Hostname: page-component-cd9895bd7-p9bg8 Total loading time: 0 Render date: 2024-12-24T02:11:48.981Z Has data issue: false hasContentIssue false
  • English
  • Français

An Extended Dynamic Model for Kinematic Positioning

Published online by Cambridge University Press:  27 January 2003

Michael Moore  and
Jinling Wang
Michael Moore
Affiliation:
Satellite Navigation & Positioning Group, University of New South Wales
Jinling Wang
Affiliation:
Satellite Navigation & Positioning Group, University of New South Wales
Get access Rights & Permissions [Opens in a new window]

Abstract

The main problems faced by a dynamic model within a Kalman filter occur when the system experiences unexpected dynamic conditions, a change in data acquisition rate, or when the dynamics of the system are non-linear. To minimize the errors produced from dynamic modelling in unusual conditions, an extended dynamic model is developed in this paper, and its usefulness demonstrated through comparison of the performance of a Kalman filter's response to simulated data with a standard dynamic model and the extended dynamic model. The results show that, in use, the proposed extended dynamic model is superior to a standard dynamic model, due mainly to its ability to adapt to a wider range of dynamic conditions, which in turn ensures the optimization of the Kalman filter and the consequent generation of reliable positioning results.

Keywords

PositioningModellingSimulation
Type
Research Article
Information
The Journal of Navigation , Volume 56 , Issue 1 , January 2003 , pp. 79 - 88
Copyright
© 2003 The Royal Institute of Navigation

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)