Title :
Estimation using a multirate filter
Author :
Andrisani, D. ; Gau, Ching-Fu
Author_Institution :
Purdue University, West Lafayette, IN
fDate :
7/1/1987 12:00:00 AM
Abstract :
This note presents both optimal and suboptimal filtering algorithms for estimating state variables based on measurements sampled at two different data rates. The optimal algorithm consists of two parallel Kalman filters; one processes the fast rate measurement and is of reduced-order, and the other processes the residuals from the first filter along with the slow rate measurement. This algorithm is used to design a suboptimal algorithm that has decreased computational requirements with only a small performance penalty.
Keywords :
Discrete-time systems; State estimation, linear systems; Algorithm design and analysis; Covariance matrix; Extraterrestrial measurements; Filtering algorithms; Filters; Gaussian noise; Q measurement; State estimation; Time measurement; Vectors;
Journal_Title :
Automatic Control, IEEE Transactions on
DOI :
10.1109/TAC.1987.1104672