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|Title:||Energy-Efficient Distributed Signal Processing in Mobile Wireless Sensor Networks|
|Citation:||Proceedings of the 4th International Conference on Performance Evaluation Methodologies and Tools vol. 1|
|Publisher:||Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering - ICST|
|Type:||Articles in periodicals and books|
|Abstract:||Wireless mobile sensor networks are important for a number of strategic applications such as surveillance, fire detection, outlier detection. Energy is a critical resource in wireless sensor networks and system lifetime needs to be prolonged through the use of energy-efficient signal processing during system operation. We present an overview of statistical prediction frameworks for tracking dynamic targets in range-based signal processing. The single mobile target algorithm has been evaluated by the metrics of tracking precision and network energy consumption. We consider the computation of the posterior Cramer-Rao bound (PCRB) for range-based target tracking. PCRB is a theoretical lower bound on the estimation error while assessing the performance of any kind of estimation algorithm. Here the method is applied to a nonlinear filtering problem of tracking node in wireless sensor networks. The evaluation is performed using the constant velocity model and the path loss propagation model, respectively, as dynamic model and measurement model. The bound is computed against the root mean square error of two non linear filters: bootstrap and unscented particle filter. We show a novel tradeoff between the accuracy of the estimation bound and the energy consumption.|
|JRC Directorate:||Space, Security and Migration|
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