Invited Speech Title: A Novel Data Fusion Method For Indoor Navigation Using IMU Aided UWB

Speaker's Bio:
Hailin Cao
Chongqing University; State Key Laboratory of Vehicle NVH and Safety Technology.

Invited Speech Abstract:
This speech proposes an unscented kalman filter (UKF) method for the IMU aided UWB indoor navigation system. GDOP is selected as the independent variable to analyze the positioning accuracy quantitatively, and the static, linear and circular motion states of the tag are simulated and analyzed. Based on the simulation analysis of the fusion positioning model, a TDOA-IMU positioning system is designed and implemented for verification. The simulation and experimental results both show that a higher positioning accuracy in linear and circular motion state is realized using TDOA-IMU fusion positioning. Compared with TDOA positioning alone, 80% probability circle error radius (CEP) in the region far from the anchor node is reduced from 0.530m to 0.340m.