Type-2 Fuzzy Extended Kalman Filter for Dynamic Security Monitoring Based on Novel Sensor Fusion
Type-2 Fuzzy Extended Kalman Filter for Dynamic Security Monitoring Based on Novel Sensor Fusion作者机构：Electrical Engineering Department Benha University Benha Egypt. School of Engineering and Computer Science Oakland University Rochester USA
出 版 物：《Journal of Intelligent Learning Systems and Applications》 (智能学习系统与应用（英文）)
年 卷 期：2012年第4卷第3期
页 面：159-168页
学科分类：07[理学] 0701[理学-数学] 070101[理学-基础数学]
主 题：Sensor Similarity Sensor Complementarity Type-2 Fuzzy
摘 要：In this paper, we have focused on several relevant sensors [Laser (for speed measurements), Sonar (for space scanning) and RF (for access rights)] to cooperate in monitoring the security status of multiple dynamic agent in surveillance area. Such coordination is achieved by employing novel concepts of sensors similarity and complementarity. Furthermore, this system is aided with Extended Kalman Filter (EKF) in order to estimate the agent’s non-linear movement. Finally, transforms system state to be able to make a security suspiciousness decision by using type-2 fuzzy logic system to handle uncertainty. It is shown that the system performance can exhibit promising improvements for this dynamic security monitoring application.
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