SAR based classification of ground moving targets to assist vehicle tracking

G. Steven Goley; Brian Rigling; Adam R. Nolan

doi:10.1117/12.2018186

3 June 2013 SAR based classification of ground moving targets to assist vehicle tracking

G. Steven Goley, Brian Rigling, Adam R. Nolan

Proceedings Volume 8746, Algorithms for Synthetic Aperture Radar Imagery XX; 87460H (2013) https://doi.org/10.1117/12.2018186
Event: SPIE Defense, Security, and Sensing, 2013, Baltimore, Maryland, United States

Abstract

Feature-aided tracking of targets in synthetic aperture radar is a topic of increasing interest. The aperture synthesized through the combination of target and platform motion facilitates the application of two-dimensional target recognition algorithms through noncooperative imaging of the target in question. Many non-parametric inverse synthetic aperture radar imaging techniques maximize image sharpness by estimating the phase error imposed by the unknown target motion. The resultant images can suffer from small unresolved phase errors and ambiguous cross range resolution. Downstream image exploitation algorithms must be robust to these effects. A set of civilian vehicles is investigated, which exacerbates image quality based ISAR algorithms due to their comparatively small radar cross section. This paper addresses the feasibility of peak-based classifcation of civilian targets moving through challenging tracking scenarios using ISAR images. Classifier performance is evaluated over a set of sensor, target, and environmental operating conditions through use of synthetically generated data.

Citation Download Citation

G. Steven Goley, Brian Rigling, and Adam R. Nolan "SAR based classification of ground moving targets to assist vehicle tracking", Proc. SPIE 8746, Algorithms for Synthetic Aperture Radar Imagery XX, 87460H (3 June 2013); https://doi.org/10.1117/12.2018186

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KEYWORDS

Synthetic aperture radar

Distortion

Sensors

Detection and tracking algorithms

Radar

Error analysis

Image quality

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