论文信息 - Filter coefficient selection using design criteria

Filter coefficient selection using design criteria

For tracking systems with a uniform data rate and stationary measurement noise, non-manoeuvring targets can be accurately tracked with a steady-state Kalman filter. The steady-state Kalman filter, which can be viewed as equivalent to an alpha-beta filter, has been widely applied to many different systems. A means of selecting the filter coefficients was proposed by Kalata (1984) using Kalman filter considerations. An alternative method based on noise reduction ratios is presented in this paper. Using a design criteria with the Kalata relation, optimal filter coefficients can be selected for specific applications. This method generalizes current methods for selecting the filter coefficients.

G. J. Foster | John E. Gray | J. Gray | G. Foster

[1] P. Kalata. The Tracking Index: A Generalized Parameter for α-β and α-β-γ Target Trackers , 1984, IEEE Transactions on Aerospace and Electronic Systems.

[2] T. Benedict,et al. Synthesis of an optimal set of radar track-while-scan smoothing equations , 1962 .

[3] Y. Bar-Shalom. Tracking and data association , 1988 .

[4] Arthur Gelb,et al. Applied Optimal Estimation , 1974 .

[5] P. Swerling. Modern state estimation methods from the viewpoint of the method of least squares , 1971 .

[6] John E. Gray,et al. The response of the transfer function of an alpha-beta filter to various measurement models , 1991, [1991 Proceedings] The Twenty-Third Southeastern Symposium on System Theory.