TDOA Based Extended Kalman Filter Fusion Approach for UAV Localization in GPS-denied Environment

Attributable to its high precision and strong interference resistance capability, the ultra-wideband (UWB) positioning technology has been widely researched as a wireless positioning technology for unmanned aerial vehicles (UAV) in global positioning denied and satellite signals blocked areas. The reliability of a solitary sensory input source may be compromised in such environmental conditions. Nevertheless, the environment variation still increases the estimation complexity of the measurement noise for UWB sensors. On the other hand, the loosely synchronized clock between the sensor nodes also limits the positioning performance of the existing UWB system. A fused positioning method with a clock-offset-compensated time difference of arrival (TDOA) positioning algorithm and extended Kalman filter (EKF) is presented in this paper to address these issues. According to the simulation results, the proposed approach attains a centimeter-level accuracy (the 95th percentile error is 0.076 m) and improves the standard deviation to 0.033 m.