Abstract
Target tracking in Wireless Sensor Networks is often not limited to the target discovery and computation of the target trajectory. In some cases, it may be required to intercept the target. The tracking information is used to guide a vehicle towards the target. This is referred to as the “Guided Navigation” problem. This paper presents a mechanism that uses Kalman filter based target state prediction and adaptive velocity of the guided object to intercept the target, using a hierarchical clustered wireless sensor network architecture. The use of adaptive velocity is different from earlier mechanisms, such as the Current Location based Guidance (CLG) and α-β Predicted Proportional based guidance (ABG) algorithms, which use fixed velocity of the guided object. Simulation modeling based experiments were conducted for varying network field sizes with a random sensor deployment. The results show that the proposed algorithm can intercept the target earlier (approx. 25% reduction in intercept time) when compared to the existing algorithms.
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Deshpande, S., Sivalingam, K.M. (2012). Adaptive Velocity Based Guided Navigation in Wireless Sensor Networks. In: Bononi, L., Datta, A.K., Devismes, S., Misra, A. (eds) Distributed Computing and Networking. ICDCN 2012. Lecture Notes in Computer Science, vol 7129. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25959-3_18
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DOI: https://doi.org/10.1007/978-3-642-25959-3_18
Publisher Name: Springer, Berlin, Heidelberg
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