Dynamic Lever Arm Estimation and Collaborative Navigation Method for Unmanned Vehicles/Pedestrians
In response to the problem of rapid accumulation of positioning errors over time caused by significant de-vice noise of micro inertial navigation systems under complex dynamic environments,the model of relative kinematics be-tween unmanned vehicles and pedestrians is fully utilized.A collaborative navigation method based on unmanned vehicle/pedestrian inertial bases is investigated to achieve the error suppression and accuracy improvement of inertial navigation sys-tems under the conditions of complex motion.Firstly,a"velocity+attitude"matching model for unmanned vehicle/pedes-trian is established.Then,taking into full consideration the motion characteristics of pedestrians,a relative motion model of unmanned vehicle/pedestrian is established,and the dynamic lever arm estimation between the two is performed.Finally,a collaborative navigation method for unmanned vehicle/pedestrian is proposed and highly reliable software in the loop simu-lation experiments are conducted.The experimental results show that he positioning accuracy of pedestrian micro inertial navigation is greatly improved under the constraint of relative motion between unmanned vehicle/pedestrian,and supports satellite independent relative navigation and collaborative navigation of unmanned vehicle/pedestrian.
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