Computationally-tractable approximate PHD and CPHD filters for superpositional sensors

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Computationally-tractable approximate PHD and CPHD filters for superpositional sensors

In this paper we derive computationally-tractable approximations of the Probability Hypothesis Density (PHD) and Cardinalized Probability Hypothesis Density (CPHD) filters for superpositional sensors with Gaussian noise. We present implementations of the filters based on auxiliary particle filter ap...

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Bibliographic Details
Main Authors:	Nannuru, S., Coates, M., Mahler, Ronald
Format:	Journal Article
Published:	Institute of Electrical and Electronic Engineers 2013
Online Access:	http://hdl.handle.net/20.500.11937/55359

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