Abstract: [Purposes] In densely forested mountainous environment,inter-system bias(ISB)between BDS and GPS significantly increases global navigation satellite system (GNSS)positioning errors.This prevents GNSS from providing high-precision position corrections to the inertial navigation system (INS).Consequently,positioning errors accumulate in GNSS+INS integrated navigation,severely degrading the performance of UAV power line inspection.[Methods] To address this issue,this paper proposes a dynamic adaptive Kalman filtering algorithm that accounts for BDS+GPS ISB.A measurement equation for BDS and GPS ISB in integrated positioning is established based on GNSS+INS dynamic adaptive fusion.A GNSS quality-check strategy is introduced to eliminate observation outliers,thereby significantly improving the accuracy and robustness of state estimation.[Findings]Experimental results demonstrate that the proposed ISB dynamic Kalman filter effectively enhances GNSS+INS position estimation performance.The RMSE are less than 10 cm horizontally and below 8 cm vertically,outperforming both the EKF and the AKF.[Conclusions]These findings provide a valuable design reference for UAV power inspection systems.

Key words: ISB, GNSS+INS, dynamic adaptive Kalman filter, power inspection system