DocumentCode :
2079490
Title :
Sparse signal representation for MIMO radar imaging
Author :
Roberts, William ; Yardibi, Tarik ; Li, Jian ; Tan, Xing ; Stoica, Petre
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Florida, Gainesville, FL
fYear :
2008
fDate :
26-29 Oct. 2008
Firstpage :
609
Lastpage :
613
Abstract :
MIMO radar can achieve superior performance over the conventional phased-array radar through waveform diversity. Considerations in transmit waveform and receive filter design are central to attaining improved performance through a MIMO system. Moreover, adaptive array techniques are needed to improve accuracy, resolution and to further provide interference suppression. Recently, the weighted least-squares based iterative adaptive approach (IAA), a non-parametric and user parameter-free method was shown to provide good performance for array processing. In this paper, we demonstrate how IAA can be extended for MIMO radar applications. Our simulations show that IAA outperforms other well-established methods in the field.
Keywords :
MIMO communication; phased array radar; radar imaging; MIMO; iterative adaptive approach; phased-array radar; radar imaging; sparse signal representation; waveform diversity; Adaptive arrays; Adaptive systems; Array signal processing; Filters; Interference suppression; Iterative methods; MIMO; Radar imaging; Signal representations; Signal resolution;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signals, Systems and Computers, 2008 42nd Asilomar Conference on
Conference_Location :
Pacific Grove, CA
ISSN :
1058-6393
Print_ISBN :
978-1-4244-2940-0
Electronic_ISBN :
1058-6393
Type :
conf
DOI :
10.1109/ACSSC.2008.5074478
Filename :
5074478
Link To Document :
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