Research on Computing the Most Threatening Areas and Resource Allocation Techniques of Rotating Phased Array Multi-function Radar
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摘要: 旋转相控阵雷达在方位和仰角上均能电子扫描，相对于传统机扫雷达在方位和仰角上能更加灵活地调配资源。为了优化探测效果，需要对探测区域进行方位分区并进行威胁度评估。该文基于旋转相控阵雷达最威胁路径的计算提出一种区域威胁等级评估的方法；通过把每点检测概率等价为代价函数，利用泛函变分将寻找最威胁路径转变为最短路径问题；利用快速行进法求解旅行最短问题满足的程函差分方程，然后利用梯度下降法回溯最威胁路径；最后以240批目标的威胁路径计算为例，给出相应的评估结果。实践结果验证了方法的有效性和正确性。Abstract: Rotating phased array multi-function radar have electronically scanning capability both in elevation and in azimuth. It can allocate time and energy both in azimuth and elevation more flexible than the mechanical scanning radar. In order to optimize the effects of search, it is needed to divide and assess the areas. Based on the calculation of the most threatening path of the rotating phased array radar, this paper presents a novel method of regional threat level assessment; The radar problem of most threatening trajectories computation may be declined to a shortest path problem solved by calculus of variations by taking the detection probability as the price function; The shortest path computation based on Eikonal equations are solved with the fast marching method. The most threatening path are computed by backtracking the minimal path based on steepest gradient descent method. Finally, the solution of rotating phased array multi-function radar resources management is proposed based on divided areas, and the validity of the technique is checked and rationality of constructed model is verified by providing instances with 240 typical targets.
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张光义. 二维电扫三坐标雷达技术应用分析[J]. 现代雷达, 2005, 27(12): 1–7. doi: 10.3969/j.issn.1004-7859.2005.12.001ZHANG Guangyi. Analysis of 3D radar with 2D-electronically scanning antenna[J]. Modern Radar, 2005, 27(12): 1–7. doi: 10.3969/j.issn.1004-7859.2005.12.001 杨善超, 田康生, 吴长飞. 基于服务质量的相控阵雷达网目标分配方法[J]. 电子与信息学报, 2019, 41(12): 2844–2851. doi: 10.11999/JEIT181133YANG Shanchao, TIAN Kangsheng, and WU Changfei. Target assignment method for phased array radar network based on quality of service[J]. Journal of Electronics &Information Technology, 2019, 41(12): 2844–2851. doi: 10.11999/JEIT181133 LABREUCHE C, BARBARESCO F, NGUYEN D, et al. Multi-criteria aggregation for adaptive multifunction radar resource management performances evaluation[C]. 2017 18th International Radar Symposium (IRS), Prague, Czech Republic, 2017: 1–10. doi: 10.23919/IRS.2017.8008152. TIAN Tuanwei, ZHANG Tianxian, and KONG Lingjiang. Timeliness constrained task scheduling for multifunction radar network[J]. IEEE Sensors Journal, 2019, 19(2): 525–534. doi: 10.1109/JSEN.2018.2878795 SHAGHAGHI M, ADVE R S, and DING Z. Multifunction cognitive radar task scheduling using Monte Carlo tree search and policy networks[J]. IET Radar, Sonar & Navigation, 2018, 12(12): 1437–1447. doi: 10.1049/iet-rsn.2018.5276 张延风, 刘建书, 张士峰. 基于层次分析法和熵值法的目标多属性威胁评估[J]. 弹箭与制导学报, 2019, 39(2): 163–165. doi: 10.15892/j.cnki.djzdxb.2019.02.037ZHANG Yanfeng, LIU Jianshu, and ZHANG Shifeng. A multi-attribute threat assessment method based on analytical hierarchy process and entropy method[J]. Journal of Projectiles,Rockets,Missiles and Guidance, 2019, 39(2): 163–165. doi: 10.15892/j.cnki.djzdxb.2019.02.037 ZHANG Kun, KONG Weiren, LIU Peipei, et al. Assessment and sequencing of air target threat based on intuitionistic fuzzy entropy and dynamic VIKOR[J]. Journal of Systems Engineering and Electronics, 2018, 29(2): 305–310. doi: 10.21629/JSEE.2018.02.11 肖力铭, 齐海生, 屈济坤, 等. 基于直觉模糊层次分析法的空中目标威胁评估[J]. 探测与控制学报, 2019, 41(3): 108–111.XIAO Liming, QI Haisheng, QU Jikun, et al. Air target threat assessment based on intuitionistic fuzzy analytic hierarchy process[J]. Journal of Detection &Control, 2019, 41(3): 108–111. OKELLO N and THORNS G. Threat assessment using Bayesian networks[C]. The 6th International Conference of Information Fusion, Cairns, Australia, 2003: 1102–1109. doi: 10.1109/ICIF.2003.177361. BUTLER J M. Tracking and control in multi-function radar[D]. [Ph. D. dissertation], University of London, 1998. BARBARESCO F. Computation of most threatening radar trajectories areas and corridors based on fast-marching & Level Sets[C]. 2011 IEEE Symposium on Computational Intelligence for Security and Defense Applications, Paris, France, 2011: 51–58. doi: 10.1109/CISDA.2011.5945944. NORTH D O. An analysis of the factors which determine signal/noise discrimination in pulsed-carrier systems[J]. Proceedings of the IEEE, 1963, 51(7): 1016–1027. doi: 10.1109/PROC.1963.2383 BARTON D K. Radar Equations for Modern Radar[M]. Boston, Mass: Artech House, 2013: 16–17. SETHIAN J A. Fast marching methods[J]. SIAM Review, 1999, 41(2): 199–235. doi: 10.1137/s0036144598347059 CHACON A and VLADIMIRSKY A. Fast two-scale methods for Eikonal equations[J]. SIAM Journal on Scientific Computing, 2012, 34(2): A547–A578. doi: 10.1137/10080909X 兰海强, 张智, 徐涛, 等. 地震波走时场模拟的快速推进法和快速扫描法比较研究[J]. 地球物理学进展, 2012, 27(5): 1863–1870. doi: 10.6038/j.issn.1004-2903.2012.05.005LAN Haiqiang, ZHANG Zhi, XU Tao, et al. A comparative study on the fast marching and fast sweeping methods in the calculation of first-arrival traveltime field[J]. Progress in Geophysics, 2012, 27(5): 1863–1870. doi: 10.6038/j.issn.1004-2903.2012.05.005 MRUDUL K, MANDAVA R K, and VUNDAVILLI P R. An efficient path planning algorithm for biped robot using fast marching method[J]. Procedia Computer Science, 2018, 133: 116–123. doi: 10.1016/j.procs.2018.07.015 李纪三, 侯姣, 班阳阳, 等. 旋转相控阵雷达资源调度策略研究[J]. 雷达与对抗, 2018, 38(4): 1–6.LI Jisan, HOU Jiao, BAN Yangyang, et al. Study on resource scheduling strategy for rotary phased array radar[J]. Radar &ECM, 2018, 38(4): 1–6. 杨善超, 田康生, 刘仁争, 等. 基于价值优化的相控阵雷达任务调度算法[J]. 电子与信息学报, 2020, 42(2): 465–471. doi: 10.11999/JEIT190147YANG Shanchao, TIAN Kangsheng, LIU Renzheng, et al. Scheduling algorithm based on value optimization for phased array radar[J]. Journal of Electronics &Information Technology, 2020, 42(2): 465–471. doi: 10.11999/JEIT190147 叶朝谋, 丁建江, 俞志强, 等. 基于周期分区的相控阵雷达任务交叉调度研究[J]. 电子与信息学报, 2014, 36(2): 435–440. doi: 10.3724/SP.J.1146.2013.00475YE Chaomou, DING Jianjiang, YU Zhiqiang, et al. Study on task interleaving scheduling of phased array radar based on period division[J]. Journal of Electronics &Information Technology, 2014, 36(2): 435–440. doi: 10.3724/SP.J.1146.2013.00475 LIU Dai, ZHAO Yongbo, CAI Xingyu, et al. Adaptive scheduling algorithm based on CPI and impact of tasks for multifunction radar[J]. IEEE Sensors Journal, 2019, 19(23): 11205–11212. doi: 10.1109/JSEN.2019.2936659 -
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