基于分数阶功率谱熵的未知水声脉冲信号检测方法

Detection of unknown underwater acoustic pulse signal based on fractional power spectrum entropy

水声侦察的核心问题是在无先验知识条件下捕获其他平台发射的脉冲信号,单频(Continuous Wave,CW)信号和调频(Frequency Modulation,FM)信号是常用的水声探测脉冲。功率谱熵算法能有效检测低信噪比的CW信号,但对FM信号性能不佳,分数阶傅里叶变换(Fractional Fourier Transform,FRFT)则能聚集FM信号能量。利用FRFT的性质,结合功率谱熵算法,设计了分数阶功率谱熵检测器,可在分数阶域实施未知脉冲信号检测。理论分析了FRFT对FM信号的能量聚集作用,优化了FRFT阶数搜索方法。仿真实验以及海试数据处理结果证实检测器对FM信号性能良好,且对CW信号的侦察检测性能无影响。通过门限学习,检测器可实现对未知水声脉冲信号的统一自动检测。

The core of underwater acoustic reconnaissance is to capture the pulse signals transmitted by other platforms without prior knowledge.Continuous wave(CW)signal and frequency modulation(FM)signal are the most widely used detection pulses.CW signal can be effectively detected by power spectrum entropy algorithm at low signal to noise ratio(SNR),but the performance of this algorithm for FM signal detection is degraded.Fractional Fourier transform(FRFT)can gather energy of FM signal.By using the properties of FRFT and power spectrum entropy algorithm,a fractional power spectrum entropy detector is designed,which can detect unknown signal in the fractional domain.And then,the energy accumulation of FRFT for FM signal is analyzed,and the method of FRFT order search is optimized.The simulation results and experimental results at sea demonstrate that the new detector has good detection performance on FM signal and has no effect on CM signal.The detector can complete unified automatic detection for unknown un-derwater acoustic pulse signal.