Next Article in Journal
Seeker-Azimuth Determination with Gyro Rotor and Optoelectronic Sensors
Next Article in Special Issue
Infrastructure for Integration of Legacy Electrical Equipment into a Smart-Grid Using Wireless Sensor Networks
Previous Article in Journal
Development and Testing of an Integrated Rotating Dynamometer Based on Fiber Bragg Grating for Four-Component Cutting Force Measurement
Previous Article in Special Issue
Analysis of Known Linear Distributed Average Consensus Algorithms on Cycles and Paths
Open AccessArticle

A Novel Energy-Efficient Multi-Sensor Fusion Wake-Up Control Strategy Based on a Biomimetic Infectious-Immune Mechanism for Target Tracking

1
School of Automation & MOE Key Laboratory of Information Fusion Technology, Northwestern Polytechnical University, Xi’an 710072, China
2
MOE Key Laboratory of Micro and Nano Systems for Aerospace, Northwestern Polytechnical University, Xi’an 710072, China
3
School of Automation, Beijing Institute of Technology, Beijing 100081, China
*
Author to whom correspondence should be addressed.
Sensors 2018, 18(4), 1255; https://doi.org/10.3390/s18041255
Received: 15 March 2018 / Revised: 10 April 2018 / Accepted: 11 April 2018 / Published: 18 April 2018
(This article belongs to the Special Issue Smart Communication Protocols and Algorithms for Sensor Networks)
A biomimetic distributed infection-immunity model (BDIIM), inspired by the immune mechanism of an infected organism, is proposed in order to achieve a high-efficiency wake-up control strategy based on multi-sensor fusion for target tracking. The resultant BDIIM consists of six sub-processes reflecting the infection-immunity mechanism: occurrence probabilities of direct-infection (DI) and cross-infection (CI), immunity/immune-deficiency of DI and CI, pathogen amount of DI and CI, immune cell production, immune memory, and pathogen accumulation under immunity state. Furthermore, a corresponding relationship between the BDIIM and sensor wake-up control is established to form the collaborative wake-up method. Finally, joint surveillance and target tracking are formulated in the simulation, in which we show that the energy cost and position tracking error are reduced to 50.8% and 78.9%, respectively. Effectiveness of the proposed BDIIM algorithm is shown, and this model is expected to have a significant role in guiding the performance improvement of multi-sensor networks. View Full-Text
Keywords: immune mechanism; infectious disease; energy efficiency; wake-up strategy; multi-sensor fusion immune mechanism; infectious disease; energy efficiency; wake-up strategy; multi-sensor fusion
Show Figures

Figure 1

MDPI and ACS Style

Zhou, J.; Liang, Y.; Shen, Q.; Feng, X.; Pan, Q. A Novel Energy-Efficient Multi-Sensor Fusion Wake-Up Control Strategy Based on a Biomimetic Infectious-Immune Mechanism for Target Tracking. Sensors 2018, 18, 1255.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop