Autonomous capability evaluation of ground-attack UAV based on improved Hopfield neural network
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摘要:
对地攻击型无人机是当前最先进的无人装备之一，无人机必须具备很高的自主能力，自主能力成为无人机的典型作战能力。针对对地攻击型无人机的自主能力量化评价问题，从感知能力、决策能力、行为能力和安全能力4个方面，并侧重机载装备参数分析，提出了一套完整的自主能力评价指标体系。结合模型因素库，运用奇异值分解设计Hopfield神经网络权值矩阵，利用基于稀疏度的权值删减算法改进网络结构。构建自主能力评价标准，对对地攻击型无人机系统自主能力进行量化分级。仿真结果表明：相对于传统Hopfield神经网络，改进算法能够在一定范围内删除非关键的连接权值，降低网络复杂度，工程上更容易实现对地攻击型无人机系统自主能力的量化评价。
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关键词:
- 对地攻击型无人机 /
- 自主能力 /
- 指标体系 /
- 改进Hopfield神经网络 /
- 综合评价
Abstract:The ground-attack UAV has been one of the most state-of-the-art unmanned equipments, which requires a high degree of autonomous capability. Autonomous capabilityis a typical operational ability of UAV. In view of the quantitative evaluation of autonomous capability forground-attack UAV, this paper proposes a detailed evaluation index system of autonomous capability from four aspects of observation capability, decision capability, action capability and security capability, and places emphasis on the analysis of airborne equipment parameters. Combined with the model factor library, the weight matrix of Hopfield neural network is designed by singular value decomposition, and based on sparsity, the weight reduction algorithm is introduced to improve the network structure. Finally, the evaluation criterion of autonomy is established to quantify and grade the autonomous capability for ground-attack UAV system. The simulation results show that, compared with traditional Hopfield neural network, the improved algorithm can delete the unimportant connection weights within a certain range, reduce the network complexity, and easily achieve quantitative evaluation of the autonomous capability of UAV system.
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图 1 对地攻击型无人机自主能力评价指标体系
Figure 1. Evaluation index system for autonomous capabilities of ground-attack UAV
表 1 感知能力
Table 1. Observation capability
指标等级 风切变威胁感知能力(风切变预警系统) 作战目标感知能力(SAR) 最小探测距离/km 提前预警时间/s 漏警率/% 数据融合率/% 最大分辨力/(m×m) 作用距离/km 发射机峰值功率/W Ⅴ 6.5 60 1 100 8×8 80 960 Ⅳ 5.6 50 3 80 6×6 64 750 Ⅲ 4.5 35 6 60 4×4 50 600 Ⅱ 3 25 8 45 3×3 26 320 Ⅰ 1.2 15 10 25 2×2 18 180 
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表 2 决策能力
Table 2. Decision capability
指标等级 战术决策能力(自主决策专家系统) 平台计算能力(主处理运算单元) 决策因素属性值 作战策略指令值 战术规则推理值 处理器运算速度/MIPS 存取和读写速度/(GB·s-1) Ⅴ 50 29 23 600 25 Ⅳ 45 22 18 200 18 Ⅲ 39 18 14 50 10 Ⅱ 32 12 11 30 3.2 Ⅰ 25 8 9 20 1.6 注：MIPS(Million Instructions Per Second)指单字长定点指令平均执行速度。
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表 3 行为能力Ⅰ
Table 3. Action capability (Ⅰ)
指标等级 飞行能力(飞行数据记录器) 协同制导能力(空地导弹与制导雷达) 最大爬升率/
(m·s-1)最大允许过载/g 最大突防速度/(km·h-1) 最低突防高度/m 提供的导弹信息维度 提供的导弹位置精度/% 雷达天线波束宽度/(°) Ⅴ 350 9 1 480 200 12 95 2 Ⅳ 310 7.5 1 390 540 10 92 1.5 Ⅲ 246 5.4 1 080 720 8 88 0.92 Ⅱ 148 4 900 900 6 84 0.57 Ⅰ 85 3.2 720 1 000 3 80 0.32
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表 4 行为能力Ⅱ
Table 4. Action capability (Ⅱ)
指标等级 协同攻击能力(航空火力控制系统) 链路通信能力(数据总线通信系统) 导弹射程/km 挂架数量 命中精度/% 传输速率/(Mbit·s-1) 通信方式 信息时延/ms 加密化程度 数据丢包率/% Ⅴ 3 000 16 98 3 8 5 1 0.2 Ⅳ 2 500 14 95 2 6 18 0.8 2.2 Ⅲ 1 000 10 92 1.5 5 30 0.6 5 Ⅱ 750 8 90 1 2 50 0.3 8.3 Ⅰ 120 4 85 0.5 1 100 0.1 10
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表 5 安全能力
Table 5. Security capability
指标等级 健康管理能力(中央维修监测系统) 故障预测能力(中央维修监测系统) 虚警率/% 故障隔离率/% 预测时间误差/s 平均预测时间/s Ⅴ 0.5 100 0.5 10 Ⅳ 2 97 1.1 30 Ⅲ 3.5 93.9 2.5 52 Ⅱ 5 87.1 3.9 86 Ⅰ 8 85 5 100
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表 6 自主能力等级划分标准
Table 6. Criteria for level of autonomous capabilities
能力级别 感知能力 决策能力 行为能力 安全能力 5集群合作 集群互助感知 集群互助决策 集群协助攻击 预测故障并隔离 4多机协作 复杂环境自主追踪 长机分配战术规划 多机协助攻击 预测故障发生 3单机实时规划任务 机外数据辅助感知 机外重新规划上传 及时规避部分威胁 补偿大多数故障 2单机复杂计划任务 天气威胁感知 数据库调整决策 单机攻击并毁伤评估 实时健康诊断 1单机简单计划任务 针对性感知地面目标 执行预编程的决策 单机对地攻击 状态报告
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