Paper Info
Title
Optimal Measurement Times for Observing a Brownian Motion over a Finite Period Using a Kalman Filter.
Abstract
This article deals with the optimization of the schedule of measures for observing a random process in time using a Kalman filter, when the length of the process is finite and fixed, and a fixed number of measures are available. The measure timetable plays a critical role for the accuracy of this estimator. Two different criteria of optimality of a timetable (not necessarily regular) are considered: the maximal and the mean variance of the estimator. Both experimental and theoretical methods are used for the problem of minimizing the mean variance. The theoretical methods are based on studying the cost function as a rational function. An analytical formula of the optimal instant of measure is obtained in the case of one measure. Its properties are studied. An experimental solution is given for a particular case with n > 1 measures.
Year
DOI
Venue
2017
10.1007/978-3-319-53547-0_48
Lecture Notes in Computer Science
Keywords
Field
DocType
Random walk,Wiener process,Kalman filter
Wiener process,Applied mathematics,Mathematical optimization,Extended Kalman filter,Random walk,Minimum mean square error,Stochastic process,Kalman filter,Rational function,Mathematics,Estimator
Conference
Volume
ISSN
Citations 
10169
0302-9743
0
PageRank 
References 
Authors
0.34
1
4
Name
Order
Citations
PageRank
Alexandre Aksenov100.34
Pierre-Olivier Amblard215018.35
Olivier J. j. Michel323223.78
Christian Jutten42925439.04