电子与控制

联合截获威胁下的雷达射频隐身目标搜索算法

  • 李寰宇 ,
  • 查宇飞 ,
  • 李浩 ,
  • 杨源 ,
  • 杨丽薇
展开
  • 1. 空军工程大学 航空航天工程学院, 西安 710038;
    2. 空军工程大学 空管领航学院, 西安 710051;
    3. 空军工程大学 综合电子信息系统与电子对抗技术研究中心, 西安 710051;
    4. 空军工程大学 科研部, 西安 710051
李寰宇 男, 博士, 讲师。主要研究方向: 电子战、模式识别、机器学习。 Tel: 029-84789518 E-mail: lihuanyu1984@163.com;查宇飞 男, 博士, 副教授。主要研究方向: 机器学习、模式识别。 Tel: 029-84789518 E-mail: kgd_bsh@163.com;李浩 男, 博士, 讲师。主要研究方向: 智能计算。 Tel: 029-84789518 E-mail: snk.poison@163.com;杨源 男, 博士, 副教授。主要研究方向: 信息与通信工程。 Tel: 029-84789518 E-mail: yangyuankgd@126.com;杨丽薇 女, 博士, 讲师。主要研究方向: 电子与通信工程。 Tel: 029-84789518 E-mail: yangliweiss@163.com

收稿日期: 2014-07-10

  修回日期: 2014-09-23

  网络出版日期: 2015-01-09

基金资助

国家自然科学基金 (61202339); 航空科学基金(20131996013); 中国博士后科学基金(2013T60926)

Radar search algorithm based on RF stealth in the case of joint intercepted threats

  • LI Huanyu ,
  • ZHA Yufei ,
  • LI Hao ,
  • YANG Yuan ,
  • YANG Liwei
Expand
  • 1. College of Aerospace Engineering, Air Force Engineering University, Xi'an 710038, China;
    2. College of ATC Navigation, Air Force Engineering University, Xi'an 710051, China;
    3. Research Center for Integrated Electronic & Information System and Electronic Countermeasure Technology, Air Force Engineering University, Xi'an 710051, China;
    4. Science Research, Air Force Engineering University, Xi'an 710051, China

Received date: 2014-07-10

  Revised date: 2014-09-23

  Online published: 2015-01-09

Supported by

National Natural Science Foundation of China (61202339); Aeronautical Science Foundation of China (20131996013); China Postdoctoral Science Foundation (2013T60926)

摘要

针对基于射频(RF)隐身需求的机载雷达目标搜索问题进行了研究。通过分析实际作战中射频辐射面临的截获威胁,提出了一种基于联合截获威胁的射频隐身性能表征方法,并给出了具体的值估算方法;对机载雷达搜索任务中辐射参数的优化问题进行了建模,并采用优化算法对目标函数进行求解。通过分析典型情景下解集的分布特点,给出了从最优解集中选取最终解的方法。结果表明,提出的射频隐身性能表征方法能更好地反映截获实现过程的多域需求,提出的雷达搜索方法能够在保证探测性能的同时,提高射频隐身性能和搜索速度,能够为相控阵雷达搜索任务中参数的优化控制提供方法和依据。

本文引用格式

李寰宇 , 查宇飞 , 李浩 , 杨源 , 杨丽薇 . 联合截获威胁下的雷达射频隐身目标搜索算法[J]. 航空学报, 2015 , 36(6) : 1953 -1963 . DOI: 10.7527/S1000-6893.2014.0363

Abstract

The radar target search problems based on radio frequency (RF) stealth is researched in the paper. By analyzing the intercept threats of actual battlefield faced by radio-frequency radiation, a new characterization method based on joint intercepted threats of RF stealth performance is proposed, and the value estimation methods is also given; A model of parameter optimization problem for airborne radar search parameters is built, and using optimization algorithms to solve the objective functions. By analyzing the distribution characterics of the solution set of typical scenario, the method of selecting final solution is given from optimal solution set. The result shows that, the RF stealth characterization method proposed is better to reflect the multi-domain requirement of intercepted, the radar search method can improve the RF stealth performance and the search speed while assuring the detection performance, and provide methods and basis for parameter optimization and control in phased array radar search tasks.

参考文献

[1] Lynch D, Jr. Introduction to RF stealth[M]. North Carolina: Science Technology Publishing Inc., 2004: 54-75.
[2] Haftbaradaran P, Kamarei M, Mofrad R F. The optimal search for multifunction phased array radar[C]//International Conference on Antennas & Propagation. Piscataway, NJ: IEEE Press, 2009: 609-612.
[3] Fan L N, Wang J K, Wang B. Radar resource management in multifunction radar[C]//International Conference on Computer Design and Applications. Piscataway, NJ: IEEE Press, 2010: 580-583.
[4] Zhang Z K, Zhou J J, Wang F. Novel algorithm of power control based on radio frequency stealth[J]. Systems Engineering and Electronics, 2012, 34(11): 2244-2248 (in Chinese). 张贞凯, 周建江, 汪飞. 基于射频隐身的相控阵雷达功率控制算法[J]. 系统工程与电子技术, 2012, 34(11): 2244-2248.
[5] Zhang Z K, Zhou J J, Wang F, et al. Research on optimal search performance of airborne phased[J]. Journal of Astronautics, 2011, 32(9): 2023-2027 (in Chinese). 张贞凯, 周建江, 汪飞,等. 机载相控阵雷达射频隐身时最优搜索性能研究[J]. 宇航学报, 2011, 32(9): 2023-2027.
[6] Liao W W, Cheng T, He Z S. A target tracking algorithm for RF stealth performance optimization of MIMO radar[J]. Acta Aeronautica et Astronautica Sinica, 2014, 35(4): 1134-1141 (in Chinese). 廖雯雯, 程婷, 何子述. MIMO雷达射频隐身性能优化的目标跟踪算法[J]. 航空学报, 2014, 35(4): 1134-1141.
[7] Feng B Y, Wang Y, An H, et al. Computational model of radio frequency risk on stealth performance of airborne radar[J]. Systems Engineering and Electronics, 2013, 35(1): 73-77 (in Chinese). 冯博宇, 王瑛, 安航, 等. 机载雷达射频隐身性能风险的计算模型[J]. 系统工程与电子技术, 2013, 35(1): 73-77.
[8] Schleher D C. LPI radar: Fact or fiction[J]. IEEE Aerospace and Electronic Systems Magazine, 2006, 21 (5): 3-6.
[9] Li H Y, Bai P, Wang Q Z. Influence of antenna beam on radio frequency stealth[J]. Modern Defence Technology, 2012, 40(4): 128-133 (in Chinese). 李寰宇, 柏鹏, 王谦喆. 天线波束对飞机射频隐身性能的影响分析[J]. 现代防御技术, 2012, 40(4): 128-133.
[10] Self A G, Smith B G. Intercept time and its prediction[J]. IEE Proceedings F: Communications, Radar and Signal Processing, 1985, 132 (4): 215-220.
[11] Alexopoulos A. Closed-form solutions for number of beams in static and rotating phased array radars[J]. Electronics Letters, 2006, 42(14): 822-824.
[12] Swerling P. Probability of detection for fluctuating targets[J]. IRE Transactions on Information Theory, 1960, 6(4): 269-308.
[13] DiFranco J V, Rubin W L. Radar detection[M]. Norwood: Artech House, 1980: 158-168.
[14] Schaffer J D. Multiple objective optimization with vector evaluated genetic algorithms[D]. Nashville: Vanderbilt University, 1984.
[15] Coello C A, Pulido G T, Lechunga M S. Handing multiple objectives with particle swarm optimization[J]. IEEE Transactions on Evolutionary Computation, 2004, 8(3): 256-279.
[16] Colorni A, Dorigo M, Maniezzo V. An investigation of some properties of an ant algorithm[C]//Proceeding of Parallel Problem Solving from Nature. Brussels : Elsevier, 1992: 509-520
[17] Ye Y M,Yin J W, Feng Z L. Wolf-Pack algorithm for business process model syntactic and semantic structure verification in the workflow management environment[C]//Asia-Pacific Services Computing Conference. Piscataway, NJ: IEEE Press, 2010: 694-699.
[18] Coello C A, Cortes N C. Solving multi-objective optimization problems using an artificial immune system[J]. Genetic Programming and Evolvable Machines, 2005, 6 (2): 163-190.
[19] Wu H S, Zhang F M, Wolf Pack algorithm for unconstrained global optimization[J]. Mathematical Problems in Engineering, 2014, DOI: 10.1155/2014/465082
[20] Deb K, Agrawal S, Pratap A. A fast and elitist multi-objective genetic algorithm: NSGA-II[J]. IEEE Transactions on Evolutionary Computation, 2004, 8(3): 256-279.

文章导航

/