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ISSN 2083-6473
ISSN 2083-6481 (electronic version)
 

 

 

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Tomasz Neumann
 

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TransNav, Faculty of Navigation
Gdynia Maritime University
3, John Paul II Avenue
81-345 Gdynia, POLAND
www http://www.transnav.eu
e-mail transnav@am.gdynia.pl
Statistical Analysis of Simulated Radar Target's Movement for the Needs of Multiple Model Tracking Filter
1 Maritime University of Szczecin, Szczecin, Poland
ABSTRACT: The quality of radar target tracking has a great impact on navigational safety at sea. There are many tracking filters used in maritime radars. Large group of them are multiple model filters in which different filter parameters are used for different states (models) of vessel movement. One of possible filter is multiple model neural filter based on General Regression Neural Network. Tuning of such filter means to adjust its parameters for a suitable target movement model. This paper shows the results of an experiment aiming at determining such models based on statistical analysis of target's movement parameters. The research has been carried out with PC-based simulator in which typical radar measuring errors were implemented. Different manoeuvres of targets have been examined. Based on this, the possibility of movement models description has been stated as conclusion.
REFERENCES
Bar Shalom Y., Li X.R.: Estimation and tracking: principles, techniques, and software, YBS, Norwood, 1998.
Bar Shalom Y., Li X.R.: Estimation with Applications to Tracking and Navigation: Theory Algorithms and Software, John Wiley & Sons, Inc., NY USA, 2001
Bole A. G., Dineley W. O., Wall A.: Radar and ARPA Manual, Elsevier Science & Technology Book, 2005
Juszkiewicz W., Stateczny A., GRNN Cascade Neural Filter for Tracked Target Maneuver Estimation, Neural Networks and Soft Computing, Zakopane 2000
Kantak T., Stateczny A., Urbański J.: Basis of automation of navigation (in polish). AMW, Gdynia 1988.
Kazimierski W., Two – stage General Regression Neural Network for radar target tracking, Polish Journal of Environmental Studies, Vol. 17, No 3B, 2008.
Kazimierski W.: Selection of General Regression Neural Network’s Training Sequence in the process of Target Tracking in Maritime Navigational Radars, Polish Journal of Environmental Studies, Vol 16A., 2007
Lee B.J, Park J.B., Joo Y.H., Jin S.H.: Intelligent Kalman Filter for tracking a manoeuvring target, IEE Proceedings: Radar, Sonar and Navigation Vol. 153, IET, Stevenage UK, 2006.
Li X.R, Jilkov V.P.: A Survey of Maneuvering Target Tracking—Part V: Multiple-Model Methods, IEEE Transactions on Aerospace and Electronic Eystems, Vol. 41, 2005.
Nadaraya E. A.: On estimating regression. Theory of Probab. Applicat., vol. 9, pp. 141–142, 1964.
Specht D. F.: A General Regression Neural Network, IEEE Transactions on Neural Network, Vol. 2, No. 6, 1991.
Stateczny A., Felski A., Krotowicz M.: Generating of correlated measurements in navigational research (in polish), Biuletyn WAT, 1987
Stateczny A., Kazimierski W., General Regression Neural Network (GRNN) in the Process of Tracking a Maneuvering Target in ARPA Devices, Proceedings of IRS 2005, Berlin 2005.
Stateczny A., Kazimierski W.: Selection of GRNN Network Parameters for the Needs of State Vector Estimation of Manoeuvring Target in ARPA Devices, SPIE Proceedings 2006
Watson G. S.: Smooth regression analysis. Sankhya Series A, vol. 26, pp. 359–372, 1964
Citation note:
Kazimierski W.: Statistical Analysis of Simulated Radar Target's Movement for the Needs of Multiple Model Tracking Filter. TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation, Vol. 5, No. 3, pp. 329-334, 2011
Authors in other databases:
Witold Kazimierski: Scopus icon24829115600 Scholar iconX7m2hjsAAAAJ

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