Position, Velocity and Acceleration Tracking Using Kalman Filter

Authors

  • G. Tziallas General Department, University of Thessaly, Lamia, Greece.
  • M. Adam Department of Computer and Biomedical Informatics, University of Thessaly, Lamia, Greece.
  • N. Assimakis General Department, National and Kapodistrian University of Athens, Greece.
  • A. Polyzos Cross Software Solutions IKE, Piraeus, Greece.

DOI:

https://doi.org/10.9734/bpi/tpmcs/v9/2441E

Keywords:

Kalman filter, steady state, estimation, prediction

Abstract

Constant acceleration movement in one, two and three dimensions can be modeled using time invariant models. Position, velocity and acceleration tracking is obtained using time invariant Kalman filter and steady state Kalman filter. The derived estimation and prediction are reliable.

Published

2021-05-04

How to Cite

G. Tziallas, M. Adam, N. Assimakis, & A. Polyzos. (2021). Position, Velocity and Acceleration Tracking Using Kalman Filter. Theory and Practice of Mathematics and Computer Science Vol. 9, 30–47. https://doi.org/10.9734/bpi/tpmcs/v9/2441E

Issue

Theory and Practice of Mathematics and Computer Science Vol. 9

Section

Chapters