TY - JOUR
T1 - Design and Analysis of Linear Predictor-Corrector Digital Filters
AU - Chui, Charles K.
N1 - Funding Information:
*Supported in part by the U.S. Army Research Office under Contract No. DAAG 29-81-K-0133. Department of Mathematics, Texas A& M Un~versity,C ollege Station, Texas 77843.
PY - 1984/1/1
Y1 - 1984/1/1
N2 - In application, it is believed that the third order linear predictor-corrector digital filter, or commonly known as the α-β-γ tracking filter, can be derived from the Kalman filter. In this paper, we characterize the values of α, β and γ so that the α-β-γ tracking filter is indeed a limiting Kalman filter, and derive the input to observation noise ratios in terms of the stochastic parameters as functions of α, β and γ to allow the user to design the α-β-γ filter to obtain near-optimal performance, z-transform is used to uncouple the filter and to study stability.
AB - In application, it is believed that the third order linear predictor-corrector digital filter, or commonly known as the α-β-γ tracking filter, can be derived from the Kalman filter. In this paper, we characterize the values of α, β and γ so that the α-β-γ tracking filter is indeed a limiting Kalman filter, and derive the input to observation noise ratios in terms of the stochastic parameters as functions of α, β and γ to allow the user to design the α-β-γ filter to obtain near-optimal performance, z-transform is used to uncouple the filter and to study stability.
UR - http://www.scopus.com/inward/record.url?scp=84892219560&partnerID=8YFLogxK
U2 - 10.1080/03081088408817577
DO - 10.1080/03081088408817577
M3 - Journal article
AN - SCOPUS:84892219560
SN - 0308-1087
VL - 15
SP - 47
EP - 69
JO - Linear and Multilinear Algebra
JF - Linear and Multilinear Algebra
IS - 1
ER -