Abstract
In this paper, classification of air vehicles according to their types is studied. Demspter-Shafer theory is utilized for this purpose. The target tracker data is used for obtaining the probability masses by comparing it with the prior information. Prior information is modeled as the probability density function of the features used for classification. The prior information models the selected features as Gaussian mixtures while the tracker data models the same features as non-parametric density. This new methodology is tested on real data.
The original version of this chapter was revised: The limits of the integrals in the equations (2-a), (2-c), (2-e), (2-g), (2-i), (2-k), (2-m), which are located in pages 395–397 are corrected. The erratum to this chapter is available at 10.1007/978-3-319-11191-9_48
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Turhan, H.I., Demirekler, M., Gunay, M. (2014). A Novel Methodology for Target Classification Based on Dempster-Shafer Theory. In: Cuzzolin, F. (eds) Belief Functions: Theory and Applications. BELIEF 2014. Lecture Notes in Computer Science(), vol 8764. Springer, Cham. https://doi.org/10.1007/978-3-319-11191-9_43
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DOI: https://doi.org/10.1007/978-3-319-11191-9_43
Publisher Name: Springer, Cham
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