TY - GEN
T1 - Globally optimal weighted fusion Kalman filter with colored measurement noises
AU - Tien, David
AU - Sun, X. J.
AU - Yan, G. M.
N1 - Includes bibliographical references.
PY - 2019/3
Y1 - 2019/3
N2 - In this paper, the multisensor systems with ARMA coloured measurement noise are converted to those with the same local dynamic model and uncorrelated noises by using the state augmented method. Furthermore, the globally optimal weighted measurement fusion Kalman filter is given. Compared with the existing methods transforming the multisensor systems into those with the same or different local dynamic models and correlated noises, the transformed system models in this paper are applicable to the weighted measurement fusion algorithm. Although the dimension of augmented state is higher than that in the existing references, the computational load and complexity of the whole optimal fusion Kalman filter are better than the existing fusers. The simulation example for a 3-sensors radar tracking system with colored measurement noises shows its effectiveness.
AB - In this paper, the multisensor systems with ARMA coloured measurement noise are converted to those with the same local dynamic model and uncorrelated noises by using the state augmented method. Furthermore, the globally optimal weighted measurement fusion Kalman filter is given. Compared with the existing methods transforming the multisensor systems into those with the same or different local dynamic models and correlated noises, the transformed system models in this paper are applicable to the weighted measurement fusion algorithm. Although the dimension of augmented state is higher than that in the existing references, the computational load and complexity of the whole optimal fusion Kalman filter are better than the existing fusers. The simulation example for a 3-sensors radar tracking system with colored measurement noises shows its effectiveness.
KW - Colored measurement noises
KW - Kalman filter
KW - Multisensor information fusion
KW - Radar tracking system
KW - Weighted measurement fusion
UR - http://www.scopus.com/inward/record.url?scp=85074426780&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85074426780&partnerID=8YFLogxK
U2 - 10.1109/ICAICA.2019.8873517
DO - 10.1109/ICAICA.2019.8873517
M3 - Conference paper
SN - 9781728112244 (Print on demand)
T3 - Proceedings of 2019 IEEE International Conference on Artificial Intelligence and Computer Applications, ICAICA 2019
SP - 79
EP - 82
BT - Proceedings of 2019 IEEE International Conference on Artificial Intelligence and Computer Applications, ICAICA 2019
PB - IEEE, Institute of Electrical and Electronics Engineers
T2 - 2019 IEEE International Conference on Artificial Intelligence and Computer Applications, ICAICA 2019
Y2 - 29 March 2019 through 31 March 2019
ER -