JOURNAL ARTICLE

Automatic ground target classification using forward scattering radar

Abstract

Experimental study is undertaken of the feasibility of forward scattering radar (FSR) and its application to automatic ground target classification. The radar itself, fundamental theoretical analysis, target recognition algorithm and the target's classification subsystem are introduced. For target recognition, the effect of shadow inverse synthetic aperture radar is used. The radar experimental set-up and experimentation results are discussed. For classification, a system is proposed, which extracts features from the radar measurements by using Fourier transform and principle component analysis and uses a nearest neighbour classifier. Speed estimation in FSR is also introduced. By analysing 850 experimentally obtained car signatures, the performance of the system is evaluated and the effectiveness of the system is confirmed. The limitations of the work and its future are also discussed.

Keywords:
Inverse synthetic aperture radar Computer science Radar Artificial intelligence Synthetic aperture radar Radar systems Radar imaging Classifier (UML) Remote sensing Fourier transform Pattern recognition (psychology) Automatic target recognition Computer vision Mathematics Geology Telecommunications

Metrics

104
Cited By
14.20
FWCI (Field Weighted Citation Impact)
19
Refs
1.00
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Advanced SAR Imaging Techniques
Physical Sciences →  Engineering →  Aerospace Engineering
Geophysical Methods and Applications
Physical Sciences →  Engineering →  Ocean Engineering
Microwave Imaging and Scattering Analysis
Physical Sciences →  Engineering →  Biomedical Engineering
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