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 978-1-4673-0417-7Full text not available from this repository.
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:||Q Science > QA Mathematics > QA75 Electronic computers. Computer science|
|Departments:||Faculty of Science and Technology > School of Computing & Communications|
|Deposited On:||27 Jul 2012 14:07|
|Last Modified:||27 Mar 2017 02:16|
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