Research on Design of Free Combat Attack and Defense Action Based on Wireless Sensor Motion Recognition

Article Preview

Abstract:

This paper introduces genetic algorithm in sensor path loss model, improves the target recognition function of sensor, and obtains the sensor target recognition method with relatively high resolution. We use MATLAB software, M function and genetic algorithm toolbox of MATLAB to design the algorithm, and apply sensor target recognition method in the identification of free combat action, and design the free combat movement recognition system based on wireless sensor. In order to verify the effectiveness and reliability of the system, this paper recognizes a set of continuous and rapid transformation of free combat movement, and obtains the curve of action recognition number changing with time, and the continuous action is displayed in the form of visualization. It provides the technical reference for the design of the free combat movement.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

2075-2078

Citation:

Online since:

August 2014

Authors:

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2014 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

* - Corresponding Author

[1] Fan Xiaoping, Xiong Zheyuan, Chen Zhijie, Liu Shaoqiang, Qu Zhihua. Research on video coding in wireless multimedia sensor networks [J]. Journal of communication, 2011, 32(9): 137-146.

Google Scholar

[2] Xiong Zheyuan, Fan Xiaoping, Liu Shaoqiang, Li Yongzhou, Qu Zhihua, Zhong Zhi. JPEG image coding algorithm suitable for wireless multimedia sensor networks [J]. Journal of transducer technology, 2011, 24(10): 1489-1495.

Google Scholar

[3] Lu Yiming, Liu Dong, Liu Jinsong. Information integration requirements and model analysis of intelligent electric power network [J]. Automation of electric power systems, 2010, 34(8): 1-4.

Google Scholar

[4] Ni Jingmin, He Guangyu, Shen Chen et al. Overview of USA smart grid assessment [J]. Automation of electric power systems, 2010, 34(8): 9-13.

Google Scholar

[5] Hu Jing. Strategy jump of strong smart grid [J]. National grid, 2011(1): 25-28.

Google Scholar

[6] Xiong Zheyuan, Fan Xiaoping, Liu Shaoqiang, Li Yongzhou, Zhong Zhi. Image mosaic algorithm of multimedia sensor networks [J]. Research on computer, 2011, 29(5): 1970-(1973).

Google Scholar

[7] Xiong Zheyuan, Fan Xiaoping, Liu Shaoqiang, Qu Zhihua, Zhong Lusheng. Analysis of image communication performance in wireless multimedia sensor network [J]. Computer engineering and applications, 2012, 48(14): 27-32.

Google Scholar

[8] Zhang Qiang, Sun Yugeng, Yang Ting et al. Application of wireless sensor network in intelligent power grid [J]. Chinese electric power, 2010, 43(6): 31-36.

Google Scholar

[9] Chen Lijun, Mao Yingchi, Chen Daoxu et al. The average constraint of wireless sensor network topology control [J]. Journal of computers, 2012, 30(9): 1544-1550.

Google Scholar

[10] Cheng Weifang, Liao Xiangke, Shen Changxiang. The maximum coverage scheduling algorithm of directed sensor networks [J]. Journal of software, 2012(4): 975-984.

Google Scholar

[11] Wen Jun, Jiang Jie, Dou Wenhua. The network optimization and node scheduling algorithm of fair directed sensor [J]. Journal of software, 2011, 20(3): 644-659.

Google Scholar

[12] Tao Dan, Ma Huadong, Liu Liang. The path coverage enhancement algorithm in video sensor network [J]. Acta electronica Sinica, 2011, 36(7): 26-31.

Google Scholar