局域波分解在被动测向声纳中的应用

局域波分解可以把复杂信号分解为有限个内蕴模式函数和一个趋势项,这个过程相当于在时间域上对不同的频率信号进行分类。不同的内蕴模式函数分量代表了不同频率分量的信号成分,利用海洋环境噪声与目标信号频域特征或相关函数的不同,滤除被动测向声纳接收信号中的海洋环境噪声,提高输入信号的信噪比,进而提高被动测向声纳的检测性能。提出了基于局域波分解的被动测向声纳信号检测模型。计算机仿真结果表明,相对于传统的二元被动测向声纳检测模型,基于局域波分解的信号检测模型可以有效提高被动测向声纳的检测性能。

The application of local-wave decomposing method in passive bearing sonar

Local-wave decomposing method can decompose complex signal into several intrinsic mode functions and a residue. This equals to sorting signals of different frequencies in time field. Different intrinsic mode functions have different frequencies. Noise can be eliminated from the received signal by taking advantage of the differences of the frequency features or the difference of their correlation functions. SNR can be enhanced and the detection performance of passive bearing sonar improved. Signal detection method based on local-wave decomposing is put forward. The result obtained by computer simulation makes it clear that, compared to the traditional bearing method of two-array passive sonar, the signal detection method based on local-wave decomposing can improve the detection performance of the passive bearing sonar effectively.