A RSS based statistical localization algorithm in WLAN

With the proliferation of location based services (LBS), various indoor localization techniques have been explored based on received signal strength (RSS). To improve performance, many algorithms and techniques have been proposed in the literature. In this paper, a new RSS based statistical location algorithm is proposed to achieve better localization performance, with a focus on statistical analysis and reasoning in wireless local area network (WLAN). Experimental results demonstrate our proposed algorithm outperforms and more than 20 percent reduction in root mean square error (RMSE) has been achieved, through comparisons with some other existing algorithms. Moreover, it has also been verified that number of training locations can be reduced without too much performance degradation.

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