Paper
10 June 1996 Three-dimensional target feature extraction via interferometric SAR
Jian Li, Zheng-She Liu, Peter Stoica
Author Affiliations +
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.
© (1996) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jian Li, Zheng-She Liu, and Peter Stoica "Three-dimensional target feature extraction via interferometric SAR", Proc. SPIE 2757, Algorithms for Synthetic Aperture Radar Imagery III, (10 June 1996); https://doi.org/10.1117/12.242028
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KEYWORDS
Interferometric synthetic aperture radar

3D acquisition

Radar

Feature extraction

Data modeling

Synthetic aperture radar

Fourier transforms

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