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Proceedings Paper

Three-dimensional target feature extraction via interferometric SAR
Author(s): Jian Li; Zheng-She Liu; Peter Stoica
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Paper Abstract

This paper considers 3D target feature extraction via an interferometric synthetic aperture radar (IFSAR). Since IFSAR itself is a relatively new technology, a self- contained detailed derivation of the data model is presented. A set of sufficient parameter identifiability conditions of the data model and the Cramer-Rao bounds (CRBs) of the parameters estimates are also derived. Four existing 2D feature extraction methods are extended to estimate the 3D parameters of the target scatterers. A new non-linear least squares (NLS) parameters estimation method is also derived to extract the target features. Finally, numerical examples are presented to compare the performance of the presented methods with each other and with the corresponding CRBs. We show with numerical examples that among the three non-parametric methods, Capon has the best resolution. The parametric methods (MUSIC and NLS) can have much better resolution and provide much more accurate parameter estimates than the non-parametric methods. We also show that between the two parametric methods, NLS can be faster and provide much better parameter estimates than MUSIC.

Paper Details

Date Published: 10 June 1996
PDF: 16 pages
Proc. SPIE 2757, Algorithms for Synthetic Aperture Radar Imagery III, (10 June 1996); doi: 10.1117/12.242028
Show Author Affiliations
Jian Li, Univ. of Florida (United States)
Zheng-She Liu, Univ. of Florida (United States)
Peter Stoica, Uppsala Univ. (Sweden)


Published in SPIE Proceedings Vol. 2757:
Algorithms for Synthetic Aperture Radar Imagery III
Edmund G. Zelnio; Robert J. Douglass, Editor(s)

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