针对低信噪比下电子侦察机接收到的多分量信号的盲检测问题,提出了一种基于特征值能量的盲信号检测算法.该算法首先计算归一化特征值,然后进行信号子空间维数估计,构建检验统计量表达式,进而研究了扰动分布,从而确定给定虚警概率下的检测门限,实现信号的盲检测.理论分析和仿真结果表明,该算法对多分量信号尤其是时频重叠的多分量信号适应性强,和现有的利用特征值分析的盲检测算法相比,性能可以提高2dB.%To solve the blind detection problem that electronic surveillance aircraft received data is multi-component signal in low signal-to-noise ratio, a new blind detection algorithm based on eigenvalue-energy is proposed. Firstly, the normalized eigenvalues are calculated and the signal subspace dimension is estimated. Secondly, the expression of the test statistic is constructed and the disturbance's distribution is studied, then the detection threshold is calculated under the given false alarm probability. Lastly, the blind detection is realized by comparing the test statistic and the threshold. Theoretical analysis and simulation results show that this new algorithm can applied to multi-component signal, especially the time-frequency overlapped multi-component signal. Compared to current eigenvalue-based algorithm, the performance can increase 2 dB.
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