Journal is indexed in following databases:
- SCOPUS
- Web of Science Core Collection - Journal Citation Reports
- EBSCOhost
- Directory of Open Access Journals
- TRID Database - Transportation Research Board
- Index Copernicus Journals Master List
- BazTech
- Google Scholar
2023 Journal Impact Factor - 0.7
2023 CiteScore - 1.4
ISSN 2083-6473
ISSN 2083-6481 (electronic version)
Editor-in-Chief
Associate Editor
Prof. Tomasz Neumann
Published by
TransNav, Faculty of Navigation
Gdynia Maritime University
3, John Paul II Avenue
81-345 Gdynia, POLAND
e-mail transnav@umg.edu.pl
A Study on the Performance Comparison of Three Optimal Alpha-Beta-Gamma Filters and Alpha-Beta-Gamma-Eta Filter for a High Dynamic Target
1 Korea Maritime and Ocean University, Busan, South Korea
2 Jomo Kenyatta University of Agriculture and Technology, Nairobi, Kenya
2 Jomo Kenyatta University of Agriculture and Technology, Nairobi, Kenya
ABSTRACT: The Alpha-Beta-Gamma tracking filter is useful for tracking a constant acceleration target with zero lag error in the steady state. It, however, depicts a constant lag error for a maneuvering target. Various algorithms of the Alpha-Beta-Gamma tracking filter exist in literature and each one of them presents its own unique challenges and advantages depending on the design requirement.
This study investigates the operation of three Alpha-Beta-Gamma tracking filter design methods which include Benedict-Bordner also known as the Simpson filter, Gray-Murray filter and the fading memory constant acceleration filter. These filters are then compared based on the ability to reduce noise and follow a maneuvering target with minimum lag error, against the jerky model Alpha-Beta-Gamma-Eta. Results obtained from simulations of the input model of the target dynamics under consideration indicate an improvement in performance of the jerky model in comparison with the constant acceleration models.
KEYWORDS: Kalman Filter, Integrated Navigation, Alpha-Beta-Gamma Filter, Target Dynamics, Benedict-Bordner Filter, Simpson Filter, Gray-Murray Filter, Alpha-Beta-Gamma-Eta Filter
REFERENCES
Benedict, T. R. & Bordner, G. W. 1962. Synthesis of an Optimal Set of Radar Track-While-Scan Smoothing Equations. IRE Trans. on Automatic Control. AC-7: pp.27-32.
Brookner, E. 1998. Tracking and Kalman filtering made easy. New York: Wiley.
Gray, J. E. & Murray, W. J. 1993. A Derivation of an Analytic Expression for the Tracking Index for the α-β-γ Filter. IEEE Trans. On Aerospace and Electronic Systems Vol. 29 (3).
Jury, E. I. 1964. Theory and application of the z-transform method. New York: Wiley.
Kalata, P. R. 1984. The tracking index: A generalized parameter for α - β and α - β - γ target tracker. IEEE Trans. on Aerospace and Electronic Systems AES-20 (2): pp. 174-181.
Pan B.F., Njonjo A.W. & Jeong T.G. 2016. Basic Study of the Optimization of the Gain Parameters α, β and γ of a Tracking Module for ARPA system on Board High Dynamic Warships Proceedings, Journal of Navigation and Port Research Vol.40 (5): pp.241-247.
Pan B.F., Njonjo, A.W. & Jeong, T.G. 2016. A Study of Optimization of α-β-γ-η filter for tracking a high Dynamic target. Proceedings, 2016 Asia Navigation conference.
Simpson, H. R. April 1963. Performance Measures and Optimization Condition for a Third Order Sampled-Data Tracker. IEEE Transactions on Automatic Control Vol. AC8: pp. 182–183.
Citation note:
Jeong T.G., Njonjo A.W., Pan B.F.: A Study on the Performance Comparison of Three Optimal Alpha-Beta-Gamma Filters and Alpha-Beta-Gamma-Eta Filter for a High Dynamic Target. TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation, Vol. 11, No. 1, doi:10.12716/1001.11.01.05, pp. 55-61, 2017
Other publications of authors:
File downloaded 1043 times
