Research on the location algorithm of android mobile phone based on extended Kalman filter

At present, there are more and more applications for mobile phone positioning, and many APPs (Applications) in the market will use the positioning function. However, most APPs use traditional positioning algorithms and can not meet the needs of people to obtain high-precision geographic location information in real time. At present, there is less research on the positioning method of the mobile phone's GPS chip raw data. Therefore, this paper mainly studies the feasibility and positioning algorithm of using the mobile phone's GPS raw data. Using the application program interface provided by the Android 7.0 system to obtain the raw data parameters of the GPS chip, according to the speed characteristics of the practical scene of the mobile phone, the static Kalman filtering for static scenes and the dynamic Kalman filtering positioning algorithm for low-speed scenes were designed and implemented respectively. Through static experiments as well as electric vehicle experiments and walking experiments, the experimental results show that compared with traditional positioning algorithms, the static Kalman filtering and dynamic Kalman filtering positioning algorithms designed in this paper have better positioning results and are closer to the actual walking route. It proves the feasibility of using mobile phone GPS raw data to locate, and also proves that the designed Kalman filter algorithm can improve the positioning accuracy. The research results of this paper provide theoretical basis for realizing static and dynamic highprecision mobile phone positioning algorithms.