用于被动声纳微弱目标检测的宽带最大信噪比方法

本文尝试利用匹配场处理中的能量匹配思想，对阵列波束形成进行优化，用于解决水下目标被动声纳微弱信号检测问题。首先，本文对比了基于线性非相干、MVDR非相干、线性相干和MVDR相干四种匹配场处理器的检测方法的性能，之后分析推导了线性非相干处理器的输出信噪比和输出功率，得出了在声源频谱起伏增大时线性非相干处理器的检测能力会下降的结论。为了得到更高的输出信噪比，本文提出了最大信噪比处理器，在理想情况下可以在处理带宽上达到最高的输出信噪比。最大信噪比处理器没有通过归一化消除声源的影响，而是利用声源频谱的估计值和拷贝场直接对接收数据进行匹配。本文证明了最大信噪比处理器的检测能力优于线性非相干处理器，并且通过仿真实验进一步验证了这个结论。 

Broadband Maximum Signal-to-Noise Ratio Method for Weak Target Detection of Passive Sonar

? ?In this paper， we tries to apply the concept of energy matching in the matched field processing to the optimization of the array beamforming to solve the weak signal detection problem of passive sonar. First， the detection capabilities based on four matched-field processors: linear incoherent， MVDR incoherent， linear coherent and MVDR coherent， are compared， then the output signal-to-noise ratio （SNR） and output signal power of linear incoherent processor are analyzed. Based on the analysis， the detection ability of the linear incoherent processor will decrease when the frequency fluctuation of the sound source increases. In order to obtain a higher output signal-to-noise ratio， this paper proposes a maximum SNR processor， which can achieve the highest output SNR in the processing bandwidth under ideal conditions. The maximum SNR processor does not eliminate the influence of the sound source through normalization， but uses the estimated value of the sound source spectrum and the copy field to directly match the received data. This paper proves that the detection ability of the maximum SNR processor is better than that of the linear incoherent processor， and this conclusion is further verified by simulation experiments.