Coordinate correction algorithm for WLAN indoor positioning

In the fingerprint matching-based wireless local area network (WLAN) indoor positioning system, Kalman filter (KF) is usually applied after fingerprint matching algorithms to make positioning results more accurate and consecutive. But this method, like most methods in WLAN indoor positioning field, fails to consider and make use of users' moving speed information. In order to make the positioning results more accurate through using the users' moving speed information, a coordinate correction algorithm (CCA) is proposed in this paper. It predicts a reasonable range for positioning coordinates by using the moving speed information. If the real positioning coordinates are not in the predicted range, it means that the positioning coordinates are not reasonable to a moving user in indoor environment, so the proposed CCA is used to correct this kind of positioning coordinates. The simulation results prove that the positioning results by the CCA are more accurate than those calculated by the KF and the CCA is effective to improve the positioning performance.