An adaptive selection algorithm of threshold value in zero velocity updating for personal navigation system

Personal navigation system(PNS) is mainly used for tracking and locating personnel walking real-time location which can be realized as underground exploration or indoor positioning when the GPS signal loses. MEMS inertial sensors are small size, low cost, low power consuming, mass-production capability and silicon-based sensors. Strap-down inertial navigation system can achieve its autonomous navigation capabilities by fixing the sensor on the user´s shoes. Zero velocity updating (ZUPT) can correct the tracking of navigation algorithm. This paper proposes an adaptive algorithm of threshold value in ZUPT of PNS. The test results show that the adaptive algorithm can effectively correct the error of tracking. The tracking of navigation algorithm with zero velocity updating is very close to the real track of walker.