Many wireless sensor network (WSN) applications require location information of targets, which motivates a variety of positioning algorithms. Due to limited power of wireless sensor nodes, energy consumption is one of the crucial factors in designing positioning algorithms for WSNs. Accordingly, decentralized approaches that exploit sensors to share information only with their neighbors have been proposed to increase the energy efficiency.
In this thesis, we propose a novel positioning scheme based on the minimization of a recursive-in-time cost function for WSNs. Due to the recursive operation feature, the proposed positioning scheme is easily realized in an iterative decentralized manner. Specifically, the target location is computed iteratively by taking a weighted average of the local observations according to the sensor nodes’ reliabilities, where a sensor node computes a location estimate of the target in terms of its own observation and the previous location estimate at each iteration. The new location estimate is sent to the next sensor node for updating, and the updating process is circulated among sensors in the close vicinity of the target. Computer simulation results show that the proposed recursive weighted least-squares (RWLS) scheme outperforms previous related methods in terms of the location accuracy.

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