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Proceedings Paper

Resolving the ambiguities due to spatial undersampling in wideband uniform linear arrays
Author(s): Alireza Shapoury; Costas N. Georghiades
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Paper Abstract

In array signal processing in general, we often wish to fuse the collected data at several sensor elements and implement a given estimation or detection task. This study is a selective treatment of the wideband array processing under some specific assumptions. Shannon Spatial Sampling Limit defines an upper bound for the frequency of transmission given certain element spacings in arrays. Beyond this bound, the exceeded ambiguity, due to spatial aliasing, avoids correct estimation of the signal parameters -e.g. the Direction Of Arrival (DOA), which is of our interest in this study. In another vein, decreasing the element spacing to meet a wider spectral support is difficult to implement due to the electromagnetic mutual coupling of the sensor elements in the array and the reduction of the resolution. This work is an attempt to develop a methodology for resolving this ambiguity or aliasing in the wideband scenario using statistical signal processing. Our approach is heuristic. We consider known implementations, adopt them to meet our scenario and then analyze the performance of our proposed method. Although the models and the formulations presented in this survey can be further generalized, we limit our discussion mainly to the Uniform Linear Arrays (ULA). Many of the topics discussed in this study have a potential for being useful in practical applications, since they would allow a realistic modeling and offer more flexibility than the conventional array processing framework, hence we believe that there are already sufficient interest in this study.

Paper Details

Date Published: 20 January 2005
PDF: 12 pages
Proc. SPIE 5655, Multispectral and Hyperspectral Remote Sensing Instruments and Applications II, (20 January 2005); doi: 10.1117/12.580718
Show Author Affiliations
Alireza Shapoury, Texas A&M Univ. (United States)
Costas N. Georghiades, Texas A&M Univ. (United States)

Published in SPIE Proceedings Vol. 5655:
Multispectral and Hyperspectral Remote Sensing Instruments and Applications II
Allen M. Larar; Makoto Suzuki; Qingxi Tong, Editor(s)

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