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Comparison of Angle-only Filtering Algorithms in 3D using Cartesian and Modified Spherical Coordinates

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

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Comparison of Angle-only Filtering Algorithms in 3D using Cartesian and Modified Spherical Coordinates. / Mallick, Mahendra; Morelande, Mark; Mihaylova, Lyudmila et al.
Information Fusion (FUSION), 2012 15th International Conference on. IEEE, 2012. p. 1392-1399.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

Harvard

Mallick, M, Morelande, M, Mihaylova, L, Arulampalam, S & Yan, Y 2012, Comparison of Angle-only Filtering Algorithms in 3D using Cartesian and Modified Spherical Coordinates. in Information Fusion (FUSION), 2012 15th International Conference on. IEEE, pp. 1392-1399, The 15th International Conference on Information Fusion, Singapore, 9/07/12. <http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=6289970>

APA

Mallick, M., Morelande, M., Mihaylova, L., Arulampalam, S., & Yan, Y. (2012). Comparison of Angle-only Filtering Algorithms in 3D using Cartesian and Modified Spherical Coordinates. In Information Fusion (FUSION), 2012 15th International Conference on (pp. 1392-1399). IEEE. http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=6289970

Vancouver

Mallick M, Morelande M, Mihaylova L, Arulampalam S, Yan Y. Comparison of Angle-only Filtering Algorithms in 3D using Cartesian and Modified Spherical Coordinates. In Information Fusion (FUSION), 2012 15th International Conference on. IEEE. 2012. p. 1392-1399

Author

Mallick, Mahendra ; Morelande, Mark ; Mihaylova, Lyudmila et al. / Comparison of Angle-only Filtering Algorithms in 3D using Cartesian and Modified Spherical Coordinates. Information Fusion (FUSION), 2012 15th International Conference on. IEEE, 2012. pp. 1392-1399

Bibtex

@inproceedings{d663e2063fbf42f99fa71335425341ec,
title = "Comparison of Angle-only Filtering Algorithms in 3D using Cartesian and Modified Spherical Coordinates",
abstract = "We compare the performance of the extended Kalman filter (EKF), unscented Kalman filter (UKF), and particle filter (PF) for the angle-only filtering problem in 3D using bearing and elevation measurements from a single maneuvering sensor. These nonlinear filtering algorithms use discrete-time dynamic and measurement models. Two types of coordinate systems are considered, Cartesian coordinates and modified spherical coordinates (MSC) for the relative state vector. The paper presents new algorithms using the UKF and PF with the MSC. We also present an improved filter initialization algorithm. Numerical results from Monte Carlo simulations show that the EKF-MSC and UKF-MSC have the best state estimation accuracy among all nonlinear filters considered and have comparable accuracy with modest computational cost. ",
keywords = "bearings only target tracking, 3D model, Angle-only filtering in 3D , Extended Kalman filter (EKF), Modified spherical coordinates (MSC), Nonlinear filtering (NLF), Particle filter (PF), Unscented Kalman filter (UKF)",
author = "Mahendra Mallick and Mark Morelande and Lyudmila Mihaylova and Sanjeev Arulampalam and Yanjun Yan",
year = "2012",
month = jul,
day = "1",
language = "English",
isbn = "978-1-4673-0417-7",
pages = "1392--1399",
booktitle = "Information Fusion (FUSION), 2012 15th International Conference on",
publisher = "IEEE",
note = "The 15th International Conference on Information Fusion ; Conference date: 09-07-2012 Through 12-07-2012",

}

RIS

TY - GEN

T1 - Comparison of Angle-only Filtering Algorithms in 3D using Cartesian and Modified Spherical Coordinates

AU - Mallick, Mahendra

AU - Morelande, Mark

AU - Mihaylova, Lyudmila

AU - Arulampalam, Sanjeev

AU - Yan, Yanjun

PY - 2012/7/1

Y1 - 2012/7/1

N2 - We compare the performance of the extended Kalman filter (EKF), unscented Kalman filter (UKF), and particle filter (PF) for the angle-only filtering problem in 3D using bearing and elevation measurements from a single maneuvering sensor. These nonlinear filtering algorithms use discrete-time dynamic and measurement models. Two types of coordinate systems are considered, Cartesian coordinates and modified spherical coordinates (MSC) for the relative state vector. The paper presents new algorithms using the UKF and PF with the MSC. We also present an improved filter initialization algorithm. Numerical results from Monte Carlo simulations show that the EKF-MSC and UKF-MSC have the best state estimation accuracy among all nonlinear filters considered and have comparable accuracy with modest computational cost.

AB - We compare the performance of the extended Kalman filter (EKF), unscented Kalman filter (UKF), and particle filter (PF) for the angle-only filtering problem in 3D using bearing and elevation measurements from a single maneuvering sensor. These nonlinear filtering algorithms use discrete-time dynamic and measurement models. Two types of coordinate systems are considered, Cartesian coordinates and modified spherical coordinates (MSC) for the relative state vector. The paper presents new algorithms using the UKF and PF with the MSC. We also present an improved filter initialization algorithm. Numerical results from Monte Carlo simulations show that the EKF-MSC and UKF-MSC have the best state estimation accuracy among all nonlinear filters considered and have comparable accuracy with modest computational cost.

KW - bearings only target tracking

KW - 3D model

KW - Angle-only filtering in 3D

KW - Extended Kalman filter (EKF)

KW - Modified spherical coordinates (MSC)

KW - Nonlinear filtering (NLF)

KW - Particle filter (PF)

KW - Unscented Kalman filter (UKF)

M3 - Conference contribution/Paper

SN - 978-1-4673-0417-7

SP - 1392

EP - 1399

BT - Information Fusion (FUSION), 2012 15th International Conference on

PB - IEEE

T2 - The 15th International Conference on Information Fusion

Y2 - 9 July 2012 through 12 July 2012

ER -