@inproceedings{cf7f99f741a74d64babd5897ba8da86c,
title = "A multisensor data fusion-based target tracking system",
abstract = "In this paper a multi sensor data fusion-based target tracking system is presented. The system includes neurofuzzy multisensor data fusion (MSDF) in order to overcome the limitation of the use of a single sensor. It has the capability of minimising the noise that contaminates the sensor measurements and excludes the faulty (invalid) measurements from use in the estimation process. Despite being a simple algorithm, it can deal with the data fusion problem using noisy non-linear sensors as well as linear sensors. A neuro-tuzzy kinematics process model is also employed in this target tracking system to cope with the lack of a priori knowledge of the target dynamics. Although no a priori statistical knowledge of the target dynamics and the sensors are involved in the estimation process, the performance of the proposed system is comparable with the Extended Kalman Filter-based target tracking system which uses the exactly known process model of the target.",
keywords = "Kalman filter, Multisensor data fusion, Neuro-fuzzy methods, Target tracking",
author = "N. Mort and Prawito Prajitno",
note = "Publisher Copyright: {\textcopyright} 2002 IEEE.; IEEE International Conference on Industrial Technology, IEEE ICIT 2002 ; Conference date: 11-12-2002 Through 14-12-2002",
year = "2002",
doi = "10.1109/ICIT.2002.1189934",
language = "English",
series = "Proceedings of the IEEE International Conference on Industrial Technology",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "427--432",
booktitle = "IEEE ICIT 2002 - 2002 IEEE International Conference on Industrial Technology",
address = "United States",
}