With the increasing application of wireless sensor networks and the emergence and application of Internet, information fusion technology has gradually integrated into social life, bringing unprecedented convenience to people's lives. Traditionally, target recognition can only rely on a sensor of a nature to collect target data. Although the operation is simple, the disadvantages are obvious: it can only be applied in a simple environment, and the recognition efficiency and recognition accuracy are low. In this paper, the multi-sensors of the same or different nature are effectively combined, and the original information of the target is obtained at the same time. The multi-azimuth and multi-attribute eigenvalue data of the target are obtained by the feature extraction method, and the feature value data is passed through the feature fusion algorithm. Feature fusion is performed to effectively improve recognition efficiency and recognition accuracy.

Zhenhua Chen. Multi-Sensor Information Fusion Technology and Its Application in Target Recognition. International Journal of New Developments in Engineering and Society (2019) Vol.3, Issue 5: 120-125. https://doi.org/10.25236/IJNDES.030514.

[1] Sun Ning, Qin Hongjun, Zhang Li, et al.(2017). Vehicle Target Recognition Method Based on Multi-sensor Information Fusion. Automotive Engineering, vol. 39, no.11, pp. 1310-1315.
[2] Liu Chaoqiang(2015). Research on Target Recognition Technology Based on Multi-sensor Feature Information Fusion.Shenyang University of Technology.
[3] WANG Junna, LEI Jing(2016). Overview of Multi-sensor Information Fusion and Its Application. Information Recording Materials, vol. 17, no.05, pp. 78-79.
[4] Meng Ke, Wu Chaozhong, Chen Zhijun, et al.(2016). Human vehicle collision risk identification and intelligent vehicle control system . Traffic Information and Safety, vol. 34, no.6, pp. 22-29.
[5] Pan Quan, Wang Zengfu, Liang Yan, et al.(2012). The basic methods and progress of information fusion theory (II) . Control Theory and Applications, vol. 29, no.10, pp. 599 - 615.
[6] Li Wenwen(2016). Application of Multi-sensor Fusion Technology in Intelligent Transportation. Shandong Industrial Technology, no.14, pp. 136-136.
[7] Zhang Qing,Summer,Fan Yufei, et al.(2017). Moving Target Tracking Algorithm Based on Multi-sensor Fusion.Modern Electronic Technique, vol. 40, no. 3, pp.43-46.
[8] Song Qiang, Xiong Wei, He You(2012). Multi-sensor multi-objective system error fusion estimation algorithm . Journal of Beijing University of Aeronautics and Astronautics, vol. 38, no.6, pp. 835 - 841.
[9] Zhang Wen(2017). Research on autonomous navigation method of indoor robot based on multi-sensor fusion. Beijing: University of Science and Technology of China.
[10] Ning Xuanjie(2014). Research and Application of Key Technologies of Multi-sensor Information Fusion Based on Air Defense Radar Network. Shenyang: Northeastern University.