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Proceedings Paper

Regularization theory-based interpretation and modification of the minimum variance distortionless response beamformer for extended object imaging
Author(s): Yuri V. Shkvarko
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Paper Abstract

A new regularization theory-based approach to the problem of development of a high resolution spatial spectral analysis technique for extended object imaging is addressed. The technique exploits the idea of combining the modified minimum variance distortionless response beam forming algorithm and regularization methodology for radar/sonar remote sensing imaging optimal/suboptimal in a fused regularization-experiment design setting. The generic spatial power spectrum distribution estimation problem is conceptualized as an ill-posed inverse problem and reformulated in the terms of a descriptive regularization problem. By matching the designed augmented cost function with prior information on the degrees of freedom" of an array imaging experiment, the modified imaging technique is derived, and the iterative spatial power spectrum distribution estimation (image improvement) algorithm is developed for computational efficiency of implementation. Keywords: beamformer, extended object, spatial spectrum, experiment design, regularization, image restoration.

Paper Details

Date Published: 5 July 1995
PDF: 12 pages
Proc. SPIE 2484, Signal Processing, Sensor Fusion, and Target Recognition IV, (5 July 1995); doi: 10.1117/12.213026
Show Author Affiliations
Yuri V. Shkvarko, Kharkov Polytechnical Institute (Ukraine)


Published in SPIE Proceedings Vol. 2484:
Signal Processing, Sensor Fusion, and Target Recognition IV
Ivan Kadar; Vibeke Libby, Editor(s)

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