Distributed Multisensor Fusion With Outlier Clearance Technique for Sensor Networks
- Resource Type
- Conference
- Authors
- Dai, Tianwei; Ding, Zhengtao
- Source
- 2018 IEEE 14th International Conference on Control and Automation (ICCA) Control and Automation (ICCA), 2018 IEEE 14th International Conference on. :486-491 Jun, 2018
- Subject
- Aerospace
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Wireless sensor networks
Sensor fusion
Anomaly detection
Nickel
Real-time systems
Reliability
Computational modeling
- Language
- ISSN
- 1948-3457
One challenge faced by sensor fusion strategy designed for sensor networks is to real-time achieve high reliability estimated data with the inaccuracy and fault in raw sensor measurements. In this paper, we present an online outlier clearance technique with low computational complexity and memory usage inspired by the nearest neighbor rule that can identify and remove the spurious data in the distributed multisensor fusion process. The proposed technique is fully localized and thus saves communication overhead as well as has a good extension as deployed nodes increasing. In this technique, we define a weighted average distance-based outlier factor criterion to detect the outlier and replace it with estimated data. With the help of contrast simulations, in which we adopt other two typical techniques, it illustrates that the proposed technique provides better performance in real-time clearing outlier during the sensor fusion process without the prior knowledge of outlier.