An Indoor Wi-Fi Positioning Method Based on RSS Matrix Relevance

Abstract

According to the time varying of Received Signal Strength (RSS) and the difference of received signal capability among different terminals, which leads to the instability and inaccuracy of Wi-Fi indoor positioning, a novel Wi-Fi positioning method based on RSS matrix correlation is proposed. This method firstly collects Wi-Fi fingerprint data of all reference points in the off-line training stage, constructs an RSS matrix by filtering and sorting the fingerprint data, and records the coordinates of the reference points and the corresponding RSS matrix to establish the off-line location fingerprint database. In the positioning stage, by comparing the RSS matrix correlation between the real-time monitoring and the reference point in the off-line fingerprint database to find the most relevant k reference points, and then estimate the final position of user by weighting centroid algorithm. Experimental results show that this method has better positioning accuracy than the traditional indoor Wi-Fi positioning, and reduce the impact of different terminals on indoor positioning, thus improving the stability of positioning.