Shoe-mounted personal navigation system based on MEMS inertial technology

An amendment navigation algorithm is studied on shoe-mounted PNS(personal navigation system),which is composed of MEMS inertial sensors with low precision.Based on traditional SINS navigation algorithm,a ZUPT(zero velocity update) method is developed to improve navigation accuracy.By analyzing the acceleration's statistical characteristic on walker's foot,a so-called SFM/SV(specific force magnitude and slip variance) detection algorithm is designed for detecting stance phase between steps.Then through a Kalman filter which is designed for zero velocity update(ZUPT),the navigation errors including attitude error,velocity error and position error can be estimated.Therefore,the navigation precision can be improved by feeding these estimated errors back to original navigation system.In the end,two physical experiments are conducted using an integrated MEMS IMU,and the results indicate that the above algorithm is feasible for PNS.In addition,future research directions are pointed out.