A MULTI-IMU BASED SELF-CONTAINED PEDESTRIAN NAVIGATION ALGORITHM
Keywords: Inertial Navigation, Inertial Measurement Units, Arbitrary Orientation Estimation, Pedestrian Dead Reckoning, Attitude and Heading Reference System
Abstract. The demand for navigation and positioning is increasing in various fields nowadays. Although Global Navigation Satellite Systems (GNSS) are currently the most widely used high-accuracy positioning method, their operation rests on signal transmission and reception, which is prone to interference from obstacles such as high-rise buildings, thereby limiting indoor navigation. In addition, in highly dynamic scenarios, the low update rate of the signal cannot track detailed motions. In this case, Inertial Measurement Units (IMUs) play an important role in serving as a complementary component. However, a single high-accuracy IMU is financially prohibitive. On the other hand, the lack of accuracy and stability limits the application of low-cost IMU in navigation. One way to improve the performance of low-cost IMU is to fuse multiple IMUs. This study focuses on the development of pedestrian navigation using multi-sensor integration of low-cost IMUs and magnetometers exploring different integration techniques to compare their performance. The Pedestrian Dead Reckoning (PDR) algorithm is a technique used to estimate the relative motion of pedestrian, which is a commonly used technology for indoor pedestrian navigation. This study use PDR with multi-sensor integration of low-cost IMUs to reduce the position error of pedestrian navigation to within one meter, with the aim of establishing a high-precision, reliable, and low-cost pedestrian navigation algorithm.