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Proceedings Paper

Reduced-Dimension Beam-Space Broad-Band Source Localization: Preprocessor Design
Author(s): Kevin M. Buckley; Xiao Liang Xu
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Paper Abstract

Data from a set of conventional beamformers, each steered to a point in location (and frequency), are analyzed in beam-space processing. By selecting a location sector of interest, and by using only those beamformers which are steered within this sector, processing is in a Reduced-Dimension Beam-Space (RDBS). For spatial-spectrum estimation, advantages of processing in a RDBS rather than in element-space include; reduction in data and therefore computation required for spatial-spectral analysis, reduction in resolution thresholds, and attenuation of out-of-sector sources through spatial filtering. A beam-space preprocessor structure provides the element-space to RDBS transfor-mation. For broad-band source processing, its objectives are data reduction, spatial filtering and broad-band source focusing. In this paper we investigate beam-space preprocessor design.

Paper Details

Date Published: 23 February 1988
PDF: 9 pages
Proc. SPIE 0975, Advanced Algorithms and Architectures for Signal Processing III, (23 February 1988); doi: 10.1117/12.948520
Show Author Affiliations
Kevin M. Buckley, University of Minnesota (United States)
Xiao Liang Xu, University of Minnesota (United States)


Published in SPIE Proceedings Vol. 0975:
Advanced Algorithms and Architectures for Signal Processing III
Franklin T. Luk, Editor(s)

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