Tracking of Maneuvering Targets Using Linear Time Invariant Estimators.

Abstract

In this paper we consider the problem of finding a filter that minimizes the worst case magnitude (l at infinity) of the estimation error in the case of linear time invariant systems subjected to unknown but magnitude bounded (l at infinity) inputs. These inputs consist of process and observation noise, as well as initial conditions; also, the optimization problem is considered over an infinite time horizon. Taking a model matching approach, suboptimal solutions are presented which stem from the resulting l oo induced norm minimization problem. Examples are also presented that compare the performance of the so-obtained estimator with that of Kalman filters.

Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1993
Accession Number
ADP009065

Entities

People

  • Petros G. Voulgaris

Organizations

  • University of Illinois Urbana–Champaign

Tags

DTIC Thesaurus Topics

  • Algorithms
  • Dynamics
  • Estimators
  • Filters
  • Kalman Filters
  • Mathematics
  • Observation
  • Optimal Estimators
  • Optimization
  • Rhode Island
  • Statistical Algorithms

Fields of Study

  • Engineering

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.