Research on Effectiveness Evaluation of Intelligent UUV Target Recognition and Anti-Countermeasure Based on Combination Weighting TOPSIS
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摘要: 随着水声对抗作战环境日益复杂, 未来水下作战的重点主要是智能水下无人系统的对抗与反对抗, 研究智能无人水下航行器(UUV)目标识别与反对抗能力对提高智能水下无人系统的整体作战效能具有重要意义。为了评估智能UUV目标识别与反对抗效能, 文中分析了影响系统效能的主要因素, 建立了系统效能指标体系, 并给出了评估模型; 运用主客观相结合的组合赋权方法确定指标体系的权重, 采用改进的逼近理想点法(TOPSIS)对智能UUV目标识别与反对抗效能进行评估, 评估结论可为UUV目标识别与反对抗系统设计与优化提供参考。Abstract: At present, the operational environment for underwater acoustic countermeasures is increasingly complicated, The emphasis of future underwater warfare is mainly focused on the confrontation and anti-countermeasure of intelligent underwater unmanned system. The research on intelligent unmanned undersea vehicle(UUV) recognition and anti-countermeasure capability is of great significance for improving the overall operational effectiveness of intelligent underwater unmanned system. In order to evaluate the target recognition and countermeasure effectiveness of the intelligent UUV, the main factors affecting the system effectiveness are analyzed, the system effectiveness index system is established, and the evaluation model is proposed. In this study, the weight of the index system is determined by the combination of subjective and objective weighting method, and the target recognition and countermeasure effectiveness of the intelligent UUV is evaluated by the improved technique for order preference by similarity to ideal solution(TOPSIS). The evaluation conclusion can provide a reference for the design and optimize of the intelligent UUV target recognition and anti-countermeasure system.
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Key words:
- intelligent UUV /
- target recognition /
- anti-countermeasure /
- effectiveness evaluation /
- combination weighting /
- TOPSIS
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表 1 UUV目标识别与反对抗指标数值表
Table 1. UUV target recognition and anti-countermeasure index numerical table
指标 ${Y_1}$ ${Y_2}$ ${Y_3}$ ${Y_4}$ 等效搜索范围/m 1848.2 2177.4 1921.7 2283.8 自导作用距离/m 1517.6 1661.6 1347.3 1564.3 探测扇面/(°) 75.0 88.0 75.0 88.0 目标捕获距离/m 1870.4 1715.4 1577.9 1430.8 目标捕获时间/s 83.5 79.6 80.6 62.4 目标捕获概率/(%) 85 86 91 95 UUV航程消耗/km 7.1833 8.3654 5.3256 7.7554 抗脉冲压力值/MPa 3.1 3.7 3.1 3.7 距离误差/m 73.8 82.5 71.8 67.9 航向误差/(°) 6.06 5.6 5.73 5.26 分辨能力 8 10 8 10 有效攻击率/(%) 35.6 40.11 36.5 48.34 表 2 能力层判断矩阵及权重
Table 2. Ability level judgment matrix and weight
U U1 U2 U3 ${\omega _0}$ U1 1 3 5 0.636 99 U2 1/3 1 3 0.258 28 U3 1/5 1/3 1 0.104 73 表 3 熵权法权重计算结果
Table 3. Index weight calculation results of entropy weight method
指标 w 等效搜索范围/m 0.062 561 自导作用距离/m 0.046 934 探测扇面/(°) 0.052 802 目标捕获距离/m 0.081 82 目标捕获时间/s 0.119 34 目标捕获概率/(%) 0.016 778 UUV航程消耗/km 0.264 22 抗脉冲压力值/MPa 0.064 644 距离误差/m 0.040 583 航向误差/(°) 0.021 398 分辨能力 0.102 59 有效攻击率/(%) 0.126 34 表 4 组合赋权计算结果
Table 4. Calculation results of combination weighting
指标 w 等效搜索范围/m 0.086 6 自导作用距离/m 0.218 6 探测扇面/(°) 0.131 7 目标捕获距离/m 0.066 7 目标捕获时间/s 0.065 6 目标捕获概率/(%) 0.108 9 UUV航程消耗/km 0.118 1 抗脉冲压力值/MPa 0.031 6 距离误差/m 0.018 7 航向误差/(°) 0.020 2 分辨能力 0.065 8 有效攻击率/(%) 0.067 7 -
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