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Open Access Publications from the University of California

Distributed Gauss-Newton Methodology for Node Localization in Wireless Sensor Networks


We present distributed algorithms for sensor localization based on the Gauss-Newton method. Each sensor updates its estimated location by computing the Gauss-Newton step for a local cost function and choosing a proper step length. Then it transmits the updated estimate to all the neighboring sensors. The proposed algorithms provide non-increasing values of a global cost function. It is shown in the paper that the algorithms have computational complexity of O(n) per iteration and a reduced communication cost over centralized algorithms.

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