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Kalman Filter Tracking

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International Journal of Computer Applications
© 2014 by IJCA Journal
Volume 89 - Number 9
Year of Publication: 2014
Authors:
Nasser H. Ali
Ghassan M. Hassan
10.5120/15530-4315

Nasser H Ali and Ghassan M Hassan. Article: Kalman Filter Tracking. International Journal of Computer Applications 89(9):15-18, March 2014. Full text available. BibTeX

@article{key:article,
	author = {Nasser H. Ali and Ghassan M. Hassan},
	title = {Article: Kalman Filter Tracking},
	journal = {International Journal of Computer Applications},
	year = {2014},
	volume = {89},
	number = {9},
	pages = {15-18},
	month = {March},
	note = {Full text available}
}

Abstract

Kalman filter estimates the state of a dynamic system, even if the precise form of the system is unknown. The filter is very powerful in the sense that it supports estimations of past and even future states. The description of the standard Kalman filter and its algorithms with the two main steps, the prediction step and the correction step. Furthermore the extended Kalman filter is discussed, which represents the conversion of the Kalman filter to nonlinear systems. Finally these filter was tested on aircraft tracking, and sinus wave using MATLAB.

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