Publication detail

Application of Kalman Filter to oversampled data from Global Position System

DITTRICH, P. CHUDÝ, 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

journal article - other

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

09.06.2011

Publisher

NEUVEDEN

Location

NEUVEDEN

ISBN

1802-4564

Periodical

ElectroScope - http://www.electroscope.zcu.cz

Year of study

2011

Number

2

State

CZ

Pages count

6

Documents

BibTex


@article{BUT76382,
  author="Petr {Dittrich} and Peter {Chudý}",
  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="NEUVEDEN",
  chapter="76382",
  edition="NEUVEDEN",
  howpublished="print",
  institution="NEUVEDEN",
  number="2",
  volume="2011",
  year="2011",
  month="june",
  pages="0--0",
  publisher="NEUVEDEN",
  type="journal article - other"
}