A Novel Wireless Localization Fusion Algorithm: BP-LS-RSSI

With the increasing demand for location-aware services, high-precision indoor positioning play more important role for some applications. People also put forward higher requirements on positioning accuracy. BP neural network as a kind of typical forward neural network has the very strong self learning ability and can approximate any discontinuity of rational function. This paper proposes BP-LS-RSSI localization model, then use the model to fix received signal strength indication (RSSI) values for positioning by the LS algorithm. Since the positioning accuracy do not satisfy the needs by the traditional LS algorithm, we transfer the RSSI values into confidence weights according to the topology of network, then use the weighted least squares (LS) method to further optimize the positioning system. Simulation results show that the proposed algorithm has obvious increase to the positioning accuracy is a feasible localization algorithm. Copyright © 2013 IFSA.