半导体激光云高仪小波去噪算法研究

Wavelet Denoising Algorithm of Laser Diode Ceilometer

针对半导体激光云高仪回波信号所含噪声的特点,提出并详细论述了一种能够对半导体激光云高仪回波信号进行有效消噪的小波自适应阈值方法。为了验证该方法的有效性,对包含高斯白噪声的模拟信号进行了仿真消噪,并对半导体激光云高测量系统实际探测得到的大气回波信号进行了消噪处理.同时,将该方法与小波模极大值消噪、小波分解重构、小波默认阈值的消噪效果进行了对比分析。仿真和实验结果表明,小波自适应阈值方法能够有效降低半导体激光云高仪回波信号中所含噪声,并且其消噪效果明显优于另外三种小波分析方法.

According to the characteristics of ceilometer return noise,an effective denoising method of wavelet adaptive threshold is presented to reduce ceilometer return noise.To verify the feasibility of the denoising method,some numerical simulations are carried out to reduce the Gauss white noise of the simulated signal, and also,the laser diode ceilometer returns contaminated by noise are denoised by the method.Moreover, the comparisons among the wavelet adaptive threshold,wavelet modulus maxima,wavelet decomposing and recomposing,and the wavelet default threshold are performed.Experiment results show that the method of the wavelet adaptive threshold is capable of effectively reducing laser diode ceilometer return noise and the denoising effect is better than other three methods.