Sequential Greedy Localization in Wireless Sensor Networks With Inaccurate Anchor Positions

In this paper, we consider the range-based sensor network localization with inaccurate anchor position information. First, a novel optimization algorithm named sequential greedy optimization (SGO) algorithm is proposed, and then two distributed localization algorithms are obtained: the first is obtained by applying the SGO algorithm to a convex formulation of the localization problem, named CSGLA; while the second is obtained by applying the SGO algorithm to a nonconvex formulation of the localization problem, named NCSGLA. The CSGLA must converge globally while the NCSGLA may converge locally. Both algorithms are partially asynchronous and can be implemented in a distributed fashion in networks. We demonstrate the localization performance via simulations. Simulation results show that, 1) the CSGLA algorithm works faster than the synchronous algorithm with the same localization accuracy; 2) with a reasonably good initialization, the NCSGLA can work much better than the CSGLA.