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Study of the Effectiveness of Different Kalman Filtering Methods and Smoothers in Object Tracking Based on Simulation Tests Cover

Study of the Effectiveness of Different Kalman Filtering Methods and Smoothers in Object Tracking Based on Simulation Tests

Open Access
|Feb 2015

Abstract

In navigation practice, there are various navigational architecture and integration strategies of measuring instruments that affect the choice of the Kalman filtering algorithm. The analysis of different methods of Kalman filtration and associated smoothers applied in object tracing was made on the grounds of simulation tests of algorithms designed and presented in this paper. EKF (Extended Kalman Filter) filter based on approximation with (jacobians) partial derivations and derivative-free filters like UKF (Unscented Kalman Filter) and CDKF (Central Difference Kalman Filter) were implemented in comparison. For each method of filtration, appropriate smoothers EKS (Extended Kalman Smoother), UKS (Unscented Kalman Smoother) and CDKS (Central Difference Kalman Smoother) were presented as well. Algorithms performance is discussed on the theoretical base and simulation results of two cases are presented.

DOI: https://doi.org/10.2478/rgg-2014-0008 | Journal eISSN: 2391-8152 | Journal ISSN: 0867-3179
Language: English
Page range: 1 - 22
Published on: Feb 3, 2015
Published by: Warsaw University of Technology
In partnership with: Paradigm Publishing Services
Publication frequency: 2 issues per year

© 2015 Marcin Malinowski, Janusz Kwiecień, published by Warsaw University of Technology
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.