Error Influences of Prior Covariance Matrices on Dynamic Kalman Filtering

The influence of the prior covariance errors to the standard dynamic Kalman filtering is discussed.The influence expressions of the prior covariance matrix errors including the covariance matrix of state parameters,dynamical model errors and measurement noises are deduced.A GPS/INS tight integration navigation is performed,and it shows that the unreasonable errors of the covariance matrices of the dynamic model information and measurements will result in biases of the dynamic navigation results.The minus errors of the covariance matrix of dynamical model information will increase the navigation errors.If the errors of the covariance matrix of the predicted states are positive,then the effects of the dynamical model error will be weakened.However,contrary conclusion could be got if only the errors of the covariance matrix of measurement noises are considered.