Accession Number:

AD0724073

Title:

Optimal Measurement Strategies for Linear Stochastic Systems

Descriptive Note:

Technical note

Corporate Author:

MASSACHUSETTS INST OF TECH LEXINGTON LINCOLN LAB

Personal Author(s):

Report Date:

1971-02-26

Pagination or Media Count:

44.0

Abstract:

The note presents the formulation of a class of optimization problems dealing with selecting, at each instant of time, one measurement provided by one out of many sensors. Each measurement has an associated measurement cost. The basic problem is then to select an optimal measurement policy, during a specified observation time interval, so that a weighted combination of prediction accuracy and accumulated observation cost is minimized. The current analysis is limited to the class of linear stochastic dynamic systems and measurement subsystem. The problem of selecting the optimal measurement strategy can be transformed into a deterministic optimal control problem. An iterative digital computer algorithm is suggested for obtaining numerical results. It is shown that the optimal measurement policy and the associated matched Kalman-type filter can be precomputed, i.e., specified before the measurements actually occur.

Subject Categories:

  • Statistics and Probability
  • Cybernetics
  • Test Facilities, Equipment and Methods

Distribution Statement:

APPROVED FOR PUBLIC RELEASE