Share Email Print

Proceedings Paper

Fourier descriptors for parametric shape estimation in inverse scattering problems
Author(s): Jong Chul Ye; Yoram Bresler; Pierre Moulin
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

We present new methods for computing fundamental performance limits for parametric shape estimation in inverse scattering problems, such as passive radar imaging. We evaluate Cramer- Rao lower bounds (CRB) on shape estimation accuracy using the domain derivative technique from nonlinear inverse scattering theory. The CRB provides an unbeatable performance limit for nay unbiased estimator, and under fairly mild regularity conditions, is asymptotically achieved by the maximum likelihood estimator (MLE). Furthermore, the resultant CRBs are used to define a global confidence region, centered around the true boundary, in which the boundary estimate lies with a prescribed probability. These global confidence regions conveniently display the uncertainty in various geometric parameters such as shape, size, orientation, and position of the estimated target, and facilitate geometric inferences. Numerical simulations are performed using the layer approach and the Nystrom method for computation of domain derivatives, and using Fourier descriptors for target shape parameterization. This analysis demonstrates the accuracy and generality of the proposed methods.

Paper Details

Date Published: 4 August 2000
PDF: 12 pages
Proc. SPIE 4052, Signal Processing, Sensor Fusion, and Target Recognition IX, (4 August 2000); doi: 10.1117/12.395082
Show Author Affiliations
Jong Chul Ye, Univ. of Illinois/Urbana-Champaign (United States)
Yoram Bresler, Univ. of Illinois/Urbana-Champaign (United States)
Pierre Moulin, Univ. of Illinois/Urbana-Champaign (United States)

Published in SPIE Proceedings Vol. 4052:
Signal Processing, Sensor Fusion, and Target Recognition IX
Ivan Kadar, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?