DocumentCode :
1547374
Title :
Reconciling steady-state Kalman and alpha-beta filter design
Author :
Painter, John H. ; Kerstetter, David ; Jowers, Steve
Author_Institution :
Dept. of Electr. Eng., Texas A&M Univ., College Station, TX, USA
Volume :
26
Issue :
6
fYear :
1990
fDate :
11/1/1990 12:00:00 AM
Firstpage :
986
Lastpage :
991
Abstract :
The deterministic design of the alpha-beta filter and the stochastic design of its Kalman counterpart are placed on a common basis. The first step is to find the continuous-time filter architecture which transforms into the alpha-beta discrete filter via the method of impulse invariance. This yields relations between filter bandwidth and damping ratio and the coefficients, α and β. In the Kalman case, these same coefficients are related to a defined stochastic signal-to-noise ratio and to a defined normalized tracking error variance. These latter relations are obtained from a closed-form, unique, positive-definite solution to the matrix Riccati equation for the tracking error covariance. A nomograph is given that relates the stochastic and deterministic designs
Keywords :
Kalman filters; network synthesis; nomograms; signal processing; stochastic systems; tracking; alpha-beta filter; alpha-beta filter design; continuous-time filter architecture; damping ratio; deterministic design; discrete filter; filter bandwidth; impulse invariance; matrix Riccati equation; nomograph; normalized tracking error variance; steady state Kalman filter; stochastic design; stochastic signal-to-noise ratio; tracking error covariance; Bandwidth; Damping; Equations; Kalman filters; Nonlinear filters; Signal generators; Signal to noise ratio; Steady-state; Stochastic processes; Wiener filter;
fLanguage :
English
Journal_Title :
Aerospace and Electronic Systems, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9251
Type :
jour
DOI :
10.1109/7.62250
Filename :
62250
Link To Document :
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