Abstract
This paper proposes a novel zero velocity update (ZUPT) method for a foot-mounted pedestrian navigation system (PNS). First, the error model of the PNS is developed and a Kalman filter is built based on the error model. Second, a novel zero velocity detection algorithm based on the variations in speed over a gait cycle is proposed. A finite state machine including three states is employed to model a gait cycle. The state transition conditions are determined based on speed using a sliding window. Third, the ZUPT software flow is illustrated and described. Finally, the performances of the proposed method and other methods are examined and compared experimentally. The experimental results show that the mean relative accuracy of the proposed method is 0.89% under various motion modes.
Highlights
The rapid development of micro-electromechanical systems (MEMS) has facilitated the production of inexpensive, lightweight and small-sized inertial sensors with low power consumption
Researches show that the performance of a pedestrian navigation system (PNS) can be significantly increased using a zero velocity update (ZUPT) algorithm
The inertial navigation algorithm of a PNS is similar to traditional inertial navigation algorithm [12,13]; certain simplifications are made based on the characteristics of a PNS
Summary
Mingrong Ren 1,2, *, Kai Pan 1,3 , Yanhong Liu 1 , Hongyu Guo 1 , Xiaodong Zhang 1 and Pu Wang 1,4. Beijing Key Laboratory of Computational Intelligence and Intelligent Systems, Beijing 100124, China
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