DocumentCode :
2434291
Title :
Reduced complexity angle-Doppler-range estimation for MIMO radar that employs compressive sensing
Author :
Yu, Yao ; Petropulu, Athina P. ; Poor, H. Vincent
Author_Institution :
Electr. & Comput. Eng. Dept., Drexel Univ., Philadelphia, PA, USA
fYear :
2009
fDate :
1-4 Nov. 2009
Firstpage :
1196
Lastpage :
1200
Abstract :
The authors recently proposed a MIMO radar system that is implemented by a small wireless network. By applying compressive sensing (CS) at the receive nodes, the MIMO radar super-resolution can be achieved with far fewer observations than conventional approaches. This previous work considered the estimation of direction of arrival and Doppler. Since the targets are sparse in the angle-velocity space, target information can be extracted by solving an ¿1 minimization problem. In this paper, the range information is exploited by introducing step frequency to MIMO radar with CS. The proposed approach is able to achieve high range resolution and also improve the ambiguous velocity. However, joint angle-Doppler-range estimation requires discretization of the angle-Doppler-range space which causes a sharp rise in the computational burden of the ¿1 minimization problem. To maintain an acceptable complexity, a technique is proposed to successively estimate angle, Doppler and range in a decoupled fashion. The proposed approach can significantly reduce the complexity without sacrificing performance.
Keywords :
Doppler radar; MIMO radar; computational complexity; direction-of-arrival estimation; radio networks; Doppler radar; MIMO radar systems; ambiguous velocity; angle-Doppler-range estimation; angle-doppler-range estimation; angle-velocity space; compressive sensing; computational complexity; direction of arrival estimation; step frequency; wireless network; Direction of arrival estimation; Doppler radar; Frequency; Image coding; MIMO; Radar antennas; Radar imaging; Receiving antennas; Signal resolution; Spatial resolution;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signals, Systems and Computers, 2009 Conference Record of the Forty-Third Asilomar Conference on
Conference_Location :
Pacific Grove, CA
ISSN :
1058-6393
Print_ISBN :
978-1-4244-5825-7
Type :
conf
DOI :
10.1109/ACSSC.2009.5469995
Filename :
5469995
Link To Document :
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