In order to detect zero speed more quickly and accurately,a pedestrian navigation method based on adaptive detection of zero speed events is proposed.The method firstly calculates the different characteristic labels of walking and running based on the inertial data and one gait cycle as a group.Then the motion state of the calculated labels is judged by support vector machine(SVM).Finally,RNN neural network is used to determine whether the output is zero velocity event by combining the original inertial data with the motion state,which reduces the calculation cost.The method was evaluated by several experiments with different gaits.The horizontal position errors were 0.748,0.593 and 1.054 m,and the closed position errors were 0.551％,0.438％and 0.777％,respectively,in 135.6 m walking,running and walking-running combined exercises.
维普
万方数据