Gaussian mixture importance sampling function for unscented SMC-PHD filter

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Gaussian mixture importance sampling function for unscented SMC-PHD filter

The unscented sequential Monte Carlo probability hypothesis density (USMC-PHD) filter has been proposed to improve the accuracy performance of the bootstrap SMC-PHD filter in cluttered environments. However, the USMC-PHD filter suffers from heavy computational complexity because the unscented inform...

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Bibliographic Details
Main Authors:	Yoon, J., Kim, Du Yong, Yoon, K.
Format:	Journal Article
Published:	Elsevier BV 2013
Online Access:	http://hdl.handle.net/20.500.11937/56017

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