Fixed-lag alpha-beta filter for target trajectory smoothing

Author

Ogle, Terrence L. ; Blair, William D.

Author_Institution

Georgia Tech Res. Inst., Georgia Inst. of Technol., Atlanta, GA, USA

Volume

40

Issue

4

fYear

2004

Firstpage

1417

Lastpage

1421

Abstract

A fixed-lag Kalman smoother can be used for target trajectory reconstruction in postmission data analysis from noisy sensor data, where lag is the time difference between the time of the latest available measurement (or the latest measurement used for estimation) and the time of the smoothed estimate. Based on the steady-state conditions of a Kalman smoother, a recursive method for calculating the steady-state gains and covariance matrix of a fixed-lag alpha-beta smoother is derived and presented. The equations derived for the alpha-beta fixed-lag smoother were verified using a Kalman smoother in steady-state, and the results are used to characterize the benefits achieved with fixed-lag smoothing.

Keywords

Kalman filters; covariance matrices; signal reconstruction; smoothing methods; covariance matrix; fixed-lag Kalman smoother; fixed-lag alpha-beta filter; fixed-lag smoothing; noisy sensor data; postmission data analysis; recursive method; steady-state conditions; steady-state gains; target trajectory reconstruction; target trajectory smoothing; time difference; Covariance matrix; Equations; Gaussian noise; Kalman filters; Noise measurement; Smoothing methods; State estimation; Steady-state; Time measurement; Trajectory;

fLanguage

English

Journal_Title

Aerospace and Electronic Systems, IEEE Transactions on

Publisher

ieee

ISSN

0018-9251

Type

jour

DOI

10.1109/TAES.2004.1386894

Filename

1386894