Adaptive threshold zero-velocity update algorithm under multi-movement patterns

Zero-velocity update (ZUPT) algorithm is imported to calibrate device's cumulative error in traditional inertial navigation system (INS) which is based on micro-electro-mechanical system inertial mea-surement unit (MEMS-IMU). The positioning accuracy will be reduced when the movement trajectory of indoor pedestrian contains multi-movement patterns, because the zero-velocity determination threshold is fixed and only suitable for a single movement pattern. An adaptive threshold ZUPT algorithm under multi-movement patterns was proposed. The selection of zero-velocity determination threshold of indoor pedestrian's five movement patterns including Still, Walk, Run, Upstairs and Downstairs was analyzed. Classification and recognition of five movement patterns using random forest (RF) algorithm were realized. And the zero-velocity determination threshold of ZUPT was adaptively adjusted according to the recognition results. In order to verify the feasibility and validity of the algorithm, the test data was disposed and was compared with traditional position-ing algorithm through MATLAB software platform. The three groups of test results show that, when there are multiple movement patterns in an indoor pedestrian trajectory, the positioning accuracy of positioning algorithm can be improved by 73.83% when ZUPT algorithm with adaptively adjusted threshold is imported, compared with traditional positioning algorithm with fixed threshold.