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20 May 2015 Ground target tracking and classification in an unattended wireless sensor network
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In this paper, we address the problem of multiple ground target tracking and classification with data from an unattended wireless sensor network. A multiple target tracking algorithm, taking into account the road and vegetation information, is studied in a centralized architecture. Despite of efficient algorithms proposed in the literature, we must adapt a basic approach to satisfy embedded processing. The algorithm enables tracking human and vehicles driving both on and off road. Based on our previous works, we integrate road or trail width and vegetation cover, in motion model to improve performance of tracking under constraint. Our algorithm also presents different dynamic models, to palliate the maneuvers of targets including a stop motion model. In order to handle realistic ground target tracking scenarios, the tracking algorithm is integrated into an operational platform (named fusion node) which is an autonomous smart computer abandoned in the surveillance area. After the calibration step of the heterogeneous sensor network, our system is able to handle real data from a wireless ground sensor network. The performance of system is evaluated in a real exercise for Forward Operating Base (FOB) protection and road surveillance.
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Benjamin Pannetier, Julien Moras, Jean Dezert, Loic Canevet, and Didier Cosson "Ground target tracking and classification in an unattended wireless sensor network", Proc. SPIE 9464, Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR VI, 94640L (20 May 2015);

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