Feedback Mechanism Based Dynamic Fingerprint Indoor Localization Algorithm in Wireless Sensor Networks

In location fingerprint based indoor localization system, the received signal strength (RSS) from a set of Wi-Fi access points are used as a unique fingerprint to identify a specific location. However, indoor environment is much more complex and changeable compared to outdoor environment, which leads to larger localization error brought by outdated RSS fingerprints. And re-measuring RSS fingerprints for all locations to maintain a dynamically changing fingerprint database will cause high cost and complexity. To solve this problem, this paper proposes a feedback mechanism based dynamic fingerprint indoor localization algorithm called FMDFLA, it makes RSS fingerprint update timely to cope with changes in the indoor environment. FMDFLA adds distance between grids matrix in offline database which used for scope judgment in online phase. In online phase, we update fingerprint to obtain the “update-point” and “non-update-point”, feedback the RSS of “update-point” to “non-update-point” by using specific method. Furthermore, we update fingerprint for a number of times to obtain the best result of localization. Simulation results show that the localization accuracy and the stability of FMDFLA are higher than traditional CS based localization algorithm and fingerprint localization algorithm in dynamic indoor environment.

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