Ad Hoc Sensor Network Localization using Distributed Kernel Regression Algorithms

In this paper we apply distributed kernel regression methods to perform sensor network localization. This follows up on earlier work where a centralized kernel regression algorithm was considered to perform localization. Here we examine the tradeoffs between using distributed algorithms versus centralized algorithms in terms of communication costs, computational costs, and performance of the estimate. Simulation results demonstrate that distributed methods work well with comparable performance to centralized algorithms with less communication costs.