Performance Analysis of the New Filtering Algorithm with Kalman on Indoor Positioning System

Location-based service (LBS) is a context-aware service, which has an awareness of its surroundings. An accurate user positioning system is required for LBS. Indoor Positioning System (IPS) is essential for LBS to determine user position in an indoor environment. The new filtering algorithm increases the accuracy of IPS, but it does not consider the fluctuation of the received signal strength index (RSSI) values, which affects the prediction results. This research describes an accuracy and performance analysis of the new filtering algorithm with Kalman filter, which is used to process the fluctuation of the test signals. The experimental result shows that the proposed method increases the positioning accuracy and computational time by as much as 0.4% and eight milliseconds, respectively than the existing method. This has made it applicable in most environments.