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Proceedings Paper

Sample selection and adaptive weight allocation for compressive MIMO UWB noise radar
Author(s): Yangsoo Kwon; Ram M. Narayanan; Muralidhar Rangaswamy
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Paper Abstract

In this paper, we propose a sample selection method for compressive multiple-input multiple-output (MIMO) ultra-wideband (UWB) noise radar imaging. The proposed sample selection is based on comparing norm values of the transmitted sequences, and selects the largest M samples among N candidates per antenna. Moreover, we propose an adaptive weight allocation which improves normalized mean-square error (NMSE) by maximizing the mutual information between target echoes and the transmitted signals. Further, this weighting scheme is applicable to both sample selection schemes, a conventional random sampling and the proposed selection. Simulations show that the proposed selection method can improve the multiple target detection probability and NMSE. Moreover, the proposed weight allocation scheme is applicable to those selection methods and obtains spatial diversity and signal-to-noise ratio (SNR) gains.

Paper Details

Date Published: 8 June 2012
PDF: 11 pages
Proc. SPIE 8365, Compressive Sensing, 83650T (8 June 2012); doi: 10.1117/12.920937
Show Author Affiliations
Yangsoo Kwon, The Pennsylvania State Univ. (United States)
Ram M. Narayanan, The Pennsylvania State Univ. (United States)
Muralidhar Rangaswamy, Air Force Research Lab. (United States)


Published in SPIE Proceedings Vol. 8365:
Compressive Sensing
Fauzia Ahmad, Editor(s)

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