Advances in Observer Techniques for Ballistic Missile Defense Filtering Algorithms.
Abstract
This report investigates the idea of utilizing Luenberger's minimal-order observer as an alternate to the Kalman filter for obtaining state estimates in linear discrete-time stochastic systems. More specifically, this dissertation presents a solution to the problem of constructing an optimal minimal-order observer for linear discrete-time stochastic systems where optimality is in the mean-square sense. The approach taken in this dissertation leads to a completely unified theory for the design of optimal minimal-order observers and is applicable to both time-varying and time-invariant linear discrete systems. The basic solution to the problem is first obtained for that class of systems having Gaussian white noise disturbances. The solution is based on a special linear transformation which transforms the given time-varying discrete-time state equations into an equivalent state space which is extremely convenient from the standpoint of observer design. (Author)
Document Details
- Document Type
- Technical Report
- Publication Date
- Mar 01, 1982
- Accession Number
- ADA124655
Entities
People
- Leslie M. Novak
Organizations
- University of California, Los Angeles