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The Evaluation of the Performance of Different Filtering Approaches in Tracking Problem and the Effect of Noise Variance

Authors: Mohammad Javad Mollakazemi, Farhad Asadi, Aref Ghafouri

Abstract:

Performance of different filtering approaches depends on modeling of dynamical system and algorithm structure. For modeling and smoothing the data the evaluation of posterior distribution in different filtering approach should be chosen carefully. In this paper different filtering approaches like filter KALMAN, EKF, UKF, EKS and smoother RTS is simulated in some trajectory tracking of path and accuracy and limitation of these approaches are explained. Then probability of model with different filters is compered and finally the effect of the noise variance to estimation is described with simulations results.

Keywords: Gaussian approximation, KALMAN smoother, Parameter estimation.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1099144

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References:


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[10] Farhad Asadi, Mohammad javad Mollakazemi, “Investigation of fluctuation locations and effect of data distribution in time series dynamical regimes”.. Accepted and oral presentation in ICBCBBE 2014: XII International Conference on Bioinformatics, Computational Biology and Biomedical Engineering, October, 27-28, 2014, Istanbul, turkey.
[11] Farhad Asadi, Mohammad javad Mollakazemi, Aref Ghafouri, “The influence of parameters of modeling and data distribution for optimal condition on locally weighted projection regression method”.. Accepted and oral presentation in ICMSE 2014: XII International Conference on Mathematics and Statistical Engineering, October, 27-28, 2014, Istanbul, turkey.
[12] Mohammad javad Mollakazemi, Farhad Asadi, “Real-time adaptive obstacle avoidance in dynamic environments with different D-S”.. Accepted and oral presentation in ICARM 2014: XII International Conference on Automation, Robotics and Mechatronics, October, 27-28, 2014, Istanbul, turkey.