DocumentCode :
1781254
Title :
Robust waveform optimization for MIMO radar to improve the worst-case detection performance
Author :
Hongyan Wang ; Bingnan Pei ; Zumin Wang ; Shuai Tao
Author_Institution :
Coll. of Inf. Eng., Dalian Univ., Dalian, China
fYear :
2014
fDate :
19-23 May 2014
Firstpage :
1098
Lastpage :
1101
Abstract :
In this paper, we consider the robust waveform optimization to improve the worst-case detection performance over a convex uncertainty model. An iterative algorithm is proposed to optimize the waveform covariance matrix (WCM) for maximizing the worst-case output signal-interference-noise-ratio (SINR) such that the worst-case detection performance can be improved. Each iteration step in the proposed algorithm can be reformulated as a semidefinite programming (SDP) problem. Numerical results show that the worst-case detection performance can be improved considerably by the proposed method compared to uncorrelated waveforms.
Keywords :
MIMO radar; convex programming; covariance matrices; iterative methods; radar detection; radar interference; MIMO radar; SDP problem; SINR; WCM; convex uncertainty model; iterative algorithm; radar detection performance; robust waveform optimization; semidefinite programming problem; signal-interference-noise-ratio; waveform covariance matrix; Arrays; MIMO radar; Numerical models; Optimization; Robustness; Signal to noise ratio; Uncertainty; MIMO radar; SDP; convex optimization; waveform optimization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Radar Conference, 2014 IEEE
Conference_Location :
Cincinnati, OH
Print_ISBN :
978-1-4799-2034-1
Type :
conf
DOI :
10.1109/RADAR.2014.6875759
Filename :
6875759
Link To Document :
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