基于Agent理论的飞机敏感性评估方法
收稿日期: 2013-04-01
修回日期: 2013-09-28
网络出版日期: 2013-10-21
基金资助
国家自然科学基金（11102159）
Assessment Method of Aircraft Susceptibility Based on Agent Theory
Received date: 2013-04-01
Revised date: 2013-09-28
Online published: 2013-10-21
Supported by
National Natural Science Foundation of China (11102159)
在以信息战为核心的现代战争中，各机种、多平台之间的信息交互成为影响战争结果的关键因素。因此进行飞机敏感性设计时，应当置于信息对抗的环境中并考虑信息交互过程。本文阐述了网络中心战的理论，建立了基于Agent理论的战场模型以及飞机对抗模型，通过对Agent对抗过程中的3个阶段（探测阶段、信息交互阶段、作战阶段）进行建模仿真，研究了预警机探测能力、飞机雷达散射截面（RCS）、信息传输时延和红外电子对抗能力等因素对飞机敏感性的影响，得到了雷达特征参数、飞机RCS与探测概率之间的关系，传输时延与先敌发射概率之间的关系，以及红外干扰弹的最优发射区间，为飞机的敏感性设计提供了一定的依据。
石帅 , 宋笔锋 , 裴扬 , 程涛 . 基于Agent理论的飞机敏感性评估方法[J]. 航空学报, 2014 , 35(2) : 444 -453 . DOI: 10.7527/S1000-6893.2013.0413
In modern intelligence-based warfare, intelligence interaction between various kinds of aircraft and multi-platforms is a key factor that influences the outcome of a battle. Therefore, when an aircraft is being designed, intelligence interaction and intelligence antagonism should be taken into consideration. In this paper, the network centric warfare theory is introduced, and an aircraft antagonistic model and a warfare model based on the agent theory are built. The three stages in the antagonism process,including the detection stage, the intelligence interaction stage and the combat stage, are simulated. In addition, the paper also studies the effect of aircraft susceptibility caused by the following parameters: the detection ability of the warning plane, the aircraft's RCS, the time delay during intelligence interaction, the infrared electronic countermeasure ability, etc. The relationship between the radar typical parameters, RCS and the detection probability, the relationship between the time delay and the first shot probability, and the best launch interval of the infrared decoys are obtained. This study can provide useful reference for aircraft.
Key words： agent theory; aircraft susceptibility; RCS; time delay; flare
[1] Ball R E. The fundamentals of aircraft combat survivability analysis and design: AIAA education series[M]. 2nd ed. VG: AIAA, 2003: 1.
[2] Gonzales D, Hollywood J, Kingston G, et al. Network-centric operations case study air-to-air combat with and without Link 16, ADA437368[R]. Santa Monica, CA: RAND Corporation, 2005.
[3] US Department of Defense. Modeling and simulation master plan[R]. Washington D.C.: US Department of Defense, 1995.
[4] Iachinski A I. Artificial war multi agent based simulation of combat[M]. Zhang Z X, Gao C R, Guo F L, translated. Beijing: Publishing House of Electronics Industry, 2010: 16-19.(in Chinese) Iachinski A I. 人工战争: 基于多Agent的作战仿真[M]. 张志祥, 高春蓉, 郭福亮, 译. 北京:电子工业出版社, 2010: 16-19.
[5] Mahapatra S. A hierarchical approach to modeling agent-based systems in Simulink, AIAA-2012-4713[R]. Reston: AIAA, 2012.
[6] Coradeschi S, Karlsson L, Törne A. Intelligent agents for aircraft combat simulation[C]//Proceedings of the 6th Conference on Computer Generated Forces and Behavioral Representation, 1996: 3-4.
[7] Grecu D, Gonsalves P. Agent-based simulation environment for UCAV mission planning and execution, AIAA-2000-4481[R]. Reston: AIAA, 2000.
[8] Li J, Li J, Zhong Z N, et al. Space-air resource multi-phase cooperation task planning approach based on heterogeneous MAS model[J]. Acta Aeronautics et Astronautica Sinica, 2013, 34(7): 1682-1697.(in Chinese) 李军, 李军, 钟志农, 等. 异构MAS结构下的空天资源多阶段协同任务规划方法[J]. 航空学报, 2013, 34(7): 1682-1697
[9] Marshall A W. Measuring the effects of network-centric warfare, ADA401399[R]. Virginia: Booz Allen & Hamilton Inc., 1999.
[10] Hewit C. Viewing control structures as patterns of passing messages[J]. Artificial Intelligence, 1977, 8(3):323-364.
[11] Gandhi P P, Kassam S A. Analysis of CFAR processors in nonhomogeneous background[J]. IEEE Transactions on Aerospace and Electronic Systems, 1988, 14(4): 431.
[12] Shlapak D A, Orletsky D T, Wilson B A. Dire strait?Military aspects of the China-Taiwan confrontation and options for U.S. policy, MR-1217-SRF[R]. Santa Monica, CA: RAND Corporation, 2000.
[13] Mu F L, Luo P C, Ma Y Z. Study on the effectiveness evaluation method of formation beyond visual range air combat[J]. Fire Control and Command Control, 2006(12): 91-93. (in Chinese) 穆富岭, 罗鹏程, 马元正. 编队超视距空战效能评估方法[J]. 火力与指挥控制, 2006(12): 91-93.
[14] Poollock D H. The infrared & electro-optical systems handbook countermeasure systems[M]. Bellingham, Washington: SPIE Optical Engineering Press, 1999: 292-293.
/
| 〈 |
|
〉 |
CJA