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小波去噪在成像激光雷达仿真信号中的应用

Application of Wavelet Noise Reduction for Simulated Signals of Imaging Lidar

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摘要

通过设计成像激光雷达的各种参数, 结合一种大气模式模拟得到了一维激光雷达信号, 并根据高斯分布的特点和实测的光束宽度还原了二维光柱图像。对该原始图像加入不同强度的高斯白噪声和一定强度的平均背景,生成类似于成像激光雷达实测信号的染噪图像。使用二维小波变换的方法对染噪的激光雷达光柱图像进行去噪, 获得了较好的去噪效果。去噪后的回波信号与原始回波信号之间的相对误差均在±12%以内。利用去噪的激光雷达信号反演出气溶胶的消光系数。将反演出的气溶胶消光系数与输入的大气模式下气溶胶的消光系数进行对比, 结果表明二者的相对误差在±15%之内, 并且总体变化趋势一致, 由此验证了所提出的利用小波对激光雷达染噪图像进行去噪的可行性。

Abstract

One-dimensional lidar signal is achieved by the simulation combining an atmospheric model and the design of parameters of imaging lidar. A two-dimensional light cross image is recovered based on measured beam widths and features of the Gauss distribution. The noised images similar to the real signals detected by imaging lidar are obtained when we add Gauss white noise with different intensities and certain intensity of average background to the original image. The good de-noising effect is obtained when we denoise the noised lidar light cross image by the two-dimensional wavelet transform method. The relative error between echo signal after denoising and original echo signal is in the range of ±12%. The extinction coefficients of aerosol are retrieved with de-noising lidar signals. Comparing extinction coefficients under the input aerosol atmospheric model with retrieved extinction coefficients of aerosol, we find that the relative error is in the range of ±15% and their variation trends are coincident, which verifies the feasibility of the proposed method using wavelet transform in the de-noising for the noised images of lidar.

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中图分类号:P427.1

DOI:10.3788/lop54.090102

所属栏目:大气光学与海洋光学

基金项目:国家自然科学基金(41405014)

收稿日期:2017-03-06

修改稿日期:2017-04-07

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孙国栋:中国科学院安徽光学精密机械研究所大气成分与光学重点实验室, 安徽 合肥 230031中国科学技术大学研究生院科学岛分院, 安徽 合肥 230026
秦来安:中国科学院安徽光学精密机械研究所大气成分与光学重点实验室, 安徽 合肥 230031
程知:中国科学院安徽光学精密机械研究所大气成分与光学重点实验室, 安徽 合肥 230031中国科学技术大学研究生院科学岛分院, 安徽 合肥 230026
侯再红:中国科学院安徽光学精密机械研究所大气成分与光学重点实验室, 安徽 合肥 230031

联系人作者:孙国栋(gds0525@163.com)

备注:孙国栋(1991-), 男, 博士研究生, 主要从事激光雷达方面的研究。

【1】Mao J D. Noise reduction for lidar returns using local threshold wavelet analysis[J]. Optical and Quantum Electronics, 202, 43(1/2/3/4/5): 59-68.

【2】Han Y, Westwater E R, Ferrare R A. Applications of Kalman filtering to derive water vapor profiles from Raman lidar and microwave radiometers[J]. Journal of Atmospheric and Oceanic Technology, 1997, 14(3): 480-487.

【3】Wu S H, Liu Z S, Liu B Y. Enhancement of lidar backscatters signal-to-noise ratio using empirical mode decomposition method[J]. Optics Communications, 2006, 267(1): 137-144.

【4】Fang H T, Huang D S. Noise reduction in lidar signal based on discrete wavelet transform[J]. Optics Communications, 2004, 233(1): 67-76.

【5】Fang H T, Huang D S, Wu Y H. Antinoise approximation of the lidar signal with wavelet neural networks[J]. Applied Optics, 2005, 44(6): 1077-1083.

【6】Yin S R, Wang W R. Denoising lidar signal by combining wavelet improved threshold with wavelet domain spatial filtering[J]. Chinese Optics Letters, 2006, 4(12): 694-696.

【7】Li Qingzhong, Liu Qing. Adaptive enhancement algorithm for low illumination images based on wavelet transform[J]. Chinese J Lasers, 2015, 42(2): 0209001.
李庆忠, 刘 清. 基于小波变换的低照度图像自适应增强算法[J]. 中国激光, 2015, 42(2): 0209001.

【8】Mao Jiandong, Hua Dengxin, Wang Yufeng, et al. Noise reduction in lidar signal based on wavelet packet analysis[J]. Chinese J Lasers, 2011, 38(2): 0209001.
毛建东, 华灯鑫, 王玉峰, 等. 基于小波包分析的激光雷达信号消噪算法的研究[J]. 中国激光, 2011, 38(2): 0209001.

【9】Barnes J E, Bronner S, Beck R, et al. Boundary layer scattering measurements with a charge-coupled device camera lidar[J]. Applied Optics, 2003, 42(15): 2647-2652.

【10】Mei L, Brydegaard M. Continuous-wave differential absorption lidar[J]. Laser & Photonics Reviews, 2015, 9(6): 629-636.

【11】Liu Houtong, Chen Liangfu, Su Lin. Theoretical research of Fernald forward integration method for aerosol backscatter coefficient inversion of airborne atmosphere detecting lidar[J]. Acta Physica Sinica, 2011, 60(6): 064204.
刘厚通, 陈良富, 苏 林. Fernald 前向积分用于机载激光雷达气溶胶后向散射系数反演的理论研究[J]. 物理学报, 2011, 60(6): 064204.

【12】Bao Qing, He Junliang, Zha Yong. Retrieval of aerosol extinction coefficient and optical thickness using varied lidar ratio[J]. Acta Optica Sinica, 2015, 35(3): 0301002.
包 青, 贺军亮, 查 勇. 基于动态雷达比的气溶胶消光系数及光学厚度反演[J]. 光学学报, 2015, 35(3): 0301002.

【13】Cai Dunhu. The research on the performance of manifold wavelet basis in image denoising[D]. Wuhan: Wuhan University, 2003: 12-13.
蔡敦虎. 多种小波基的图像去噪性能研究[D]. 武汉: 武汉大学, 2003: 12-13.

【14】Chen Tao, Wu Decheng, Liu Bo, et al. A new method for determining aerosol backscatter coefficient boundary value in the lower troposphere[J]. Acta Optica Sinica, 2010, 30(6): 1531-1536.
陈 涛, 吴德成, 刘 博, 等. 低层大气中确定气溶胶后向散射系数边界值的新方法[J]. 光学学报, 2010, 30(6): 1531-1536.

【15】Fernald F G. Analysis of atmospheric lidar observations: Some comments[J]. Applied Optics, 1984, 23(5): 652-653.

引用该论文

Sun Guodong,Qin Laian,Cheng Zhi,Hou Zaihong. Application of Wavelet Noise Reduction for Simulated Signals of Imaging Lidar[J]. Laser & Optoelectronics Progress, 2017, 54(9): 090102

孙国栋,秦来安,程知,侯再红. 小波去噪在成像激光雷达仿真信号中的应用[J]. 激光与光电子学进展, 2017, 54(9): 090102

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