Degree of Inconsistency: Iterative localization with error control

A novel iterative localization algorithm based on Particle Filter with error control is proposed in this paper. First, each node´s location is estimated by a cloud of particles and their weights. Second, Degree of Inconsistency(DoI) is proposed to detect the nodes with high error. DoI makes full use of the fact that node density is high and they are randomly and uniformly distributed. The nodes with large error could be gradually identified by DoI and their estimated locations are then updated wisely to get higher accuracy. The proposed algorithm only needs local information and it is implemented in a distributive way. Simulation results show that the proposed error control strategy can solve error propagation problem successfully and provide relative high accuracy, especially in network with high ranging error and low beacon density.