Indoor 3-D localization based on simulated annealing bat algorithm

Abstract

The non-line of sight (NLOS) propagation caused by the building shielding and background interference will lead to large error when applying Ultra-Wideband (UWB) technology to indoor positioning. In order to reduce the positioning error, a joint simulated annealing algorithm and a bat algorithm is proposed in the paper. First, based on the Bat Algorithm (BA), transform the problem of the target into the problem of difference between the estimated position and the actual position to establish an iterative optimization model. Then introduce random perturbation factor to improve the search ability of the bat individual; Aiming at BA is easy to fall into local optimum, a Simulate Anneal (SA) algorithm is integrated to improve the classification and search ability of the algorithm. Finally, we use Chan-Taylor algorithm to determine the accurate position of the target. The research result shows that proposed algorithm improves positioning accuracy by 11∼23cm which can effectively improve the positioning accuracy of the positioning algorithm under the LOS/NLOS environment.