TDOA based Tightly Coupled Sensor Fusion for UAV Positioning in GPS-denied Environment

Currently, the integration of the Global Navigation Satellite System (GNSS) and Inertial Navigation System (INS) meets the positioning requirements of unmanned aerial vehicles (UAVs) across a wide range of scenarios. However, these systems are not suitable for localization within GPS-denied environments. This paper proposes a tightly coupled fusion algorithm that integrates Ultra-Wideband (UWB) and Inertial Measurement Unit (IMU) data based on Time Difference of Arrival (TDOA) measurements, suitable for using in GPS-denied environments. TDOA algorithm reduces communication burden, reduces power consumption and enhances positioning accuracy. Furthermore, the tightly coupled architecture enables the updating of UAV positioning information in harsh environments and enhances positioning accuracy and robustness. The algorithm was tested in a Gazebo-simulated UAV flight, comparing it against traditional and loosely coupled approaches, also using Two-Way Time of Flight (TW-TOF) measurements for internal comparisons. Results demonstrate that the method significantly enhances positioning accuracy and stability, achieving a median error of 0.0319 m, a 95 th percentile error of 0.0789 m, and an average standard deviation of 0.0207 m. This study validates the improvements in UWB positioning accuracy and robustness, promoting its application in real-world scenarios.