Kalman Filtering Design Based on Real-Time Updating of Noise Matrix

Abstract

At present, Kalman filtering is widely used in dynamic positioning. With continuous development of deep-sea exploration, the accuracy of Kalman filtering is affected by more complex oceanic condition. As erratic performance of Kalman filtering with fixed system noise matrix and measurement noise matrix in complex oceanic condition, a new filtering method called Kalman filtering based on real-time updating of noise matrix is put forward. The algorithm obtains real-time calculation results of the system noise and measurement noise which are devoted to revising variance of noise array. Compared with Kalman filtering, it is more accurate and more efficacious in improving the performance of dynamic positioning in complex oceanic condition proved by computer simulation.