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Continuous-Discrete Filtering using EKF, UKF, and PF

Mallick, Mahendra and Morelande, Mark and Mihaylova, Lyudmila (2012) Continuous-Discrete Filtering using EKF, UKF, and PF. In: Information Fusion (FUSION), 2012 15th International Conference on :. IEEE, pp. 1087-1094. ISBN 978-1-4673-0417-7

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Continuous-discrete filtering (CDF) arises in many real-world problems such as ballistic projectile tracking, ballistic missile tracking, bearing-only tracking in 2D, angle-only tracking in 3D, and satellite orbit determination. We develop CDF algorithms using the extended Kalman filter (EKF), unscented Kalman filter (UKF), and particle filter (PF) with applications to the angle-only tracking in 3D. The modified spherical coordinates are used to represent the target state. Monte Carlo simulations are performed to compare the performance and computational complexity of the proposed filtering algorithms. Our results show that the CDF algorithms based on the EKF and UKF have the best state estimation accuracy and nearly the same computational cost.

Item Type: Contribution in Book/Report/Proceedings
Uncontrolled Keywords: continuous-discrete filtering ; unscented Kalman filter ; particle filter ; Angle-only filtering in 3D ; Continuous-discrete Extended Kalman filter ; Continuous-discrete Particle filter ; Continuous-discrete Unscented Kalman filter ; Continuous-discrete filtering (CDF) ; Modified spherical coordinates (MSC)
Subjects: ?? qa75 ??
Departments: Faculty of Science and Technology > School of Computing & Communications
ID Code: 56272
Deposited By: ep_importer_pure
Deposited On: 27 Jul 2012 14:07
Refereed?: No
Published?: Published
Last Modified: 17 Jul 2018 06:33
Identification Number:

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