Research On Multi-information Fusion Based Seamless Outdoor/Indoor Personal Navigation System

In recent years, personal navigation has been gradually researched. With the development of the Satellite Positioning Technology, personal navigation method using GPS tends to be more mature. However, the signal of the satellite is susceptible. To improve the system performance of personal navigation system, the algorithm based on inertial navigation has been researched and will become the main research trend of personal navigation in the future. In this paper, we research on seamless personal indoor and outdoor navigation with low-cost sensors.Firstly, we design a module equipped with MEMS sensors. With the output of the inertial sensor and the optical motion capture system, we briefly analyze the human gait, to make sure that foot zero speed stage exists. Based on the analysis, we implement the personal navigation method using ZUPT, and lay the foundation for further work.To improve the performance of navigation system without GPS, as well as solve heading angle error divergence problem in inertial personal navigation system, we design and implement two methods. One is based on cellular structure particle filter, and the other uses visual means.In order to improve the personal navigation and positioning precision of the outdoor environment, we add GPS and magnetic sensor to assist INS. The output data of these sensors are fused by kalman filter. The result shows that, the use of GPS and magnetic sensor can effectively improve navigation accuracy.After finishing the study on the method of indoor and outdoor personal navigation, the seamless navigation strategy is given. We distinguish indoor and outdoor condition by detecting the effectiveness of the GPS signal. Finally, we establish the personal seamless navigation software platform. This experimental platform can be used when we research on personal navigation, and have a good project reference value.