Abstract
For observation information from multiple sensors to analyze consolidated. To arrive at decisions and the information needed to estimate task processing, a novel fusion method is proposed based on the approach degree and weights. The method calculate mean and variance based on the measured sensor’s data, Using the maximum and minimum approach degree of this fuzzy set, the approach degree of the measured data from various sensors is processed quantitatively, eliminating outlier data by Grubbs method, assigned the weight’s of data measured in the fusion process reasonably, so that the final expression of the data fusion is obtained, thus the data fusion of multi-sensor is realized. The results demonstrate that this method can bring higher fusion precision and more suitable for microcontroller and embedded systems applications.
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References
Hall, D.L.: Mathematical techniques in multisensor data fusion. Artech House, Boston (1992)
Liu, C.R.: Discussion on ballistic missile guidance technology. Navy Aeronautical Engineering Institute (2002)
Man, S., Yang, H., Peng, Y., Wang, X.: ARM9-based embedded wireless smart home gateway design. Computer Application (2010)
Hashemipour, H.R., Roy: Decentralized structures for parallel Kalman filtering. IEEE Transactions on AC (1998)
Carlson, N.A.: Federated square root filter for decentralized parallel processes. IEEE T-AES (1990)
Niu, Y.-P., Cheng, S.: Based on Ultrasonic Ranging System. Ordnance Industry Automation (April 2005)
Su W., Gong B.J., Pan L.: Ultrasonic distance measurement error analysis. Sensor Technology (June 2004)
Sun, P.-Y., Li, J.Z., Tang, Y., Liu, Y.: AVR microcontroller based diesel engine oil - water emulsion-line automatic control system. Test and Measurement Technology (February 2005)
Lei, J.: LM567 and the ultrasonic detection. Electronic Technology (April 2004)
Jian, L.X.: Microcontroller-based gasoline tank of gasoline vapor pressure measurement and control system. Electronic Instrumentation Customer (June 2006)
Fang, W.B., Min, L., Haibin, X.: Ultrasonic distance sensor development. Hubei University of Technology (June 2004)
Hong X., Wu S.S., TRADITIONAL, Zheng Y.: ultrasonic Driving Circuit. Henan Vocation (March 1999)
Wang, L., Lei, S., Yu, J.: Based on PC and AT89C52 single-chip serial communication protocol design. Electrical Engineering Technology (February 2006)
Zhang S., Chen J.: Combine harvester automatic alarm system design. Agricultural Mechanization Research (March 2002)
Lee M.S.: Ultrasonic distance measurement principle and practice techniques. Practical Testing Techniques (January 1994)
Hui, Y.: Based on ultrasonic sensors automatic header height control system of Northwest Agriculture and Forestry University (2007)
Chen, J.: Obstacle discrimination based on ultrasonic sensors systematic study. Northwest Agriculture and Forestry University (2005)
Chen, Y.: Microcontroller based ultrasonic ranging system. Huazhong University of Science (2004)
Wang, Q.: Corn combine harvester yield monitor system intelligence research. China Agricultural University (2005)
Jiang, C.: Obstacle discrimination based on ultrasonic sensors systematic study. Northwest Agriculture and Forestry University (2005)
Ju, L.: ultrasonic distance measurement principle and its large electrode extrusion process application. Hunan University (2005)
Zhou, J.: Dibble fertilizing water planter control system design; Northwest Agriculture and Forestry University (2006)
Jiang, X.: Based on the “electronic identity card” model of vehicle identification system research Yanbian University (2007)
Han, Y.: Utility vehicle protection device design and implementation. Daqing Petroleum Institute (2006)
Qi, H.: Car reversing radar system research. Harbin Institute of Technology (2006)
Djenouri, D., Khelladi, L., Badache, N.: A survey of security issues in mobile ad hoc and sensor networks. IEEE Communications Surveys & Tutorials 7(4), 2–28 (2005)
Wang, Y., Attebury, G., Ramamurthy, B.: A survey of security issues in wireless sensor networks. IEEE Communications Surveys & Tutorials 8(2), 2–23 (2006)
Zhou, Y., Fang, Y., Zhang, Y.: Securing wireless sensor networks: a survey. IEEE Communications Surveys & Tutorials 10(3), 6–28 (2008)
Ozdemir, S., Cam, H.: Integration of False Data Detection With Data Aggregation and Confidential Transmission in Wireless Sensor Networks. IEEE/ACM Transactions on Networking 18(3), 736–749 (2010)
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Lu, H. (2013). Data Fusion Algorithm Based on Ultrasonic Sensor Network. In: Yang, Y., Ma, M., Liu, B. (eds) Information Computing and Applications. ICICA 2013. Communications in Computer and Information Science, vol 392. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-53703-5_1
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DOI: https://doi.org/10.1007/978-3-642-53703-5_1
Publisher Name: Springer, Berlin, Heidelberg
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