Publication detail

Application of Kalman Filter to oversampled data from Global Position System

DITTRICH, P.

Original Title

Application of Kalman Filter to oversampled data from Global Position System

English Title

Application of Kalman Filter to oversampled data from Global Position System

Type

conference paper

Language

en

Original Abstract

There are many applications using the Global Positioning System (GPS) as a source of position and velocity data. A main problem of the GPS data is its inconsistency on higher sampling frequencies. The usage of enhanced Kalman Filter is presented to fill the gaps between the GPS data samples. The presented Kalman filter is enhanced to contain the velocity data on the output. The output velocity data meet the condition of integration and differentiation between the values of the position and the velocity.

English abstract

There are many applications using the Global Positioning System (GPS) as a source of position and velocity data. A main problem of the GPS data is its inconsistency on higher sampling frequencies. The usage of enhanced Kalman Filter is presented to fill the gaps between the GPS data samples. The presented Kalman filter is enhanced to contain the velocity data on the output. The output velocity data meet the condition of integration and differentiation between the values of the position and the velocity.

Keywords

Kalman Filter, Oversampled Data, GPS, Flight Path Reconstruction, Aircraft

RIV year

2011

Released

10.04.2011

Publisher

Brno University of Technology

Location

Brno

ISBN

978-80-214-4273-3

Book

Proceedings of the 17th Conference STUDENT EEICT 2011

Edition

Volume 3

Edition number

NEUVEDEN

Pages from

580

Pages to

584

Pages count

5

Documents

BibTex


@inproceedings{BUT76310,
  author="Petr {Dittrich}",
  title="Application of Kalman Filter to oversampled data from Global Position System",
  annote="There are many applications using the Global Positioning System (GPS) as a source
of position and velocity data. A main problem of the GPS data is its
inconsistency on higher sampling frequencies. The usage of enhanced Kalman Filter
is presented to fill the gaps between the GPS data samples. The presented Kalman
filter is enhanced to contain the velocity data on the output. The output
velocity data meet the condition of integration and differentiation between the
values of the position and the velocity.",
  address="Brno University of Technology",
  booktitle="Proceedings of the 17th Conference STUDENT EEICT 2011",
  chapter="76310",
  edition="Volume 3",
  howpublished="print",
  institution="Brno University of Technology",
  year="2011",
  month="april",
  pages="580--584",
  publisher="Brno University of Technology",
  type="conference paper"
}