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Type-2 Fuzzy Extended Kalman Filter for Dynamic Security Monitoring Based on Novel Sensor Fusion
School of Engineering and Computer Science, Oakland University, Rochester, USA
School of Engineering and Computer Science, Oakland University, Rochester, USA
Electrical Engineering Department, Benha University, Benha, Egypt.
- 1 School of Engineering and Computer Science, Oakland University, Rochester, USA
- 2 School of Engineering and Computer Science, Oakland University, Rochester, USA
- 3 Electrical Engineering Department, Benha University, Benha, Egypt.
Journal of Intelligent Learning Systems and Applications·Volume 04 (2012)·Pages 159–168·Published 30 August 2012·DOI10.4236/jilsa.2012.43016
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Abstract
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.
KeywordsSensor SimilaritySensor ComplementarityType-2 Fuzzy
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