DocumentCode
2437163
Title
MIMO field directionality estimation using orientation-diverse linear arrays
Author
Hickman, Granger ; Krolik, Jeffrey L.
Author_Institution
Dept. of Electr. & Comput. Eng., Duke Univ., Durham, NC, USA
fYear
2009
fDate
1-4 Nov. 2009
Firstpage
146
Lastpage
150
Abstract
This paper addresses the estimation of power versus azimuth and elevation using a sparse sensor array. In MIMO radar, clutter and noise field directionality can be measured both from the transmit array and to the receive array. In applications where sparse arrays must be used, however, often substantial ambiguities in the field directionality map occur due to spatial under-sampling and/or sidelobe leakage. In this paper, we propose an alternative field-directionality mapping approach which incoherently combines the outputs of several uniform linear arrays with different orientations. The proposed orientation-diverse multi-line array (ODMA) treats the 1-D field directionality estimate from each line array as a projection of a 2-D spatial spectrum. Two methods for reconstruction from these projections are presented: 1) least-squares estimation subject to a positivity constraint, and 2) maximum likelihood estimation using the EM algorithm. Simulation results suggest both methods achieve ODMA field directionality maps with improved ambiguity resolution and sidelobe performance versus conventional beamforming techniques.
Keywords
MIMO radar; maximum likelihood estimation; noise; radar clutter; 2D spatial spectrum; EM algorithm; MIMO field directionality estimation; MIMO radar; ambiguity resolution; clutter measurement; field directionality map; field-directionality mapping approach; least-squares estimation; maximum likelihood estimation; noise field directionality measurement; orientation-diverse linear arrays; orientation-diverse multiline array; positivity constraint; power estimation; receive array; sidelobe leakage; sidelobe performance; sparse sensor array; spatial under-sampling; transmit array; Apertures; Array signal processing; Azimuth; Frequency estimation; MIMO; Maximum likelihood estimation; Radar applications; Radar clutter; Radar measurements; Sensor arrays;
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.2009.5470146
Filename
5470146
Link To Document