INS/GPS Tightly Integrated Algorithm with Reduced Square-Root Cubature Kalman Filter

Focusing on the problem about the real time of nonlinear model's calculation, we propose to use the Reduced Square Root Cubature Kalman Filter (RSCKF to improve the operating rate of INS/GPS tightly integrated navigation system. This reduced arithmetic simplify the Square Root Cubature Kalman Filter (SCKF) in Time Update step, it directly use the state-transition matrix for calculating the one-step prediction matrix of state and covariance, avoiding the complex approximate calculation process of calculating cubature. In simulation experiments, we compare the RSCKF with SCKF and EKF. Results from the simulation show that this two arithmetic perform well than EKF. The RSCKF algorithm performs nearly the same as the SCKF in accuracy, and can effectively reduce the calculated amount.