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Statistical Analysis of Simulated Radar Target's Movement for the Needs of Multiple Model Tracking Filter

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EN
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EN
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 differ-ent filter parameters are used for different states (models) of vessel movement. One of possible filter is multi-ple 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 de-termining 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.
Twórcy
  • Maritime University of Szczecin, Poland
Bibliografia
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  • [9] 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.
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  • [14] 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
  • [15] Stateczny A., Kazimierski W.: The Process of Radar Tracking by Means of GRNN Artificial Neural Network with Dy-namically Adapted Teaching Sequence Length in Algo-rithmic Depiction, Proceedeings of 7th International Symposium of Navigation TransNav2007, Gdynia 2007
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Bibliografia
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