基于证据融合的雷达反隐身性能评估方法

师俊朋; 胡国平; 王馨

doi:10.13700/j.bh.1001-5965.2014.0388

基于证据融合的雷达反隐身性能评估方法

doi: 10.13700/j.bh.1001-5965.2014.0388

空军工程大学防空反导学院, 西安 710051

详细信息

作者简介:
师俊朋(1988—),男,河南许昌人,博士研究生,1065698473@qq.com

通讯作者:
胡国平(1964—),男,陕西西安人,教授,博士生导师,15667081720@163.com,主要研究方向为雷达信号与信息处理.

中图分类号: TN957
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- 被引次数: 0
出版历程
- 收稿日期: 2014-06-30
- 网络出版日期: 2015-06-20

Evaluation method for radar anti-stealth performance based on evidence fusion

Air and Missile Defense College, Air Force Engineering University, Xi'an 710051, China

摘要

摘要: 针对雷达反隐身性能评估过程复杂、算法不完善等现象,提出了一种基于改进证据融合算法的雷达反隐身性能评估方法.针对证据源主观性强、关联性差等现象,依据熵理论、欧式距离等客观分析得到了可信度因子与熵权值、受支持系数间的变化关系,实时修正了可信度分配函数.并结合雷达反隐身分层次性能评估指标体系,建立了基于效用区间的雷达反隐身性能优劣比较方法,得出了客观、准确的评估结果.算例分析和仿真表明,与一般融合算法相比,改进的证据融合算法系统评估能力更强、鲁棒性更好.
- 雷达反隐身 /
- 证据理论 /
- 可信度因子 /
- 分层次指标体系 /
- 效用区间
Abstract: Aiming at the phenomenon of complicated process and imperfect algorithm in the evaluation of radar anti-stealth performance, a new method for the evaluation based on improved evidence theory was presented. Firstly, to overcome the shortcomings of strong subjectivity and weak correlation, the credibility assignment function was corrected in real time according to the relationship among credibility factor, entropy weight and supported coefficient, which is based on the objective analysis of entropy theory and Euclidean distance. Secondly, combined with the multi-hierarchy indexes of radar anti-stealth performance, the rank order of whole radars anti-stealth performance on utility interval was attained. At last, an objective and accurate assessment results were obtained. The analysis of theory and simulation proved that, in contrast to other fusion algorithm, the improved fusion algorithm had better ability of assessment and better robustness.
- radar anti-stealth /
- evidence theory /
- credibility factor /
- multi-hierarchy indexes /
- utility interval

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参考文献(15)

[1]	曹丽梅, 王瑛.雷达隐身与反隐身技术发展综述[J].现代导航, 2012, 6(3):215-218. Cao L M, Wang Y.Overview on development of radar stealth and anti-stealth technologies of radar[J].Modern Navigation, 2012, 6(3):215-218(in Chinese).
[2]	唐政, 孙超, 刘宗伟, 等.基于灰色层次分析法的水声对抗系统性能评估[J].兵工学报, 2012, 33(4):432-436. Tang Z, Sun C, Liu Z W, et al.Research on efficiency evaluation for underwater acoustic countermeasure system based on grey hierarchy analysis[J].Aata Armamentarii, 2012, 33(4):432-436(in Chinese).
[3]	齐照辉, 刘雪梅, 梁伟, 等.基于分层赋权的导弹防御性能模糊评估方法[J].系统工程理论与实践, 2011, 31(9):1811-1815. Qi Z H, Liu X M, Liang W, et al.Fuzzy evaluation approach to missile defense effectiveness based on layered weight coefficients[J].Systems Engineering-Theory & Practice, 2011, 31(9):1811-1815(in Chinese).
[4]	Gong S F, Long W J, Huang H, et al.Polyphase orthogonal sequences design for opportunistic array radar via HGA[J].Journal of Systems Engineering and Electronics, 2013, 24(1):60-67.
[5]	吴瑕, 周焰, 杨龙坡, 等.基于聚类分析与几何的目标特征敏感性评估算法[J].控制与决策, 2012, 27(6):914-917. Wu X, Zhou Y, Yang L P, et al.Target feature sensitivity evaluation method based on clustering analysis and geometry[J].Control and Decision, 2012, 27(6):914-917(in Chinese).
[6]	Lei Y G, He Z J, Zi Y Y.A new approach to intelligent fault diagnosis of rotating machinery[J].Expert Systems with Applications, 2008, 35(4):1593-1600.
[7]	姜志敏, 刘婕.基于探测范围的雷达网反隐身能力评估方法[J].空军雷达学院学报, 2010, 24(2):115-118. Jiang Z M, Liu J.Method for anti-stealth capability evaluation of radar net based on detection range[J].Journal of Air Force Radar Academy, 2010, 24(2):115-118(in Chinese).
[8]	陈永光, 李修和, 沈阳.组网雷达作战能力分析与评估[M].北京:国防工业出版社, 2006:53-56. Chen Y G, Li X H, Shen Y.Radar network analysis and evaluation of operational capability[M].Beijing:National Defense Industry Press, 2006:53-56(in Chinese).
[9]	李金梁, 李永祯, 王雪松.米波极化雷达的反隐身研究[J].雷达科学与技术, 2005, 3(6):321-326. Li J L, Li Y Z, Wang X S.Study on anti-stealth with meter-band polari metric radar[J].Radar Science and Technology, 2005, 3(6):321-326(in Chinese).
[10]	美林 I·斯科尼克.雷达系统导论[M].北京:电子工业出版社, 2010:42-55. Merrill I S.Introduction to radar systems[M].Beijing:Publishing House of Electronics Industry, 2010:42-55(in Chinese).
[11]	孙锐.基于D-S证据理论的信息融合及在可靠性数据处理中的应用研究[D].成都:电子科技大学, 2011. Sun R.Research on D-S evidence theory based information fusion and its application in reliability data processing[D].Chengdu:University of Electronic Science and Technology of China, 2011(in Chinese).
[12]	李巍华, 张盛刚.基于改进证据理论及多神经网络融合的故障分类[J].机械工程学报, 2010, 46(9):93-99. Li W H, Zhang S G.Fault classification based on improved evidence theory and multiple neural network fusion[J].Journal of Mechanical Engineering, 2010, 46(9):93-99(in Chinese).
[13]	孟光磊, 龚光红.证据源权重的计算及其在证据融合中的应用[J].北京航空航天大学学报, 2010, 36(11):1365-1368. Meng G L, Gong G H.Weight coefficients calculation for evidence sources and its application in evidences fusion[J].Journal of Beijing University of Aeronautics and Astronautics, 2010, 36(11):1365-1368(in Chinese).
[14]	曹一家, 姚欢, 黄小庆, 等.基于D-S证据理论的变电站通信系统信息安全评估[J].电力自动化设备, 2011, 31(6):1-5. Cao Y J, Yao H, Huang X Q, et al.Security evaluation of substation communication system based on D-S theory[J].Electric Power Automation Equipment, 2011, 31(6):1-5(in Chinese).
[15]	潘超.雷达抗干扰性能评估准则与方法研究[D].成都:电子科技大学, 2006. Pan C.Principles and method of radar ECCM effectiveness evaluation[D].Chengdu:University of Electronic Science and Technology of China, 2006(in Chinese).