Integration of Inertial Measurement Unit with ToF/AoA Local Navigation System Using Extended Kalman Filter

This paper is devoted to the development of an algorithm for the integration of an inertial measurement unit (IMU) and a time-of-flight/angle-of-arrival (ToF/AoA) local navigation system (LNS) based on ultra-wideband (UWB) signals. Proposed approach for integration of radio and inertial measurements implies of three extended Kalman filters (EKF). The first filter is necessary for estimation of the components of the velocity vector of the wheeled platform based on ToF and AoA measurements from UWB LNS. The second filter uses velocity vector estimates from first filter and IMU measurements for user orientation estimation. The third filter estimates user coordinates and velocity vector utilizing velocity estimates from second filter and ToF and AoA radio measurements. Proposed approach allows to obtain estimates of user coordinates and orientation at IMU sample rate, and also increases the reliability of the system and ensures the continuity of navigation solution.