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9 April 2007 Multi-sensor detection and fusion technique
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Abstract
A multi-sensor detection and fusion technology is described in this paper. The system consists of inputs from three sensors, Infra Red, Doppler Motion, and Stereo Video. The technique consists of three processing parts corresponding to each sensor data, and a fusion module, which makes the final decision based on the inputs from the three parts. The signal processing and detection algorithms process the inputs from each sensor and provides specific information to the fusion module. The fusion module is based on the bayes belief propagation theory. It takes the processed inputs from all of the sensor modules and provides a final decision for the presence and absence of objects, as well as their reliability based on the iterative belief propagation algorithm operating on decision graphs. This choice of sensors is designed to give high reliability. The infra red and Doppler provide detection ability at night, while stereo video has the ability to analyze depth and range information. The combination of these sensors has the ability to provide a high probability of detection and a very low false alarm rate. A prototype system was built using this technique to study the feasibility of intrusion detection for NASA's launch danger zone protection. The system verified the potential of the proposed algorithms and proved the feasibility of high probability of detection and low false alarm rates compared to many existing techniques.
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Ashish Bhargave, Barry Ambrose, Freddie Lin, and Manthos Kazantzidis "Multi-sensor detection and fusion technique", Proc. SPIE 6571, Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2007, 657109 (9 April 2007); https://doi.org/10.1117/12.719505
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