一种无人机蜂群飞行同步检测和抑制方案

张霞; 余道杰; 刘广怡; 白艺杰; 王钰

doi:10.11999/JEIT221084

一种无人机蜂群飞行同步检测和抑制方案

doi: 10.11999/JEIT221084

战略支援部队信息工程大学郑州 450000

详细信息

作者简介:
张霞：女，副教授，研究方向为无人机网络协议设计与优化

余道杰：男，教授，研究方向为无人机蜂群干扰反制

刘广怡：男，讲师，研究方向为无人机蜂群设计

白艺杰：女，博士生，研究方向为无人机网络协议设计与优化

王钰：男，硕士生，研究方向为无人机蜂群设计与优化

通讯作者:
余道杰　yudj2003@163.com

中图分类号: TN975
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出版历程
- 收稿日期: 2022-08-16
- 修回日期: 2022-10-15
- 网络出版日期: 2023-04-06
- 刊出日期: 2023-12-26

Countermeasures Against UAV Swarm Through Detection and Suppression of Fly Synchronization

Institute of Information System Engineering, PLA Strategic Support Force Information Engineering University, Zhengzhou 450000, China

摘要

摘要: 该文研究了无人机蜂群飞行同步的检测和干扰方案，把无人机蜂群飞行同步过程看作复杂系统的涌现效应，提出一种基于双阈值的涌现判定算法。通过同时监测目标系统飞行同步过程中的熵差和网络连通度，克服已有算法因忽略网络状态监控而误判的问题，准确及时地识别飞行同步的发生、达成和失败，为控制抑制时机提供坚实的前提基础。以平均功率为约束设计带内干扰行为，从使目标系统通信容量降低的角度建立干扰行为模型，并通过仿真分析其效能。研究发现，低强度持续干扰可有效迟滞目标系统同步过程、延长同步时间，且具有更好隐蔽性；中等强度持续干扰可快速终止飞行同步过程。基于以上分析，首次根据破坏和迟滞的不同作战意图设计了无人机蜂群飞行同步的反制方案。通过仿真验证了其有效性。
- 无人机蜂群 /
- 反制 /
- 飞行同步 /
- 带内干扰 /
- 涌现
Abstract: This paper studies the detection and suppression mechanisms of fly synchronization of Unmanned Aerial Vehicle (UAV) swarm. Fly synchronization process is viewed as emergence in the complex system. A detection algorithm is proposed based on emergence identification with double thresholds. By simultaneously monitoring the entropy difference of flight synchronization process and network connectivity of the target system, the misjudgment of existing algorithms caused by ignoring the network status is overcomed, and the occurrence, achievement, or failure of fly synchronization is accurately identified, which provides a solid prerequisite for the timing control of the suppression mechanism. In-band radio interference behavior is designed under the constraint of average power. The interference behavior modeled from the perspective of degrading the target system’s communication capacity and the effect is analyzed through simulations. It is found that low-intensity continuous interference can effectively delay the fly synchronization process and prolong the time of that. What’s more, it has better concealment. Medium-intensity continuous interference can rapidly stop that process. Based on the above perception, for the first time, countermeasures for the UAV swarm’s fly synchronization are designed according to different operational intentions of delay and disruption. Simulation results show the effectiveness of the countermeasures.
- UAV swarm /
- Countermeasure /
- Fly synchronization /
- In-band interference /
- Emergence

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图 1 两种现有方法下目标系统的涌现强度

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图 2 不同同步半径下系统在仿真结束时的位置分布

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图 3 固定强度、不同占空比的干扰效能对比

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图 4 干扰对飞行同步的迟滞效果

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图 5 固定平均干扰强度、不同干扰模式的效能对比

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图 6 中等强度条件下的随机和固定图案干扰对比

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图 7 低强度条件下随机和固定干扰图案反制效能对比

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图 8 以破坏目标系统飞行同步为目的反制策略的效果

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图 9 反制成功后目标系统的拓扑

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图 10 释放和不释放干扰时系统熵差的变化

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图 11 干扰和不干扰时达成同步后的网络拓扑对比

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算法1　基于双阈值的涌现判定算法
步骤1：设定参数初始值，$\varPhi = \phi $, $L = \{ {l_0}\} $，连通度阈值${\delta _c} $。
步骤2：监视是否发现目标无人机集群。
若发现目标，测量个体速度角$\varPhi = \{ {\varphi_i},i = 1, 2,\cdots ,N\}$，记当前　时刻为$t = 0 $，根据式(7)估计$\varPhi$的概率分布，计算初始观察时　刻熵${H_0} $。
步骤3：测量t时刻UAVs速度角$\varPhi = \{ {\varphi _i},i = 1, 2,\cdots ,N\}$，根据　　　　式(7)估计其概率分布，计算角度熵${H_t} $，计算熵差　　　　 ${E_t} = {H_0} - {H_t} $。
若$E > 0 $，则记录涌现起始时刻${t_{{\rm{start}}} } = t$，记录${E_{ {t_{{\rm{start}}} } } }$，进入步　　　　骤4；否则回到步骤3；
步骤4：设定滑窗长度为2，在滑窗内连续观测目标系统，并记录　　　　如下状态。
for $t = {t_0}:{t_0} + k $：
{4a.对时刻t，测量各节点的速度角${\varPhi }$，根据式(7)估计其概率分　布，并计算角度熵${H_t} $和熵差${E_t} $，测量位置$L = {l_i},i = 1, 2,\cdots ,N $，　根据式(10)计算$C(t) $，判定是否满足$C\left( t \right) > 1 - {\delta _c} $。若不满　足，则判定无法达到涌现，记录判定时间${t_{{\rm{end}}} }$，跳到步骤5；若　满足，跳到4b}
4b.计算观察窗口内两个连续的熵差，若满足　$\Delta {E_1} = {E_{{t_0} + 1}} - {E_{{t_0}}} $, $ \Delta {E_2} = {E_{{t_0} + 2}} - {E_{{t_0} + 1}} > 0 $且　$ \Delta {E_1} > \Delta {E_2} $，则判定为涌现达成，记录判定结果记录flag为涌　现成功，记录${t_{{\rm{end}}} } = i$；}
步骤5：记录判定结果，计算判定时间$t = {t_{{\rm{end}}} } - {t_{{\rm{start}}} }$。

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算法2　无人机蜂群飞行同步反制方案
步骤1　初始化$ {\delta _c} $，启动无人机蜂群监测，若发现目标，转步　　　　骤2，否则，转步骤1；
步骤2　利用算法1判定是否启动飞行同步，若是，则转步骤3，　　　　否则，转步骤2；
步骤3　测量到目标无人机蜂群的距离，利用式(15)计算路径损耗^[26]。
${\rm{Loss}}[{\rm{dB}}] = 32.44 + 20\lg d\left( {{\rm{km}}} \right) + 20\lg f\left( {{\rm{MHz}}} \right) - 20 \lg A$ (15)
其中，d是到蜂群的距离，以km计；f是工作频点，以MHz计；　A是路径损耗因子，通常取2到4。将路径损耗转换为比值形式，　即${l_{{\rm{path}}} } = 1{0^{{\rm{Loss}}/10} }$；
步骤4　根据反制意图和${l_{{\rm{path}}} }$，按如下方式生成干扰图案　　 ${\boldsymbol{I}} = [{I_m},m = 1,2,\cdots,M]$，发送干扰信号。
4a 若为了迟滞飞行同步，则发送低强度持续干扰信号(即占空　比100%)，等效噪声系数设为$\beta = 0.25 $，即${I_m} = \beta {n_0}B{l_{{\rm{path}}} }$；
4b 若为了破坏飞行同步，则发送中等强度持续干扰信号(即，占　空比100%)等效噪声系数$ \beta = 1 $, ${I_m} = \beta {n_0}B{l_{{\rm{path}}} }$；
步骤5　测量目标系统连通度$C(t) $，若$ C\left( t \right) < 1 - {\delta _c} $，或　　 $ C\left( t \right) > 1 - {\delta _c} $且目标达成同步，则终止干扰。

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