Fingerprint Indoor Positioning Technology Based On WiFi

With the rapid development of the global Internet, modern communications, global positioning system(GPS), and indoor GPS signal is weak and the lack of supporting factors such as indoor maps,At the same time due to human activities indoors and gradually expand the radius of the indoor environment more complicated factors, Indoor growing location-aware and location-based services in real demand. Many indoor positioning solutions currently, indoor location solutions based wireless LAN(local Area Network) with low cost, easy maintenance, easy construction and low power consumption. But while the program has a low prevalence of positioning accuracy, low resource utilization equipment, anti-interference ability and pre-built library labor costs and large investment, so this program has been very popular field of study because of that.In this paper, the core content for the study and implementation of indoor positioning technology fingerprint in Wi Fi environments. We will be the following three aspects to optimize the defect: 1. we bring forward two solutions in theory, including the rapid construction of inertial navigation equipment and the attenuation coefficient based on database to enhance the construction speed and reduce construction required information and hardware overhead and human cost problem. 2. We have introduced a series of effective data preprocessing methods to overcome fluctuations in RSSI,improve the accuracy of the status and application experience. 3. In Engineering, We conduct circuit optimization design of Qualcomm official reference design board DB120,then we transplant the Open Wrt system to the that platform while optimize the driver layer packet filtering, so as to realize the efficient real-time acquisition device of received signal strength, at last we modified the control layer to reduce the viscosity of the best environment to ensure the terminal roaming in the terminal location.Through the above scheme to solve the practical application in the indoor positioning accuracy is seriously insufficient. Finally, we introduce how to further improve the positioning accuracy and stability in the more complex indoor environment and put forward ideas for future solutions.