复杂海洋环境中，无人艇通信系统易受自然干扰、人为干扰及多普勒频偏等因素影响。本文分析无人艇通信面临的多类型干扰特征及典型场景参数建模，提出“频谱感知-干扰分类-自适应抑制”三级融合抗干扰架构，并设计抗干扰抑制系统，通过噪声功率动态估计与循环平稳特征检测提升低信噪比下的干扰识别精度，设计低复杂度变步长递归最小二乘（RLS）算法降低计算开销。最后通过仿真与无人艇实船测试，在平静湖面与复杂海况场景下验证了系统性能。结果表明，本文提出的抗干扰架构能够实现干扰抑制增益≥25 dB，系统响应时延≤10 ms，满足无人艇动态作业的抗干扰需求。
In complex marine environments, the communication system of unmanned surface vessels (USVs) is susceptible to natural interference, man-made interference, Doppler frequency shift, and other factors. This paper analyzes the characteristics of multiple types of interference faced by USV communication and the parameter modeling of typical scenarios, proposes a three-level integrated anti-jamming architecture of "spectrum sensing - interference classification - adaptive suppression", and designs an anti-jamming system. To improve the interference recognition accuracy under low signal-to-noise ratio (SNR), a combination of dynamic noise power estimation and cyclostationary feature detection is adopted. A low-complexity variable-step-size RLS algorithm is designed to reduce computational overhead. Finally, the system performance is verified through simulations and sea trials on a USV under both calm lake and complex sea state scenarios. The results demonstrate that the proposed anti-jamming architecture can achieve an interference suppression gain of ≥25 dB, and a system response delay of ≤10 ms, which meets the anti-jamming requirements of USVs for dynamic operations.
2025,47(24): 147-151 收稿日期：2025-6-17
DOI：10.3404/j.issn.1672-7649.2025.24.023
分类号：U674.941；TN973.3
作者简介：张秀丽(1988-),女,硕士,讲师,研究方向为电子与通信技术
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