In this paper we present a high-precision and robust indoor navigation system based on foot-mounted inertial sensors. We use a finite state machine based step detection technique for precise localization. This approach is able to detect different stances of the foot with high accuracy. The FSM-based step detection technique precisely detect Zero Velocity Updates (ZUPTs). ZUPTs can be applied in time in the navigation filter and positively affect the grade 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 personal navigation system. Even with ultra-low cost inertial sensors, this approach delivers a personal navigation system for precise positioning in indoor environments and outdoor areas.