Title :
On the reduction of Gaussian inverse Wishart mixtures
Author :
Granström, Karl ; Orguner, Umut
Author_Institution :
Dept. of Electr. Eng., Linkoping Univ., Linkoping, Sweden
Abstract :
This paper presents an algorithm for reduction of Gaussian inverse Wishart mixtures. Sums of an arbitrary number of mixture components are approximated with single components by analytically minimizing the Kullback-Leibler divergence. The Kullback-Leibler difference is used as a criterion for deciding whether or not two components should be merged, and a simple reduction algorithm is given. The reduction algorithm is tested in simulation examples in both one and two dimensions. The results presented in the paper are useful in extended target tracking using the random matrix framework.
Keywords :
Gaussian distribution; Gaussian processes; target tracking; Gaussian inverse Wishart mixtures; Kullback-Leibler divergence; arbitrary number; mixture components; random matrix framework; target tracking; Approximation algorithms; Approximation methods; Covariance matrix; Merging; Signal processing algorithms; Symmetric matrices; Target tracking; Gaussian inverse Wishart; Kullback-Leibler divergence; extended target; mixture reduction; random matrix;
Conference_Titel :
Information Fusion (FUSION), 2012 15th International Conference on
Conference_Location :
Singapore
Print_ISBN :
978-1-4673-0417-7
Electronic_ISBN :
978-0-9824438-4-2
