To effectively detect a multi-component emitter signal (MCES) composed of several signal components with different energies and serious overlapping in the time-frequency plane, a detection method based on product high-order ambiguity function ( PHAF) was proposed. By using a strategy of peeling onion, this method sequentially detects signal components in light of their energy magnitudes. In the process of detection, the signal components with strong energy are first detected and then are deleted from the original signal so that the signal components with weak energy are not interfered by the cross-terms and other signal components. Through multiplying several high-order ambiguity functions with different time-delays, the method strengthens the useful signal components, weakens noises and effectively detects the multi-component emitter signal with a low signal-to-noise ratio. The analysis and test results show that the proposed method can effectively detect multi-component emitter signals with serious overlapping in the time-frequency plane, and that the relative detection error is less than 2.457 × 10 -4 and 7.560 × 10 -2 for the signal components with strong energy and the ones with weak energy, respectively; and to noised signals, it is respectively less than 1.300 × 10 -3 and 7.330 × 10 -2 for the two kinds of the signal components.%为解决信号分量能量不同且时频交叠严重时多分量辐射源信号的检测问题,提出了一种基于乘积高阶模糊函数(PHAF)的检测方法.该方法采用"剥洋葱"的策略,按照能量强弱逐次检测各信号分量.检测时,先检测和剥除能量较强的信号分量,以避免弱信号分量受其它信号分量和交叉项的干扰.将不同时延的高阶模糊函数相乘,以强化信号分量、弱化噪声,有效检测低信噪比信号.分析和实验结果表明:提出的方法能有效检测时频交叠严重的多分量辐射源信号,对强、弱能量信号分量的相对检测误差分别小于2.457×10-4和7.560×10-2;检测含噪声的信号时,对强、弱能量信号分量的相对检测误差分别小于1.300×10-3和7.330×10-2.
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