Regularization theory-based interpretation and modification of the minimum variance distortionless response beamformer for extended object imaging

Yuri V. Shkvarko

doi:10.1117/12.213026

5 July 1995 Regularization theory-based interpretation and modification of the minimum variance distortionless response beamformer for extended object imaging

Yuri V. Shkvarko

Author Affiliations +

Proceedings Volume 2484, Signal Processing, Sensor Fusion, and Target Recognition IV; (1995) https://doi.org/10.1117/12.213026
Event: SPIE's 1995 Symposium on OE/Aerospace Sensing and Dual Use Photonics, 1995, Orlando, FL, United States

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.

Citation Download Citation

Yuri V. Shkvarko "Regularization theory-based interpretation and modification of the minimum variance distortionless response beamformer for extended object imaging", Proc. SPIE 2484, Signal Processing, Sensor Fusion, and Target Recognition IV, (5 July 1995); https://doi.org/10.1117/12.213026

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available