Share Email Print

Proceedings Paper

Choice of an entropy-like function for range-Doppler processing
Author(s): Benjamin C. Flores; Alberto Ugarte; Vladik Kreinovich
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

Motion compensation of range-Doppler target signatures results in focused target imagery. Recently, an iterative approach based on a logarithmic entropy measure has been proposed for the motion compensation of signatures collected in the frequency domain. The effectiveness of this approach can be significantly improved by using an entropy-like function which is maximally resistant to noise and consistent with statistical boundaries. For purposes of analysis, the entropy-like function is written in terms of an information gain function (Delta) I. Several expressions for (Delta) I are tested to verify the accuracy of radial-motion parameter estimation. The effectiveness of these expressions is determined by the number of iterations required to find the minimum entropy measure, within an acceptable tolerance level for a given signal-to-noise ratio. Results show that the exponential information gain (Delta) I equals exp(1-I) yields an optimally convex entropy measure surface over a prescribed motion- parameter solution space. The surface minimum in this solution space has coordinates which are interpreted as the optimum motion-parameter estimates that can be obtained for the purpose of image focusing.

Paper Details

Date Published: 15 October 1993
PDF: 10 pages
Proc. SPIE 1960, Automatic Object Recognition III, (15 October 1993); doi: 10.1117/12.160625
Show Author Affiliations
Benjamin C. Flores, Univ. of Texas/El Paso (United States)
Alberto Ugarte, Univ. of Texas/El Paso (United States)
Vladik Kreinovich, Univ. of Texas/El Paso (United States)

Published in SPIE Proceedings Vol. 1960:
Automatic Object Recognition III
Firooz A. Sadjadi, Editor(s)

© SPIE. Terms of Use
Back to Top