Dual MIMU Pedestrian Navigation by Inequality Constraint Kalman Filtering
AbstractThe foot-mounted inertial navigation system is an important method 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 pedestrian navigation aided with both ZUPT (zero velocity update) and the range decomposition constraint performs better than those in their own respective methods. This paper recommends that the separation distance between the position estimates of the two foot-mounted inertial navigation systems be restricted by an ellipsoidal constraint that relates to the maximum step length and the leg height. The performance of the proposed method is studied by utilizing experimental data, and the results indicate that the method can effectively correct the dual navigation systems’ position over the traditional spherical constraint. View Full-Text
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Shi, W.; Wang, Y.; Wu, Y. Dual MIMU Pedestrian Navigation by Inequality Constraint Kalman Filtering. Sensors 2017, 17, 427.
Shi W, Wang Y, Wu Y. Dual MIMU Pedestrian Navigation by Inequality Constraint Kalman Filtering. Sensors. 2017; 17(2):427.Chicago/Turabian Style
Shi, Wei; Wang, Yang; Wu, Yuanxin. 2017. "Dual MIMU Pedestrian Navigation by Inequality Constraint Kalman Filtering." Sensors 17, no. 2: 427.
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