基于遗传算法的应召搜潜路径优化

张宁; 寇小明; 李斌; 李谦; 周景军

doi:10.11993/j.issn.2096-3920.2022-0002

基于遗传算法的应召搜潜路径优化

doi: 10.11993/j.issn.2096-3920.2022-0002

中国船舶集团有限公司第705研究所, 陕西西安, 710077

详细信息

作者简介:
张宁：张　宁(1997-), 男, 在读硕士, 主要研究方向为水下航行器总体技术

中图分类号: U674.71; TJ67
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- 文章访问数: 291
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- PDF下载量: 74
- 被引次数: 0
出版历程
- 收稿日期: 2022-06-06
- 修回日期: 2022-07-08
- 录用日期: 2022-07-27
- 网络出版日期: 2023-03-10

Route Optimization of on Call Submarine Search Based on Genetic Algorithm

The 705 Research Institute, China State Shipbuilding Corporation Limited, Xi’an 710077, China

摘要

摘要: 针对水面舰艇应召反潜中敌潜艇未知航向机动的情形, 提出了一种基于遗传算法的对潜搜索方法。该方法分别结合了舰船声呐探测模型、敌潜艇目标运动模型、舰船搜索运动模型以及搜索路径发现概率计算模型, 并将信息置信度引入发现概率计算模型, 增强了发现概率计算的可信度; 再利用遗传算法分别求解单舰及双舰在应召反潜搜索过程中每段的最优航向角和速度, 分别给出单舰和双舰应召螺旋搜索的最优路径; 最后给出了单舰和双舰在仅改变转角和既改变转角又改变速度条件下, 搜索到目标发现概率的变化规律。通过与传统螺旋算法对比表明, 增加改变速度的舰船搜索机制更为灵活, 可提高发现概率; 当搜索兵力足够时, 采用多舰编队搜索可大幅度提高发现概率。该研究可为水面舰搜攻潜作战提供参考。
- 水面舰艇 /
- 应召搜索 /
- 螺旋搜索 /
- 遗传算法 /
- 发现概率
Abstract: To address the situation wherein an enemy submarine maneuvers in an unknown course when an anti-submarine surface ship is called, a genetic algorithm-based submarine search method is proposed. The method combines the ship sonar detection model, enemy submarine target motion model, ship search motion model, and search path discovery probability calculation model. It introduces information confidence into the discovery probability calculation model, which enhances its reliability. Subsequently, a genetic algorithm is used to solve the optimal heading angle and speed of each section of a single ship and double ships in the on-call search process, and the optimal paths of single and double ships on call spiral search are determined. Finally, the variation law of the discovery probability of searching the target is formulated under the conditions of changing only the heading angle and changing both the angle and speed of single and double ships. The results indicate that, compared to the traditional spiral algorithm, the ship search mechanism with increasing change speed is more flexible and can improve the discovery probability. When the search force is sufficient, using a multiship formation search can significantly improve the discovery probability. The results provide a tactical reference for surface ship searches and submarine attacks.
- surface ship /
- on call search /
- spiral search /
- genetic algorithm /
- discovery probability

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图 1 声呐探测范围示意图

Figure 1. Schematic diagram of sonar detection range

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图 2 舰船搜索过程示意图

Figure 2. Schematic diagram of ship search process

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图 3 遗传算法流程图

Figure 3. Flow chart of genetic algorithm

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图 4 目标分布图

Figure 4. Target distribution

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图 5 单舰起始探测点示意图

Figure 5. Schematic diagram of initial detection point of single ship

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图 6 单舰仅改变航向角的搜索路径

Figure 6. Search path of single ship only changing heading angle

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图 7 单舰改变各段航向角和各段速度的搜索路径

Figure 7. Search path of single ship changing heading angle and speed of each section

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图 8 单舰传统螺旋线搜索路径

Figure 8. Single ship traditional spiral search path

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图 9 双舰搜索示意图

Figure 9. Schematic diagram of double ships search

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图 10 双舰仅改变航向角的搜索路径

Figure 10. Search path of double ships only changing heading angle

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图 11 双舰改变各段航向角和各段速度的搜索路径

Figure 11. Search path of double ships changing heading angle and speed of each section

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图 12 双舰传统螺旋线搜索路径

Figure 12. Double ships traditional spiral search path

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表 1 引入信息置信度参数变化

Table 1. Parameter changes of introduced information confidence

参数名称	未引入信息置信度	引入信息置信度后
目标消失方位	$({x_0},{y_0})$	$({x_0},{y_0})Q$
航速	$V$	$VQ$

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表 2 单舰仅改变航向角参数值

Table 2. Parameter values of single ship only changing heading angle

阶段数	θ/rad	阶段数	θ/rad
1	0.626 6	9	1.400 8
2	0.079 5	10	1.401 1
3	0.064 7	11	1.579 8
4	0.074 1	12	1.959 2
5	0.232 1	13	2.009 3
6	0.378 8	14	2.193 4
7	0.639 1	15	2.525 0
8	1.228 4

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表 3 单舰改变各段速度和航向角参数值

Table 3. Parameter values of changing speed and heading angle of each section of a single ship

阶段数	${v \mathord{\left/ {\vphantom {v {{\text{kn}}}}} \right. } {{\text{kn}}}}$	${\theta \mathord{\left/ {\vphantom {\theta {{\text{rad}}}}} \right. } {{\text{rad}}}}$
1	20.177 4	1.168 1
2	16.678 0	1.092 6
3	24.991 2	5.812 2
4	24.921 8	6.050 2
5	24.714 4	6.266 5
6	23.727 5	6.282 1
7	24.326 8	0.724 3
8	24.989 9	1.520 3
9	24.958 0	1.695 6
10	24.830 5	1.815 3
11	24.954 2	2.072 5
12	24.985 5	2.292 0
13	24.905 0	2.673 7
14	24.980 5	2.851 6
15	24.951 4	3.270 7

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表 4 单舰不同搜索算法的发现概率对比

Table 4. Comparison of discovery probability of different search algorithms for single ship

仿真次数	发现概率/%
仿真次数	单舰变航向搜索算法	单舰变航向和速度搜索算法	单舰传统螺旋搜索算法
100	69.80	79.20	42.43
500	69.82	79.18	42.45
1 000	69.84	79.17	42.39
2 000	69.81	79.19	42.42

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表 5 双舰仅改变航向角参数值

Table 5. Parameter values of only changing heading angle of double ships

阶段数	${{{\theta _1}} \mathord{\left/ {\vphantom {{{\theta _1}} {{\text{rad}}}}} \right. } {{\text{rad}}}}$	${{{\theta _2}} \mathord{\left/ {\vphantom {{{\theta _2}} {{\text{rad}}}}} \right. } {{\text{rad}}}}$
1	1.179 1	0.080 3
2	1.410 7	0.064 0
3	1.998 8	0.045 9
4	1.624 2	0.330 6
5	1.047 9	0.661 2
6	1.330 9	0.849 8
7	0.535 8	0.990 1
8	0.683 8	1.298 3
9	0.427 2	1.186 4
10	0.325 7	1.781 1
11	0.033 7	1.654 4
12	1.300 9	1.884 6
13	1.288 0	2.191 8
14	1.404 4	2.021 5
15	1.857 2	2.530 5

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表 6 双舰改变各段速度和各段航向角参数值

Table 6. Parameter values of heading angle and speed of each section changed by double ships

阶段数	${{{v_1}} \mathord{\left/ {\vphantom {{{v_1}} {{\text{kn}}}}} \right. } {{\text{kn}}}}$	${{{\theta _1}} \mathord{\left/ {\vphantom {{{\theta _1}} {{\text{rad}}}}} \right. } {{\text{rad}}}}$	$ {{{v_2}} \mathord{\left/ {\vphantom {{{v_2}} {{\text{kn}}}}} \right. } {{\text{kn}}}} $	${{{\theta _2}} \mathord{\left/ {\vphantom {{{\theta _2}} {{\text{rad}}}}} \right. } {{\text{rad}}}}$
1	23.775 9	0.913 2	24.748 7	0.125 7
2	24.932 3	1.914 3	24.318 4	0.024 6
3	22.450 5	1.593 2	23.845 4	0.250 1
4	18.205 7	1.288 9	24.905 1	0.679 2
5	18.104 8	1.026 6	16.196 8	0.646 1
6	10.453 1	1.545 9	14.426 6	1.481 8
7	14.095 9	0.668 4	12.418 1	1.147 9
8	20.580 9	0.422 5	15.895 8	1.290 7
9	21.647 3	0.260 3	24.853 2	1.597 2
10	24.788 0	0.141 0	19.722 3	1.372 0
11	10.229 7	0.061 0	21.602 7	2.247 2
12	12.748 0	0.468 1	24.030 4	2.196 8
13	18.631 7	5.964 3	16.283 2	2.163 9
14	16.948 0	6.266 2	17.540 8	2.561 3
15	14.691 8	3.410 1	22.136 5	3.140 4

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表 7 双舰不同搜索算法的发现概率对比

Table 7. Comparison of discovery probability of different search algorithms for double ships

仿真次数	发现概率/%
仿真次数	双舰编队变航向搜索算法	双舰编队变航向和速度搜索算法
100	87.01	95.00
500	86.97	95.03
1 000	87.02	94.96
2 000	86.98	95.03


仿真次数	发现概率/%
仿真次数	双舰传统螺旋搜索算法	双舰单独搜索算法
100	65.78	66.82
500	65.80	66.87
1 000	65.82	66.81
2 000	65.81	66.85

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参考文献(13)

[1]	陈菁, 何心怡, 高贺, 等. 水面舰艇编队反潜武器系统架构与关键技术[J]. 指挥控制与仿真, 2016, 38(6): 12-15. Chen Jing, He Xinyi, Gao He, et al. Anti-submarine weapon system architecture and key technology of surface ship formation[J]. Command Control and Simulation, 2016, 38 (6): 12-15.
[2]	鞠建波, 郁红波, 范赵鹏, 等. 吊放声呐扩展螺旋阵搜潜效能评估改进方法[J]. 水下无人系统学报, 2020, 28(4): 434-439. Ju Jianbo, Yu Hongbo, Fan Zhaopeng, et al. An improved method for submarine search efficiency evaluation of extended spiral array of suspended sonar[J]. Journal of Underwater Unmanned Systems, 2020, 28 (4): 434-439.
[3]	屈也频, 廖瑛. 潜艇位置散布规律与搜潜效能评估模型研究[J]. 系统仿真学报, 2008(12): 3280-3283, 3289. doi: 10.16182/j.cnki.joss.2008.12.054 Qu Yepin, Liao Ying. Research on submarine position dispersion law and submarine search efficiency evaluation model[J]. Journal of System Simulation, 2008(12): 3280-3283, 3289. doi: 10.16182/j.cnki.joss.2008.12.054
[4]	崔旭涛, 何友, 杨日杰. 应召平行搜索方法的多舰协同搜潜概率[J]. 火力与指挥控制, 2010 (8): 29-31. Cui Xutao, He You, Yang Rijie. Multi ship cooperative submarine search probability of call parallel search method[J]. Fire and command and control, 2010(8): 29-31
[5]	吴芳, 杨日杰, 徐俊艳. 基于遗传算法的对潜螺旋搜索[J]. 系统仿真学报, 2009, 21(6): 1682-1684. Wu Fang, Yang Rijie, Xu Junyan. Latent spiral search based on genetic algorithm[J]. Journal of System Simulation, 2009, 21(6): 1682-1684.
[6]	崔旭涛, 杨日杰, 何友. 基于潜艇航向均匀分布的多舰检查搜潜建模与仿真[J]. 现代电子技术, 2009(23): 20-22, 26. Cui Xutao, Yang Rijie, He You. Modeling and simulation of multi ship inspection and submarine search based on uniform distribution of submarine course[J]. Modern Electronic Technology, 2009(23): 20-22, 26.
[7]	Martin J. Multiplying the effectiveness of helicopter ASW sensors[J]. Sea Technology(S0093-3651), 2006, 47(11): 33-36.
[8]	崔旭涛, 何友, 杨日杰, 等. 基于舰壳声纳的多舰协同检查搜潜建模与仿真[J]. 海军航空工程学院学报, 2009, 24(5): 568-572. Cui Xutao, He you, Yang Rijie, et al. Modeling and simulation of multi ship cooperative inspection submarine search based on ship hull sonar[J]. Journal of Naval Aeronautical Engineering College, 2009, 24(5): 568-572.
[9]	赵亮, 任耀峰, 张献. 舰艇编队协同应召搜索最优路径规划方法[J]. 指挥控制与仿真, 2017(2): 24-30. doi: 10.3969/j.issn.1673-3819.2017.02.006 Zhao Liang, Ren Yaofeng, Zhang Xian. Optimal path pl- anning method for ship formation cooperative call to se- arch[J]. Command control and simulation, 2017(2): 24-30. doi: 10.3969/j.issn.1673-3819.2017.02.006
[10]	瓦格纳, 迈兰德, 森德. 海军运筹分析[M]. 3 版. 姜青山, 郑保华, 译. 北京: 国防工业出版社, 2008.
[11]	Kierstead D P, DelBalzo D R. A genetic algorithm applied to planning search paths in complicated environment[J]. Military Operations Research, 2003, 8(2): 45-59. doi: 10.5711/morj.8.2.45
[12]	吴柱, 孙睿, 许腾. 搜潜发现概率模型探讨[J]. 指挥控制与仿真, 2010, 32(5): 28-30. Wu Zhu, Sun Rui, Xu Teng. Discussion on probability model of submarine search and discovery[J]. Command control and simulation, 2010, 32(5): 28-30.
[13]	张溢文, 尹韶平, 王志杰, 等. 基于多目标遗传算法的雷载计算机隔振系统优化设计[J]. 水下无人系统学报, 2017, 25(2): 57-63. Zhang Yiwen, Yin Shaoping, Wang Zhijie, et al. Optimal design of vibration isolation system of mine borne computer based on multi-objective genetic algorithm[J]. Journal of Underwater Unmanned Systems, 2017, 25(2): 57-63.