为助力民航无线电监测系统提升干扰检测与应急响应能力，提出了一种基于随机矩阵理论的自适应全球导航卫星系统（global navigation satellite system, GNSS）干扰盲检测方法。首次将频谱感知领域的最大特征值检测算法（maximum eigenvalue detection, MED）技术应用于民航GNSS干扰检测中，并改进了传统MED算法的门限值，提出了自适应最大特征值检测算法（adaptive maximum eigenvalue detection, A-MED），在无需先验信息的情况下显著提升了低信噪比条件下的检测性能。仿真实验表明，A-MED算法在对单音、多音、扫频、脉冲及部分带噪声干扰信号的检测实验中性能最优，低信噪比（-30 dB）时检测概率已达0.8，并快速趋于1。对于脉冲干扰（pulse interference, PI），能量检测法（energy detection, ED）在脉冲幅值较小时存在局限性，而MED和A-MED均能有效检测。

To enhance the interference detection and emergency response capabilities of civil aviation radio monitoring systems, an adaptive blind GNSS interference detection method was proposed based on random matrix theory. The maximum eigenvalue detection(MED) algorithm in the field of spectrum sensing was transplanted to the civil aviation GNSS interference detection for the first time, and the threshold value of the traditional MED algorithm was improved. The adaptive maximum eigenvalue detection (A-MED) algorithm was proposed, which significantly improved the detection performance under the condition of low signal-to-noise ratio without prior information. The simulation experiments show that the A-MED algorithm has the best performance in the detection experiments of single-tone, multi-tone, sweep frequency, pulse and some noisy interference signals. The detection probability has reached 0.8 at a low signal-to-noise ratio (-30 dB) and is rapidly approaching 1. For pulse interference (PI), the energy detection method (ED) has limitations when the pulse amplitude is small, while both MED and A-MED can effectively detect it.