We propose the prior covariance estimation method based on inverse covariance intersection (ICI) method for applying to particle flow filter. The proposed method has better estimate performance and guarantees consistent estimation results compared with previous works. ICI is the recently developed method of the ellipsoidal intersection and is used to integrate the sample covariance estimate which is unbiased but normally with high variance, together with a more structured but typically a biased target covariance through fusion gains, to get the combined estimate of prior covariance. In order to verify the performance of the proposed algorithm, analysis and simulations are performed. Through the simulations, the results are given to illustrate the consistency and accuracy of the proposed algorithm’s estimate performance.

Keywords: prior covariance estimation, inverse covariance intersection, particle flow filter