Fusion of imaging data and auxiliary signal for target classification

Aleksandar Zatezalo; Ssu-Hsin Yu

doi:10.1117/12.2050652

20 June 2014 Fusion of imaging data and auxiliary signal for target classification

Aleksandar Zatezalo, Ssu-Hsin Yu

Proceedings Volume 9091, Signal Processing, Sensor/Information Fusion, and Target Recognition XXIII; 90910G (2014) https://doi.org/10.1117/12.2050652
Event: SPIE Defense + Security, 2014, Baltimore, MD, United States

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.

Citation Download Citation

Aleksandar Zatezalo and Ssu-Hsin Yu "Fusion of imaging data and auxiliary signal for target classification", Proc. SPIE 9091, Signal Processing, Sensor/Information Fusion, and Target Recognition XXIII, 90910G (20 June 2014); https://doi.org/10.1117/12.2050652

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