The WiFi-based Location Algorithm Research And Implementation

With the explosive growth in the number and technology of the global positioning satellite at the end of 20 th centuries, GPS(Which is short for Global Positioning System) develops rapidly in Car Navigation, satisfying civilian demand of road location service.For the recent years, the development of the short-range wireless communication technology get a rapid growth, wireless network is spreading to every corner of the ci ty life, while the application scenarios and demands for wireless network increased m ore. Meanwhile, the behalf of the mobile terminal such as the smart phones, tablet, laptop are in rapid development provide a good user base of the development of wireless networks, and also make wireless network application more widely. In the wireless network applications, the location services are used most frequency, and gradually become one of the most wide range of services, the GPS and cellular wireless communication have met the intelligent terminal user's location in outdoor service requirements, it makes the research and development of location services for the indoor environment on the agenda, and become the hotspot research in the field of wireless services. With the demand of users for indoor location service, the research of this paper is in the background of the rapid development of wireless network technology in recent years, and the Wireless Fidelity coverage are more and more widely.The main study of the author are as follows:1. Researched the characteristics of different indoor positioning technologies, divided the common indoor positioning technology as the positioning technology based on direct measurements and the positioning technology based on indirect measurements, And depth studied the key positioning technology of positioning based on direct measurement. 2. Proposed the first filter based on Grubbs criteria and the secondary algorithm based on kalman filter. In view of the RSSI sampling signal processing, divided the error of RSSI sampling signals as three classes: gross error, random error and systematic error. Removed the gross error through Grubbs criteria, and reduced the random error through kalman filter. 3. This thesis established a sub-channel model based on channel parameter updates. According to the indoor RSSI attenuation characteristics, studied RSSI with distance, time, obstacle attenuation curve. Meanwhile, we studied differentchannel models. By comparing field measurements of comparative data and fitting channel parameters established channel segmentation model based on channel parameter update. 4. This thesis proposed secondary channel localization algorithm based on the model parameter updates, and designed and implied Wi Fi-based indoor positioning smar t android terminal system and secondary positioning algorithm. According to the c oordinate positioning algorithm, I put coordinate positioning algorithm based on d irect measurements of positioning as the initial localization algorithm, and choose precise positioning algorithm based on segment channel model as a secondary loc ation algorithm.This thesis proposed an idea that comes from RSSI sampling for si gnal processing, RSSI indoor channel model establishment, and coordinate positio ning algorithm. And then, achieve a Wi Fi indoor positioning system. And through this system and the algorithms above, results has been tested and the analyzed.