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Proceedings Paper

Fusion of imaging data and auxiliary signal for target classification
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Paper Abstract

Fusion of imaging data with auxiliary signal such as EW data for multitarget classification poses daunting theoretical and practical challenges. The problem is exacerbated by issues such as asynchronous data flow, uneven feature quality and object occlusion. In our approach, we assign prior probabilities to image and signal feature elements to handle those practical issues in a unified manner. Current state and class probability distributions estimated from previous instances are fused with new outputs from individual classifiers immediate after the outputs become available to establish updated state and class probability distributions in a Bayesian framework. Results are presented that demonstrate joint segmentation and tracking, target classification using imaging data, and fusion of imaging data with noisy and asynchronous auxiliary EW information under realistic simulation scenarios.

Paper Details

Date Published: 20 June 2014
PDF: 11 pages
Proc. SPIE 9091, Signal Processing, Sensor/Information Fusion, and Target Recognition XXIII, 90910G (20 June 2014); doi: 10.1117/12.2050652
Show Author Affiliations
Aleksandar Zatezalo, Scientific Systems Co., Inc. (United States)
Ssu-Hsin Yu, Scientific Systems Co., Inc. (United States)


Published in SPIE Proceedings Vol. 9091:
Signal Processing, Sensor/Information Fusion, and Target Recognition XXIII
Ivan Kadar, Editor(s)

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