改进布谷鸟算法在协同干扰资源分配中的应用
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摘要
针对敌方雷达网的多干扰机协同干扰资源分配问题,提出了一种基于二维整数编码的改进布谷鸟(ICS)算法。首先,根据不同干扰样式在不同恒虚警检测器中的干扰效果差异,从压制概率公式出发,构建目标函数;然后,根据分配原则建立干扰资源分配模型;最后,利用ICS算法对模型寻优求解,并给出具体求解步骤。仿真结果表明:ICS算法收敛速度快,全局寻优能力强,能很好地解决雷达干扰资源协同优化分配问题。
In order to solve the problem of optimization assignment for cooperative jamming resources against radar network,an improved cuckoo search(ICS) algorithm is proposed. Firstly, to get the best jamming effect by using different types of jamming in different constant false alarm detectors,an objective function for allocating radar jamming resources is built,which is based on the calculation of the suppression probability formula.Then, the optimal distribution model of radar jamming resource is built according to the principle of distribution. Finally, ICS algorithm is applied to solve the model and the calculation steps are presented in detail. The simulation results show that ICS algorithm has satisfying global optimization performance and the convergence quality, which is applicable for the optimal distribution of radar jamming resource.
In order to solve the problem of optimization assignment for cooperative jamming resources against radar network,an improved cuckoo search(ICS) algorithm is proposed. Firstly, to get the best jamming effect by using different types of jamming in different constant false alarm detectors,an objective function for allocating radar jamming resources is built,which is based on the calculation of the suppression probability formula.Then, the optimal distribution model of radar jamming resource is built according to the principle of distribution. Finally, ICS algorithm is applied to solve the model and the calculation steps are presented in detail. The simulation results show that ICS algorithm has satisfying global optimization performance and the convergence quality, which is applicable for the optimal distribution of radar jamming resource.
引文
[1] 赵珊珊, 张林让, 李强,等.分布式多站雷达转发式欺骗干扰研究[J]. 电子与信息学报, 2017, 39(1): 138-143.ZHAO Shanshan,ZHANG Linrang, LI Qiang, et al. Research on repeater jamming against distributed multiple-radar system[J]. Journal of Electronics & Information Technology, 2017, 39(1): 138-143.
[2] RAO B, XIAO S P, WNAG X S, et al. Maximum likelihood approach to the estimation and discrimination of exoatmospheric active phantom tracks using motion features[J]. IEEE Transactions on Aerospace and Electronic Systems, 2012, 48(1): 794-819.
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[5] 李东生, 高杨, 雍爱霞. 基于改进离散布谷鸟算法的干扰资源分配研究[J]. 电子与信息学报, 2016, 38(4): 899-905.LI Dongsheng, GAO Yang, YONG Aixia. Jamming resource allocation via improved discrete cuckoo search algorithm[J]. Journal of Electronics & Information Technology, 2016, 38(4): 899-905.
[6] 沈阳, 陈永光, 李修和. 基于 0-1规划的雷达干扰资源优化分配研究[J]. 兵工学报, 2007, 28(5): 528-532. SHEN Yang, CHEN Yongguang, LI Xiuhe. Research on optimal distribution of radar jamming resource based on zero-one programming[J]. Acta Armamentarii, 2007, 28(5): 528-532.
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[8] 任松,司长哲.雷达干扰机分配的模糊多属性动态规划模型[J].系统工程与电子技术,2008, 30(10): 1909-1913.REN Song, SI Changzhe. Fuzzy multi-attribute dynamic programming model for radar's disturbing machine allocation[J]. Systems Engineering and Electronics, 2008, 30(10): 1909-1913.
[9] 张养瑞,李云杰,高梅国.协同干扰资源优化分配模型及算法[J]. 系统工程与电子技术, 2014, 36(11): 1744-1749.ZHANG Yangrui, LI Yunjie, GAO Meiguo. Optimal assignment model and solution of cooperative jamming resources[J]. Systems Engineering and Electronics, 2014,36(11): 1744-1749.
[10] XUE Y, ZHUANG Y, NI T Q, et al. Self-adaptive learning based discrete differential evolution algorithm for solving CJWTA problem[J]. Journal of Systems Engineering and Electronics, 2014, 25(1): 59-68.
[11] YANG X S, DEB S. Cuckoo search via levy flights[C]// 2009 World Congress on Nature & Biological Inspired Computing. Coimbatore: IEEE Press, 2009: 210-214.
[12] CIVCIOGLU P, BESDOK E. A conceptual comparison of the Cuckoo-search, particle swarm optimization, differential evolution and artificial bee colony algorithms[J]. Artificial Intelligence Review, 2011, 39(4): 315-346.
[13] 何友,关键,孟祥伟,等. 雷达目标检测与恒虚警处理[M]. 北京:清华大学出版社, 2011.HE You, GUAN Jian,MENG Xiangwei, et al. Radar target detection and CFAR processing[M]. Beijing: Tsinghua University Press, 2011.
[14] 柳向,李东生, 刘庆林. 基于OS-CFAR的LFM脉压雷达多假目标干扰分析[J]. 系统工程与电子技术, 2017, 39(7): 1486-1492.LIU Xiang,LI Dongsheng,LIU Qinglin. Jamming technique of multiple false targets against linear frequency modulated pulse-compression radar based on OS-CFAR[J]. Systems Engineering and Electronics, 2017, 39(7): 1486-1492.
[15] 张养瑞, 高梅国, 罗皓月,等. 基于检测概率的雷达网协同干扰效果评估方法[J]. 系统工程与电子技术, 2015, 37(8): 1778-1786.ZHANG Yangrui, GAO Meiguo, LUO Haoyue, et al. Evalution method of cooperative jamming effect on radar net based on detection probability[J]. Systems Engineering and Electronics, 2015, 37(8): 1778-1786.
[16] 刘忠. 基于DRFM的线性调频脉冲压缩雷达干扰新技术[D]. 长沙: 国防科技大学, 2006.LIU Zhong. Jamming technique for countering LFM pulse compression radar based on digital radio frequency memory[D]. Changsha: National University of Defense Technology, 2006.
[17] 唐文龙, 张剑云, 王冰川,等. 干扰样式选择方法研究[J]. 现代雷达, 2017,39(1): 72-76.TANG Wenlong, ZHANG Jianwen, WANG Bingchuan, et al. A study on jamming style selecting[J]. Modern Radar, 2017, 39(1): 72-76.
[2] RAO B, XIAO S P, WNAG X S, et al. Maximum likelihood approach to the estimation and discrimination of exoatmospheric active phantom tracks using motion features[J]. IEEE Transactions on Aerospace and Electronic Systems, 2012, 48(1): 794-819.
[3] ZHAO S S,ZHANG L R, ZHOU Y, et al. Discrimination of active false targets in multistatic radar using spatial scattering properties[J]. IET Radar, Sonar & Navigation, 2016, 10(5): 816-826.
[4] 刘以安, 倪天权, 张秀辉,等. 模拟退火算法在雷达干扰资源优化分配中的应用[J]. 系统工程与电子技术, 2009, 31(8): 1914-1917.LIU Yian,NI Tianquan, ZHANG Xiuhui, et al. Application of simulated annealing algorithm in optimizing allocation of radar jamming resources[J]. Systems Engineering and Electronics, 2009, 31(8): 1914-1917.
[5] 李东生, 高杨, 雍爱霞. 基于改进离散布谷鸟算法的干扰资源分配研究[J]. 电子与信息学报, 2016, 38(4): 899-905.LI Dongsheng, GAO Yang, YONG Aixia. Jamming resource allocation via improved discrete cuckoo search algorithm[J]. Journal of Electronics & Information Technology, 2016, 38(4): 899-905.
[6] 沈阳, 陈永光, 李修和. 基于 0-1规划的雷达干扰资源优化分配研究[J]. 兵工学报, 2007, 28(5): 528-532. SHEN Yang, CHEN Yongguang, LI Xiuhe. Research on optimal distribution of radar jamming resource based on zero-one programming[J]. Acta Armamentarii, 2007, 28(5): 528-532.
[7] 吕永胜, 王树宗, 王向伟, 等. 基于贴近度的雷达干扰资源分配策略研究[J]. 系统工程与电子技术, 2005, 27(11): 1893-1894.Lü Yongsheng, WANG Shuzong, WANG Xiangwei, et al. Study on the allocation tactics for radar jamming resources based on close degree[J]. Systems Engineering and Electronics, 2005, 27(11): 1893-1894.
[8] 任松,司长哲.雷达干扰机分配的模糊多属性动态规划模型[J].系统工程与电子技术,2008, 30(10): 1909-1913.REN Song, SI Changzhe. Fuzzy multi-attribute dynamic programming model for radar's disturbing machine allocation[J]. Systems Engineering and Electronics, 2008, 30(10): 1909-1913.
[9] 张养瑞,李云杰,高梅国.协同干扰资源优化分配模型及算法[J]. 系统工程与电子技术, 2014, 36(11): 1744-1749.ZHANG Yangrui, LI Yunjie, GAO Meiguo. Optimal assignment model and solution of cooperative jamming resources[J]. Systems Engineering and Electronics, 2014,36(11): 1744-1749.
[10] XUE Y, ZHUANG Y, NI T Q, et al. Self-adaptive learning based discrete differential evolution algorithm for solving CJWTA problem[J]. Journal of Systems Engineering and Electronics, 2014, 25(1): 59-68.
[11] YANG X S, DEB S. Cuckoo search via levy flights[C]// 2009 World Congress on Nature & Biological Inspired Computing. Coimbatore: IEEE Press, 2009: 210-214.
[12] CIVCIOGLU P, BESDOK E. A conceptual comparison of the Cuckoo-search, particle swarm optimization, differential evolution and artificial bee colony algorithms[J]. Artificial Intelligence Review, 2011, 39(4): 315-346.
[13] 何友,关键,孟祥伟,等. 雷达目标检测与恒虚警处理[M]. 北京:清华大学出版社, 2011.HE You, GUAN Jian,MENG Xiangwei, et al. Radar target detection and CFAR processing[M]. Beijing: Tsinghua University Press, 2011.
[14] 柳向,李东生, 刘庆林. 基于OS-CFAR的LFM脉压雷达多假目标干扰分析[J]. 系统工程与电子技术, 2017, 39(7): 1486-1492.LIU Xiang,LI Dongsheng,LIU Qinglin. Jamming technique of multiple false targets against linear frequency modulated pulse-compression radar based on OS-CFAR[J]. Systems Engineering and Electronics, 2017, 39(7): 1486-1492.
[15] 张养瑞, 高梅国, 罗皓月,等. 基于检测概率的雷达网协同干扰效果评估方法[J]. 系统工程与电子技术, 2015, 37(8): 1778-1786.ZHANG Yangrui, GAO Meiguo, LUO Haoyue, et al. Evalution method of cooperative jamming effect on radar net based on detection probability[J]. Systems Engineering and Electronics, 2015, 37(8): 1778-1786.
[16] 刘忠. 基于DRFM的线性调频脉冲压缩雷达干扰新技术[D]. 长沙: 国防科技大学, 2006.LIU Zhong. Jamming technique for countering LFM pulse compression radar based on digital radio frequency memory[D]. Changsha: National University of Defense Technology, 2006.
[17] 唐文龙, 张剑云, 王冰川,等. 干扰样式选择方法研究[J]. 现代雷达, 2017,39(1): 72-76.TANG Wenlong, ZHANG Jianwen, WANG Bingchuan, et al. A study on jamming style selecting[J]. Modern Radar, 2017, 39(1): 72-76.