SAR ATR performance using a conditionally Gaussian model

Author

O´Sullivan, J.A. ; DeVore, Michael D. ; Kedia, Vikas ; Miller, Michael I.

Author_Institution

Dept. of Electr. Eng., Washington Univ., St. Louis, MO, USA

Volume

37

Issue

1

fYear

2001

fDate

1/1/2001 12:00:00 AM

Firstpage

91

Lastpage

108

Abstract

A family of conditionally Gaussian signal models for synthetic aperture radar (SAR) imagery is presented, extending a related class of models developed for high resolution radar range profiles. This signal model is robust with respect to the variations of the complex-valued radar signals due to the coherent combination of returns from scatterers as those scatterers move through relative distances on the order of a wavelength of the transmitted signal (target speckle). The target type and the relative orientations of the sensor, target, and ground plane parameterize the conditionally Gaussian model. Based upon this model, algorithms to jointly estimate both the target type and pose are developed. Performance results for both target pose estimation and target recognition are presented for publicly released data from the MSTAR program

Keywords

Gaussian distribution; radar imaging; radar resolution; radar target recognition; radar tracking; synthetic aperture radar; target tracking; Hilbert-Schmidt estimator; MSTAR program; SAR imagery; automatic target recognition; coherent combination of returns; complex-valued radar signals; complexity; conditionally Gaussian signal models; confusion matrix; ground plane; relative orientation; target pose; target speckle; target type; Image resolution; Layout; Radar detection; Radar imaging; Radar scattering; Robustness; Signal resolution; Speckle; Synthetic aperture radar; Target recognition;

fLanguage

English

Journal_Title

Aerospace and Electronic Systems, IEEE Transactions on

Publisher

ieee

ISSN

0018-9251

Type

jour

DOI

10.1109/7.913670

Filename

913670