低空无人机群声学预警技术发展

doi:10.3969/j.issn.1009-086x.2026.05.001

摘要/Abstract

摘要：

低空无人机群凭借低成本、易部署和协同突防等特点，逐步压缩低空防御体系的预警与处置效能。雷达、光电和无线电在低空遮蔽、复杂电磁环境与静默飞行等场景存在探测盲区，声学预警因被动隐蔽、布设灵活可作为补充。多机协同飞行存在谐波重叠、声场混叠和定位误差累积，增加分离、测向与态势生成难度，是低空无人机群预警的热点研究之一。围绕声纹特性、系统架构、阵列前端、鲁棒识别、多目标声源分离定位、分布式组网及多模态融合等关键技术问题，系统凝练了相关研究进展，梳理了分布式声-光-电-磁融合预警体系，可为低空无人机群全域立体协同预警技术体系构建提供支持。

关键词: 低空无人机群, 声学预警, 声纹, 声源定位, 分布式声学网络, 多模态融合

Abstract:

Low-altitude UAV swarms， characterized by low cost， easy deployment， and cooperative penetration， are progressively degrading the early-warning and response effectiveness of low-altitude defense systems. Radar， electro-optical and radio-frequency surveillance may have detection blind spots in scenarios involving low-altitude masking， complex electromagnetic environments and radio-silent flight， whereas acoustic early warning provides a passive， covert and flexibly deployable complement. Coordinated multi-UAV flight causes harmonic overlap， sound-field mixing and accumulated localization errors， which complicate source separation， direction finding and situation generation. This paper synthesizes research progress in acoustic signatures， system architectures， array front ends， robust recognition， multi-target sound source separation and localization， distributed networking and multimodal fusion. It further outlines a distributed integrated acoustic-optical-electronic-magnetic early-warning architecture， providing support for the development of an all-domain， three-dimensional collaborative early-warning technology system for low-altitude UAV swarms.

Key words: low-altitude UAV swarm, acoustic early warning, acoustic signature, sound source localization, distributed acoustic network, multimodal fusion

中图分类号:

TN974

王文杰, 牛煜智, 孙西仓, 王梓, 何敬玉, 侯艳杰, 支强, 杨玖文. 低空无人机群声学预警技术发展[J]. 现代防御技术, 2026, 54(5): 1-17.

Wenjie WANG, Yuzhi NIU, Xicang SUN, Zi WANG, Jingyu HE, Yanjie HOU, Qiang ZHI, Jiuwen YANG. Development of Acoustic Early Warning Technology for Low-altitude UAV Swarms[J]. Modern Defense Technology, 2026, 54(5): 1-17.

图/表 12

图1 无人机旋翼噪声典型频谱特征示意图［6］

Fig. 1 Typical spectral characteristics of UAV rotor noise

图2 无人机群声学预警系统架构图

Fig. 2 Architecture of UAV swarm acoustic early warning system

图3 无人机声学预警核心信号处理技术框架

Fig. 3 Core signal processing framework for UAV acoustic early warning

图4 典型无人机声学预警阵列构型示意图

Fig. 4 Typical array configurations for UAV acoustic early warning

图5 战场环境噪声抑制流程示意图

Fig. 5 Battlefield environmental noise suppression workflow

图6 低功耗边缘声学预警节点工作流程图

Fig. 6 Workflow of low-power edge acoustic early warning node

图7 无人机声学鲁棒识别流程图

Fig. 7 Robust acoustic recognition workflow for UAVs

图8 多目标声源分离、测向与定位级联误差示意图

Fig. 8 Cascaded errors in multi-target sound source separation， direction finding， and localization

图9 分布式声学节点与多模态融合预警链路示意图

Fig. 9 Distributed acoustic nodes and multimodal fusion early warning link

图10 分布式声学预警网络工作机制图

Fig. 10 Operating mechanism of distributed acoustic early warning network

图11 声学与异类传感器互补融合链路图

Fig. 11 Complementary fusion link for acoustic and heterogeneous sensors

图12 实战声学预警系统效能评估框架图

Fig. 12 Effectiveness evaluation framework for operational acoustic early warning systems

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