Probability Estimation and Prediction Methods of Escape Area for Underwater Lost Targets
-
摘要: 在水下高速机动平台面临真假目标共存的复杂水声对抗环境时, 若攻击目标选择错误, 可能导致真实高价值目标逃逸。传统的无针对性再搜索策略效率低下, 需要深入分析高价值目标的对抗策略, 综合考虑其机动能力和战术选择, 制定针对性的反对抗与再搜索策略。文中基于高价值目标对抗策略分析构建了目标逃逸区域模型, 提出一种水下丢失目标逃逸区域概率评估方法, 用于预测对抗区域内目标的逃逸概率。仿真结果表明, 该方法有助于提升目标再搜索的成功率, 缩短水下高速机动平台的搜索时间, 从而显著提高整体搜索效率。Abstract: In the complex underwater acoustic countermeasures where underwater high-speed maneuvering platforms face the coexistence of true and false targets, incorrect target selection may lead to the escape of true high-value targets. Traditional non-targeted research strategies are inefficient, necessitating an in-depth analysis of high-value target countermeasure strategies, comprehensive consideration of their maneuverability and tactical choices, and the formulation of targeted counter-countermeasure and research strategies. Based on the analysis of high-value target countermeasure strategies, a target escape area model was constructed, and a probability estimation method was proposed for lost target escape areas to predict the escape probability of targets within the countermeasure area. The simulation results indicate that this method helps improve the success rate of target re-search and reduce the search time of underwater high-speed maneuvering platforms, thus enhancing overall search efficiency.
-
图 1 丢失目标左转左舷观测几何示意图
Figure 1. Geometric schematic diagram of left-turn port observation with lost target
图 2 丢失目标左转右舷观测几何示意图
Figure 2. Geometric schematic diagram of left-turn starboard observation with lost target
图 3 丢失目标右转左舷观测几何示意图
Figure 3. Geometric schematic diagram of right-turn port observation with lost target
图 4 丢失目标右转右舷观测几何示意图
Figure 4. Geometric schematic diagram of right-turn starboard observation with lost target
图 5 目标转向角概率密度曲线(无约束)
Figure 5. Probability density curve of target steering angle (unconstrained)
图 6 目标转向角概率密度曲线(有约束)
Figure 6. Probability density curve of target steering angle (with constraints)
图 7 丢失目标逃逸距离概率密度曲线(无约束)
Figure 7. Probability density curve of escape distance for lost targets (unconstrained)
图 8 丢失目标逃逸距离概率密度曲线(有约束)
Figure 8. Probability density curve of escape distance for lost targets (with constraints)
图 9 丢失目标逃逸位置概率密度预测分布云图
Figure 9. Contour of probability density prediction distribution for lost target escape positions
图 11 机动能力限制下丢失目标逃逸位置概率密度预测分布云图
Figure 11. Contour probability density prediction distribution for lost target escape positions under maneuverability constraints
-
[1] 唐波, 孟荻, 范文涛. 国外水声对抗器材发展现状与启示——潜用器材[J]. 水下无人系统学报, 2022, 30(1): 15-22.Tang B, Meng D, Fan W T. Current situation and enlightenment of foreign underwater acoustic countermeasure equipment for submarine[J]. Journal of Unmanned Undersea Systems, 2022, 30(1): 15-22. [2] 沈沁轩. 潜艇水声对抗技术的现状与发展[J]. 电子技术与软件工程, 2019(9): 88. [3] 何心怡, 卢军, 张思宇, 等. 国外鱼雷现状与启示[J]. 数字海洋与水下攻防, 2020, 3(2): 87-93. doi: 10.19838/j.issn.2096-5753.2020.02.001He X Y, Lu J, Zhang S Y, et al. Research status and enlightenment of foreign torpedoes[J]. Digital Ocean & Underwater Warfare, 2020, 3(2): 87-93. doi: 10.19838/j.issn.2096-5753.2020.02.001 [4] 侯文姝. 人机协同的潜艇智能防御鱼雷水声对抗模型体系[J]. 舰船电子工程, 2022, 42(1): 1-4, 88. doi: 10.3969/j.issn.1672-9730.2022.01.001Hou W S. Underwater acoustic warfare model system of intelligent submarine torpedo defense based on man-machine coordination[J]. Ship Electronic Engineering, 2022, 42(1): 1-4, 88. doi: 10.3969/j.issn.1672-9730.2022.01.001 [5] 夏奎, 郑援, 胡先锋. 潜艇水声对抗方案评估方法分析[J]. 鱼雷技术, 2010, 18(1): 76-80. doi: 10.3969/j.issn.1673-1948.2010.01.016Xia K, Zheng Y, Hu X F. An evaluation method of submarine acoustic countermeasure schemes[J]. Journal of Unmanned Undersea Systems, 2010, 18(1): 76-80. doi: 10.3969/j.issn.1673-1948.2010.01.016 [6] 杨静, 陆铭华, 郭力强, 等. 不确定环境下潜艇综合防御鱼雷的作战决策分析与优化方法[J]. 兵工学报, 2024, 45(2): 564-573.Yang J, Lu M H, Guo L Q, et al. Operational decision analysis and optimization method of submarine integrated defense against torpedo in uncertain environment[J]. Acta Armamentarii, 2024, 45(2): 564-573. [7] 李本江, 李贵彬, 魏敬广. 潜艇使用噪声干扰器规避鱼雷攻击最优航向仿真研究[J]. 鱼雷技术, 2009, 17(6): 75-78.Li B J, Li G B, Wei J G. Simulation of submarine’s optimal course after using noise jammer to elude acoustic homing torpedo[J]. Torpedo Technology, 2009, 17(6): 75-78. [8] 丁文强, 丁浩, 赵志允. 潜艇强机动变深规避鱼雷攻击仿真研究[J]. 现代防御技术, 2024, 52(1): 124-129.Ding W Q, Ding H, Zhao Z Y. Research on simulation of submarine evading torpedo attack through changing depth by strong movement[J]. Modern Defense Technology, 2024, 52(1): 124-129. [9] 付留芳, 周明, 许林周, 等. 潜艇旋回机动规避对声自导鱼雷发现概率的影响分析[J]. 舰船电子工程, 2022, 42(11): 118-122. doi: 10.3969/j.issn.1672-9730.2022.11.026Fu L F, Zhou M, Xu L Z, et al. Effect analysis of detectionprobability of submarine evasion to acoustic homing torpedo[J]. Ship Electronic Engineering, 2022, 42(11): 118-122. doi: 10.3969/j.issn.1672-9730.2022.11.026 [10] 张林芳, 刘杰, 刘冠杉. 潜艇反鱼雷防御的发展和思考[J]. 数字海洋与水下攻防, 2022, 5(5): 435-442.Zhang L F, Liu J, Liu G S. Development and thinking of submarine anti-torpedo defense[J]. Digital Ocean & Underwater Warfare, 2022, 5(5): 435-442. [11] 侯文姝, 陆铭华. 潜艇声诱饵防御声自导鱼雷改进PSO算法[J]. 水下无人系统学报, 2023, 31(3): 436-441. doi: 10.11993/j.issn.2096-3920.202205001Hou W S, Lu M H. Improved PSO algorithm to defend against acoustic homing torpedoes using an acoustic decoy of a submarine[J]. Journal of Unmanned Undersea Systems, 2023, 31(3): 436-441. doi: 10.11993/j.issn.2096-3920.202205001 [12] 李本江, 李贵彬, 丁文强. 潜艇机动规避主动自导鱼雷性能的仿真分析[J]. 声学与电子工程, 2009, 96(4): 41-43. [13] 杨真勇, 郑援, 吕海平. 潜艇机动性能对使用干扰器规避主动声自导鱼雷对抗效果的影响分析[J]. 鱼雷技术, 2011, 19(2): 129-133.Yang Z Y, Zheng Y, Lü H P. Effects of submarine’s maneuverability on evading active acoustic homing torpedo with jammer[J]. Torpedo Technology, 2011, 19(2): 129-133. [14] 梁向阳, 郭孝文, 姜雨菲. 浮标阵搜潜建模仿真与潜艇逃逸结果分析[J]. 电光与控制, 2019, 26(2): 53-56, 79. doi: 10.3969/j.issn.1671-637X.2019.02.011Liang X Y, Guo X W, Jiang Y F. Simulation of submarine searching by sonobuoy array and analysis of submarine escape[J]. Electronics Optics & Control, 2019, 26(2): 53-56, 79. doi: 10.3969/j.issn.1671-637X.2019.02.011 -
下载:
点击查看大图
计量
- 文章访问数: 497
- HTML全文浏览量: 287
- PDF下载量: 60
- 被引次数: 0
