A novel finite state machine based step detection technique for pedestrian navigation systems

In this paper we present a novel finite state machine based step detection technique for precise personal navigation solutions with a foot-mounted inertial measurement unit (IMU). Generally, step detection methods are used to improve the navigation solution by applying Zero Velocity Updates (ZUPTs) in the navigation filter. All step detection techniques distort the navigation solution if ZUPTs are utilized at wrong times. Our approach based on a finite state machine is able to detect different stances of the foot with high accuracy. Therefore, Zero Velocity Updates can be applied in time and positively affect the precision of the navigation solution. The functionality of the step detection module in combination with a constraint, stochastic cloning (SC) Kalman filter are analyzed with real sensor data recorded with our pedestrian navigation system. Even with ultra-low cost inertial sensors, this new approach can clearly increase the accuracy of pedestrian navigation systems compared to state-of-the-art approaches.