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Sensors 2018, 18(1), 56;

Mixed H2/H-Based Fusion Estimation for Energy-Limited Multi-Sensors in Wearable Body Networks

Key Laboratory of Communication and Information Systems, Beijing Jiaotong University, Beijing 100044, China
Beijing Municipal Commission of Education, Department of Electronic and Information Engineering, Beijing Jiaotong University, Beijing 100044, China
School of Software Engineering, Beijing Jiaotong University, Beijing 100044, China
School of Information Science and Engineering, Fujian University of Technology, Fuzhou 350118, China
School of Mathematics and Computer Science, Wuhan Polytechnic University, Wuhan 430024, China
Department of Electrical Engineering, National Dong Hwa University, Hualien 97401, Taiwan
Department of Computer Science and Information Engineering, National Ilan University, Yilan 26047, Taiwan
Author to whom correspondence should be addressed.
Received: 21 September 2017 / Revised: 23 December 2017 / Accepted: 24 December 2017 / Published: 27 December 2017
(This article belongs to the Special Issue Sensor-based E-Healthcare System: Greenness and Security)
Full-Text   |   PDF [2391 KB, uploaded 27 December 2017]   |  


In wireless sensor networks, sensor nodes collect plenty of data for each time period. If all of data are transmitted to a Fusion Center (FC), the power of sensor node would run out rapidly. On the other hand, the data also needs a filter to remove the noise. Therefore, an efficient fusion estimation model, which can save the energy of the sensor nodes while maintaining higher accuracy, is needed. This paper proposes a novel mixed H2/H-based energy-efficient fusion estimation model (MHEEFE) for energy-limited Wearable Body Networks. In the proposed model, the communication cost is firstly reduced efficiently while keeping the estimation accuracy. Then, the parameters in quantization method are discussed, and we confirm them by an optimization method with some prior knowledge. Besides, some calculation methods of important parameters are researched which make the final estimates more stable. Finally, an iteration-based weight calculation algorithm is presented, which can improve the fault tolerance of the final estimate. In the simulation, the impacts of some pivotal parameters are discussed. Meanwhile, compared with the other related models, the MHEEFE shows a better performance in accuracy, energy-efficiency and fault tolerance. View Full-Text
Keywords: fusion estimation; wearable sensors; energy-efficiency; accuracy fusion estimation; wearable sensors; energy-efficiency; accuracy

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Li, C.; Zhang, Z.; Chao, H.-C. Mixed H2/H-Based Fusion Estimation for Energy-Limited Multi-Sensors in Wearable Body Networks. Sensors 2018, 18, 56.

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