ZUPT-Aided INS Bypassing Stance Phase Detection by Using Foot-Instability-Based Adaptive Covariance

In this paper, we propose a Foot-Instability-Based Adaptive (FIBA) covariance to dynamically adjust the matrix for pseudo-zero-velocity measurements in Zero velocity UPdaTe (ZUPT)-aided Inertial Navigation Systems (INS). The proposed ZUPT-aided INS using FIBA is implemented an Extended Kalman Filter (EKF) framework, which utilizes time-varying measurement that updated each iteration according covariance. designed have very high value during swing phases gait cycle, and significantly decreases stance phases. As result, method eliminates need use binary phase detector implementation of INS. Properties EKF innovation sequences algorithm were studied, two series indoor pedestrian navigation experiments conducted demonstrate performance system. first experiments, included cases walking running, localization solutions produced by system demonstrated 36% 64% improvements accuracy along horizontal vertical directions, respectively. second on different terrains, such as flat planes, stairs, ramps, reduced position errors 12% 45%, respectively, compared conventional