A Location Fingerprinting Algorithm Based on RSSI Statistic Parameters Matching Estimate

Abstract

This study focuses on the indoor location system based on radio fingerprinting, and a grid positioning method based on weighted Euclidean distance matching by RSSI statistic parameters is presented in this paper. We analyze the principle of location fingerprint system and study the signal intensity distribution characteristics in indoor environment. According to the unsteadiness problem of the indoor signal strength caused by environmental impact, the positioning parameter model based on distributed grid is given. Moreover, the grid matching location algorithm is put forward based on the RSSI statistic parameters fusion estimation. Attributed to the proposed two-dimensional grid model, the algorithm is fit for the rapid matching calculations in continuous positioning case. Simulation results show that the approach has better robustness and accuracy, and it can effectively solve the problem of location estimates stability in general RSSI location fingerprinting system.