Threat assessment is one of the most important parts of the tactical decisions, and it has a very important influence on task allocation. An application of fuzzy cognitive map (FCM) for target threat assessment in the air combat is introduced. Considering the fact that the aircrafts participated in the cooperation may not have the same threat assessment mechanism, two different FCM models are established. Using the method of combination, the model of cooperative threat assessment in air combat of multi-aircrafts is established. Simulation results show preliminarily that the method is reasonable and effective. Using FCM for threat assessment is feasible. Key words: threat assessment| synthetic fuzzy cognitive map (FCM)| multi-aircrafts| cooperative air combat
CHEN Jun 1 (陈军), YU Guan-hua 2 (俞冠华), GAO Xiao-guang 1 (高晓光)
. Cooperative Threat Assessment of Multi-aircrafts Based on Synthetic Fuzzy Cognitive Map[J]. Journal of Shanghai Jiaotong University(Science), 2012
, 17(2)
: 228
-232
.
DOI: 10.1007/s12204-012-1257-1
[1] Yao Lei, Wang Hong-ming, Zheng Feng, et al. Study fuzzy clustering method of air target threat assessment[J]. Journal of Wuhan University of Technology:
Transportation Science & Engineering, 2010, 34(6):1159-1161 (in Chinese).
[2] Liu Shun-li, Chen Ya-sheng, Chen Lin. Model for aerial targets threat evaluation based on agent [J]. Journal of Projectiles, Rockets, Missiles and Guidance,
2010, 30(6): 212-215 (in Chinese).
[3] Han Zhao-chao, Huang Shu-cai, Wang Feng-chao. Aerial targets threat evaluation method based on interval-number & entropy-weight analysis [J]. Tactical
Missile Technology, 2010 (1): 32-35 (in Chinese).
[4] Jan T. Neural network based threat assessment for automated visual surveillance [C]//Proceedings of 2004 IEEE International Joint Conference on Neural Networks.
Piscataway, NJ: IEEE, 2004: 1309-1312.
[5] Kosko B. Fuzzy cognitive maps [J]. International Journal of Man-Machine, Studies, 1986, 24: 65-75.
[6] Ma Ji-hong, Shi Jun, Guan Hui-fen. Survey of application about theories of cognitive map [J]. Computer Technology and Development, 2008, 18(8): 126-129 (in
Chinese).
[7] Perusich K, Mcneese M D. Using fuzzy cognitive maps for knowledge management in a conflict environment [J]. IEEE Transactions on Systems, Man, and
Cybernetics. Part C. Applications and Reviews, 2006,36(6): 810-821.
[8] Lu Zhen-bang, Zhou Li-hua. A detection model for multi-stage attacks based on WOWA-FCM [J]. Journal of Sichuan University, 2008, 40(1): 122-126 (in
Chinese).
[9] Zhai Dong-sheng, Zhang Juan, Zhou Juan. A new exploration of comprehensive FCM and BP neural network [J]. Statistics and Decision, 2008 (4): 147-149 (in
Chinese).
[10] Li Shi-yong. Fuzzy control, neuro control and intelligent cybernetics [M]. Harbin: Harbin Institute of Technology Publishing House, 1998 (in Chinese).
[11] Papageoriou E, Stylios C, Greumpos P. Fuzzy cognitive map learning based on nonlinear Hebbian rule [C]//Proceedings of Australian Conference on
Artificial Intelligence’2003. Perth, Australia: LNAI, 2003: 256-268.
[12] Bu Xin-yi, Liu Xiao-xiao, Chen Feng. Quantitative representation of tacit knowledge based on dynamical fuzzy cognitive maps [J]. Journal of the China Society
for Scientific and Technical Information, 2007, 26(6): 839-844 (in Chinese).
[13] Yang Ya-ping, Hu Jun-jie. Application of fuzzy cognitive-map in collaborative medical diagnosis system [J]. Computer Engineering and Applications, 2006,
42(7): 218-220 (in Chinese).
