Modified Kalman filtering for linear discrete-time systems with correlated noise

作者：Liu Wei^*; Zhang Hua Guang

来源：Journal of Northeastern University, 2010, 31(1): 1-3+7.

• Conditional means
• Correlated noise
• Covariance matrix estimation
• Hamiltonian approach
• Kalman gain matrix
• Kalman-filtering
• Linear discrete-time systems
• Observation noise
• Optimal performance
• Regression equation
• Simulation result
• System noise
• System state

The state estimation problem of linear discrete-time systems was studied in case the system noises and observation noises are both correlated. A modified Kalman filtering which is in combination with the Hamiltonian approach of Kalman filter was proposed. Compared with the classic Kalman filtering, the proposed algorithm needn't calculate the Kalman gain matrix and conditional mean of observation sequence, and it obtains the optimal performance under conditions that less regression equations are needed and they are easily calculated. Thus, the algorithm is easy to use. Simulation results demonstrated that the algorithm can effectively estimate the system states.

• 出版日期2010
• 单位东北大学