas; Adaptive arrays; block-diagonal growth-curve (BDGC) model; detection; generalized-likelihood ratio test (GLRT); growth-curve (GC) model; localization; multiple-input multiple- output (MIMO) radar; parameter estimation;
Journal_Title :
Signal Processing, IEEE Transactions on
DOI :
10.1109/TSP.2007.893937