Adaptive filter design for suppressing the moving surface interferences in optic-acoustic remote sensing
Adaptive filter design for suppressing the moving surface interferences in optic-acoustic remote sensing
复制标题
光声遥感中运动表面干扰抑制的自适应滤波器设计
作者：
Xiaodong Peng;Wen Xu;Xiaofeng Jin;J. Shang
光声遥感技术被提出来从空中探测水下声音信号，从而为水下通信和探测提供了一种新的方法。它利用了在水环境中传播的声压波引起空气-水界面振动的事实，并且可以通过观察从激光干涉仪发出的反射光束的幅度或相位特性来光学检测粒子速度。本文研究了我们的光声遥感实验中观察到的一个有趣的现象。在水动力表面条件下，空气-水界面处于运动状态，因此运动的水面是强干扰源。我们设计了一些自适应滤波器，例如最小均方（LMS）、递归最小二乘（RLS）和卡尔曼滤波器来抑制这种干扰。将设计的滤波器应用于实验原始数据，处理结果表明信干比明显提高。
Optic-acoustic remote sensing has been proposed to detect underwater sound signal from the air, thus providing a new method for underwater communication and detection. It exploits the fact that acoustic pressure waves propagating within the water environment cause vibrations on an air-water interface and the particle velocities can be optically detected by observing the amplitude or phase characteristics of the reflected optical beam which is emanated from a laser interferometer. This paper studies an interesting phenomenon observed from our optic-acoustic remote sensing experiments. In the hydrodynamic surface condition, the air-water interface is in motion, thus the moving water surface is a strong interference source. We design some adaptive filters such as the least mean squares (LMS), recursive least squares (RLS) and Kalman filter to suppress this interference. The designed filters are applied to the experiment raw data, and the processing results show an obviously improved signal-to-interference ratio.