Research And Implementation On Indoor Positioning Technology Based On Wlan Location Fingerprint

In recent years, with the rapid development of wireless communication technology and the increasing popularity of mobile devices, a variety of indoor environment has become increasingly urgent demand for location-based services Interior is the most intensive human activities and the longest stay of the occasion, there is an urgent need to achieve positioning indoor environment, navigation and surveillance personnel supplies a full range of intelligent ubiquitous services. Therefore, indoor location-based services environment there are a lot of applications and broad application space. WLAN Fingerprint indoor location technology has become a hot research indoor positioning technology in recent years, because of its simple equipment, high positioning accuracy. This topic has been studied and mainly completed the following tasks:First, there is a lot of interference factors for the indoor environment of the received signal strength RSSI volatile issues raised by pretreatment of RSSI Kalman filter algorithm, which effectively eliminate random noise, reproduction system status. Experimentally determined optimal parameter values of the Kalman filter.Secondly, the Kalman filter algorithm transitions occur when the RSSI for the slow convergence of the problem, an improved Kalman filter algorithm can take advantage of previous observations RSSI quickly determine whether the occurrence of RSSI jump, and there RSSI transition occurs, modify the relevant parameters Kalman filter algorithm, reducing algorithm for the state transition occurs before the estimated value of recognition, thereby improving the algorithm in the case of the occurrence of RSSI jump convergence rate, RSSI estimation error is reduced Experiments demonstrate the effectiveness of the improved algorithm.Third, when a large range for positioning algorithm computation larger issues we propose a matching algorithm based on zoning and AP ID filtering. The algorithm is through zoning and AP ID filter to locate within a larger area of the lower value of the position of the majority of fingerprint reference filter to narrow the scope of fingerprint matching, and then using the recently identified a more precise estimate of the position of neighbor, thus, matching the positioning process greatly reduced the amount of computation to improve the positioning speed.Fourth, in order to improve the positioning algorithm for real-time moving target tracking capability, reduce positioning errors, we present a moving target indoor Kalman filter-based real-time positioning algorithm, which is estimated by the position of the matching algorithm was subjected to Karl filtering process, the greatest degree of positioning results close to the real trajectory. Experiments demonstrate the effectiveness of the algorithm.Fifth, the use of modular design concept, design and implementation of an authentication WLAN fingerprint-based indoor location positioning system software providing a platform for researching and improving positioning algorithm, joining the adaptive Kalman filtering algorithm based matching algorithm zoning and AP ID filtering. The software localization experiments conducted to verify the effectiveness of the proposed algorithm, but also proved that the software has a good positioning performance.