Indoor Wireless Localization Using Kalman Filtering in Fingerprinting-based Location Estimation System

As “smart” devices such as smart phone and smart TVs become widely distributed, various studies on location-based services have been conducted. Such location-based services are useless, however, unless the user’s location is known. A number of researchers have examined methods to trace and determine indoor locations for indoor location-based services. In particular, WALN has been examined in various studies because of its advantage to use a frequency band available without advanced settings. This study suggests a new indoor tracing method to reduce time delays upon location fingerprinting for point data collection, which is a disadvantage of the existing Kalman filtering algorithm and fingerprinting type location tracing algorithm. This study also compares its performance with that of existing methods based on the collected data. As a result of the experiment, the fast collection algorithm is presented as a solution to the problems of existing methods. It is proven that the fast collection algorithm presented in this study is applicable to a location tracing system in an actual environment.