An Improved Anti-outlier Robust Square-Root Cubature Kalman Filter Algorithm

An improved anti-outlier robust square-root cubature Kalman filter (SRCKF) algorithm is studied. Based on Scaled-Contaminated Normal Distribution Model (SCNM), the improved anti-outlier robust-SRCKF algorithm is proposed by combining the idea of SCNM model with SRCKF algorithm. The simulation results show that the anti-outlier robust SRCKF algorithm has strong stability and high estimation accuracy, and can better suppress the adverse effects of observation outliers.