A new zero velocity update algorithm for the shoe-mounted personal navigation system based on IMU

Abstract

In this article, a new ZUPT (zero velocity update) algorithm for the shoe-mounted PNS (personal navigation system) based on low-precision IMU (inertial measurement unit) has been studied. Based on the cascade framework of Kalman filtering and particle filtering, the observability analysis on the state variables of Kalman filtering in the bottom layer is conducted, and the error of course angle and position with bad observability in traditional Kalman filtering is thus removed; For the upper particle filter, the length of each step and the change of heading angle have been taken as the variables for observation, while the coordinates of heading angle and horizontal position have been taken as the state variables, to build the dead-reckoning motion model that integrates with indoor map information. The ZUPT algorithm with a mutual modification between Kalman filtering and particle filtering has been designed. Finally, the effectiveness and reliability of the new algorithm have been verified by using the indoor walking data of low-precision IMU.