Indoor Track Positioning Model Based on WiFi Fingerprint
As one of the most promising indoor positioning technologies, the WiFi-based fingerprinting model has attracted much research attention in recent years. However,most of the existing studies mainly focus on the single point positioning method,while in the actual applications,it often needs to track the object trajectory. Hence, in this paper, the Hidden Markov Model ( HMM ) based on kernel function is presented, which is on the basis of the single-point positioning model. The Gaussian kernel function is used to calculate the likelihood between fingerprints. The transition probability is defined and the search range is limited by a threshold value, which can improve the efficiency of the algorithm. HMM is applied to the track positioning. Experimental result shows that the proposed algorithm outperforms the benchmark algorithms significantly on both of the precision and distance measures.
indoor positioningfingerprint positioningtrack positioningHidden Markov Model(HMM)kernel function
国家科技期刊平台
NSTL
万方数据
维普
