Accession Number:

ADA446968

Title:

Multiple Sampling for Estimation on a Finite Horizon

Descriptive Note:

Technical research rept.

Corporate Author:

MARYLAND UNIV COLLEGE PARK INST FOR SYSTEMS RESEARCH

Report Date:

2006-01-01

Pagination or Media Count:

9.0

Abstract:

We discuss some multiple sampling problems that arise in real-time estimation problems with limits on the number of samples. The quality of estimation is measured by an aggregate squared error over a finite horizon. We compare the performances of the best deterministic, level-triggered and optimal sampling schemes. We restrict the signal to be either a Wiener process or an Ornstein-Uhlenbeck process. For the Wiener process, we provide closed form expressions and series expansions. For the Ornstein-Uhlenbeck process, we provide procedures for numerical computation. Our results show that level-triggered sampling is almost optimal when the signal is stable.

Subject Categories:

  • Statistics and Probability
  • Numerical Mathematics

Distribution Statement:

APPROVED FOR PUBLIC RELEASE