On Kalman Filtering With Nonlinear Equality Constraints

Abstract

The state space description of some physical systems possess nonlinear equality constraints between some state variables. In this paper, we consider the problem of applying a Kalman filter-type estimator in the presence of such constraints. We categorize previous approaches into pseudo-observation and projection methods and identify two types of constraints-those that act on the entire distribution and those that act on the mean of the distribution. We argue that the pseudo-observation approach enforces neither type of constraint and that the projection method enforces the first type of constraint only. We propose a new method that utilizes the projection method twice-once to constrain the entire distribution and once to constrain the statistics of the distribution. We illustrate these algorithms in a tracking system that uses unit quaternions to encode orientation.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Jun 01, 2007
Accession Number
ADA606230

Entities

People

  • Joseph J. Laviola Jr.
  • Simon J. Julier

Organizations

  • United States Naval Research Laboratory

Tags

Communities of Interest

  • Air Platforms
  • Energy and Power Technologies
  • Materials and Manufacturing Processes
  • Space

DTIC Thesaurus Topics

  • Algorithms
  • Computer Graphics
  • Computer Science
  • Electrical Engineering
  • Estimators
  • Filters
  • Filtration
  • Human-Machine Interaction
  • Information Science
  • Kalman Filtering
  • Kalman Filters
  • Mathematical Filters
  • Signal Processing
  • Simultaneous Localization And Mapping
  • Stochastic Processes
  • Three Dimensional
  • Virtual Reality

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Operations Research

Technology Areas

  • Space