SQUARE-ROOT ALGORITHMS FOR PARALLEL PROCESSING IN OPTIMAL ESTIMATION

被引：13

作者：

MORF, M ^{[1
]}

DOBBINS, JR ^{[1
]}

FRIEDLANDER, B ^{[1
]}

KAILATH, T ^{[1
]}

机构：

[1] SYST CONTROL INC,PALO ALTO,CA 94303

来源：

AUTOMATICA | 1979年 / 15卷 / 03期

基金：

美国国家科学基金会;

关键词：

Computational methods; computer-aided design; filtering; Kalman filters; large scale systems; optical filtering; parallel processing; smoothing; square-root doubling; state estimation;

D O I：

10.1016/0005-1098(79)90046-3

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

We give explicit algorithms in square-root form that allow measurements for the standard state estimation problem to be processed in a highly parallel fashion with little communication between processors. After this preliminary processing, blocks of measurements may be incorporated into state estimates with essentially the same computation as usually accompanies the incorporation of a single measurement. This formulation also leads to square-root doubling formulae for calculating the steady-state error-covariance matrix of constant models, and an extension of the class of problems for which Chandrasekhar-type algorithms offer computational reductions to include piecewise constant systems with arbitrary initial conditions. © 1979.

引用

页码：299 / 306

页数：8

共 17 条

[1] A SQUARE ROOT FORMULATION OF KALMAN COVARIANCE EQUATIONS [J].