【作者】 李强；

【导师】 井文才；

【作者基本信息】 天津大学 ， 光学工程， 2005， 硕士

【摘要】 分布式偏振耦合测试仪(Distributed Polarization Coupling Analyzer--DPCA)是一种基于白光干涉原理工作的测量保偏光纤绕组中寄生偏振耦合点位置及耦合强度的系统,该系统的成功开发将在降低光纤陀螺开发成本以及提高光纤陀螺精度方面有重要应用。本文在实现DPCA测试系统的数据采集的基础上将小波分析应用于DPCA系统的信号处理。本文主要工作:实现了DPCA数据采集卡的设计及数据采集,建立了信号处理模型。将小波分析应用于DPCA系统的信号处理:应用Morlet小波实现了信号包络提取;应用Daubechies小波对信号滤波,在保证信号相似性的前提下,最大限度的提高了信噪比增益。利用Matlab和VC++混合编程实现了DPCA数据处理软件。分析了光能对DPCA测试结果信噪比的影响以及滤波阈值变化对信号去噪效果的影响,确定了光源能量的最佳范围,验证了小波分析应用于DPCA信号滤波的正确性。主要创新点:根据保偏光纤模式耦合理论建立了DPCA信号处理模型。将小波分析应用于DPCA信号处理,获得了更加光滑的信号包络以及更好的信号分辨率。利用Matlab和VC++混合编程,缩短了DPCA干涉图的信号处理时间。更多还原

【Abstract】 Distributed polarization coupling analyzer (DPCA) is a white-lightinterference system capable of detecting the location and the intensity of thepolarization coupling points in the polarization maintained fiber (PMF). Itcan be used to improve the precision of fiber-optic gyroscope (FOG) andreduce the system cost. In this paper, wavelet analysis method is adopted toprocess the signals sampled by the DPCA.Main Works: Implemented with FPGA (Field Programmable Gate Array), the DPCAdata-sampling cards were designed to realize the data sampling. Themodel of DPCA signal processing was successfully built. Wavelet analysis was adopted to realize the signal processing of DPCA:Signal envelope extracting and signal filtering were successfullyrealized with Morlet wavelet and Daubechies wavelet respectively;Signal similarity was assured, and simultaneously the gain of SNR washighly improved after filter. The signal processing software was designed using Matlab and VC++. The influences of the light intensity and the variation of denoisingthreshold on denoising effects were both analyzed. The range of thelight power was confirmed by experiments. Moreover, the theory ofDPCA signal processing with Wavelet analysis was validated.Innovations: The model of DPCA signal processing was established based on thePMF mode coupling theory. Wavelet analysis was introduced to DPCA signal processing. Moresmooth signal envelopes and better signal resolution were achieved.With Matlab and VC++ programming, the DPCA signal processing timewas reduced.更多还原