Dual MIMU Pedestrian Navigation by Inequality Constraint Kalman Filtering

Abstract

Abstract:The foot-mounted inertial navigation system is an important application of pedestrian navigation as it in principle does not rely any external assistance. A real-time range decomposition constraint method is proposed in this paper to combine the information of dual foot-mounted inertial navigation systems. It is well known that low-cost inertial sensors with ZUPT (zero-velocity update) and range decomposition constraint perform better than in either single way. This paper recommends that the distance of separation between the position estimates of feet-mounted inertial navigation systems be restricted in the ellipsoidal constraint which relates to the maximum step and leg height. The performance of the proposed method is studied utilizing experimental data. The results indicate that the method can effectively correct the dual navigation systems' position over the existing spherical constraint.

Lower Limb Model Based Inertial Indoor Pedestrian Navigation System for Walking and Running

“…In [17], the relative distance constrained algorithm and the adaptive co-localization algorithm are proposed, which improved the positioning accuracy by 60% compared to the traditional method. In [18], [19], a bipedal ellipsoidal constraint method is proposed to achieve a threedimensional bipedal distance constraint, which effectively reduced the heading drift. A bipedal inertial/magnetometer pedestrian positioning method based on adaptive inequalityconstrained Kalman filtering is presented in [20], which allows for long-time walking navigation.…”

Radar Update (RUPT): A Pedestrian Navigation System with Enhanced Trajectory Performance

“…In this system, two independent foot-mounted inertial navigation systems with zero velocity update (ZUPT) [1], [25] are built via data from IMUs. The use of two IMUs would greatly improve the heading tracking accuracy compared to the case of a single IMU [3], [16]- [18], [26], [27]. Millimeter wave radar provides a reliable and noncumulative external observation to the inertial navigation system.…”