Indoor Security Localization Algorithm Based on Location Discrimination Ability of AP

Abstract

Indoor localization algorithm based on WIFI has attracted much attention due to its high localization accuracy, universal applicability and no need for additional equipment. However, when the indoor environment changes dynamically, the environment has different degrees of influence on access points (APs) communication in different regions. The traditional fingerprint localization algorithm cannot take into account the situation of abnormal received signal strength indication (RSSI) in different areas. This paper proposes an indoor security localization algorithm based on location discrimination ability of AP (SLABLDA), which is robust to indoor complex abrupt environments. In the offline detection phase, the AP location discrimination ability detection model is proposed to detect the location discrimination ability of AP in different regions in indoor complex abrupt environment. In the online phase, a fingerprint distance adjustment algorithm based on the minimum difference of RSSI is proposed to eliminate the abnormal RSSI interference caused by the regional dynamic environment. Through experiments we demonstrate the proposed method can effectively filter the influence of abnormal RSSI in indoor complex abrupt environment and can improve the localization accuracy effectively compared with the existing fingerprint localization algorithm.