GMM-based localization algorithm under NLOS conditions - Wei CUI; Cheng-dong WU; Yun-zhou ZHANG; Zi-xi JIA; Long CHENG (Tongxin xuebao)
Aiming at indoor node localizations of WSN,a node localization algorithm,where priori-knowledge is not necessary,was proposed.on basis of analyzing the error model,combined with Gaussian mixture model (GMM).By training the distance measurements containing NLOS errors,the more accurate range estimations can be obtained.For higher localization accuracy,the particle swarm optimization (PSO) was introduced to optimize the expectation-maximization (EM)algorithm.Finally,by using the residual weighting algorithm to estimate the distance,the estimation coordinates of target nodes can be determined.The proposed algorithm was proved to be effective through simulation experiments.