Nonlinear Target Identification and Tracking Using UKF

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http://doi.ieeecomputersociety.org/10.1109/GrC.2007.97

2007 IEEE International Conference on ...

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	ASCII Text	x
	Dilip Gopichand Khairnar, S.N. Merchant, U.B. Desai, "Nonlinear Target Identification and Tracking Using UKF," Granular Computing, IEEE International Conference on, pp. 761, 2007 IEEE International Conference on Granular Computing (GRC 2007), 2007.

	BibTex	x
	@article{ 10.1109/GrC.2007.97, author = {Dilip Gopichand Khairnar and S.N. Merchant and U.B. Desai}, title = {Nonlinear Target Identification and Tracking Using UKF}, journal ={Granular Computing, IEEE International Conference on}, volume = {0}, year = {2007}, isbn = {0-7695-3032-X}, pages = {761}, doi = {http://doi.ieeecomputersociety.org/10.1109/GrC.2007.97}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Granular Computing, IEEE International Conference on TI - Nonlinear Target Identification and Tracking Using UKF SN - 0-7695-3032-X SP EP A1 - Dilip Gopichand Khairnar, A1 - S.N. Merchant, A1 - U.B. Desai, PY - 2007 VL - 0 JA - Granular Computing, IEEE International Conference on ER -

Dilip Gopichand Khairnar

S.N. Merchant

U.B. Desai

In this paper, we implemented target identification al- gorithm using Dempster Shafer Theory (DST) and tracking algorithm using Extended Kalman Filter (EKF) and Un- scented Kalman Filter (UKF). A tracking filter is developed and simulated based on UKF to track nonlinear, ballistic and reentry targets. Comparison of EKF and UKF for non- linear targets tracking are presented based on the simula- tion results. Simulated results gives more supporting points to use UKF for nonlinear target tracking rather using EKF.

Citation:

Dilip Gopichand Khairnar, S.N. Merchant, U.B. Desai, "Nonlinear Target Identification and Tracking Using UKF," grc, pp.761, 2007 IEEE International Conference on Granular Computing (GRC 2007), 2007

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