无人机载探地雷达数据消除地面影响的正反向延拓方法研究
Forward and Reverse Continuation of Unmanned Aerial Vehicles (UAV) Ground-Penetrating Radar (GPR) Data to Eliminate Ground Surface’s Effect
DOI: 10.12677/CSA.2017.71004, PDF, HTML, XML, 下载: 1,794  浏览: 4,076  国家科技经费支持
作者: 鲁兴林, 刘雅琼, 宋 翱, 王玉洁, 钱荣毅*:中国地质大学(北京),“地下信息探测技术与仪器”教育部重点实验室,北京
关键词: 无人机载探地雷达多次波正反向延拓逆时偏移Unmanned Aerial Vehicles Ground-Penetrating Radar Multiple Wave Forward Continuation and Reverse Continuation Reverse Time Migration
摘要: 随着全球气候的变化,青藏高原冻土区热融湖塘的大小、形状和冰层厚度在区域内存在明显的变化,热融湖塘的变化与区域内富冰冻土层和气候变化息息相关。高原区热融湖塘分布广,覆盖面大,现有的地面探地雷达技术很难快速准确地监测冰层厚度的变化。机载探地雷达能在复杂的地形区域实现快速、重复监测,但由于强反射地表面产生的多次波的干扰,严重影响冰层厚度的识别。本篇文章基于机载探地雷达数据中普遍存在地表面问题,应用正反向延拓方法压制地表面引起的多次波,消除地表面对地下构造识别的影响。通过比较正反向延拓前后的零偏移距逆时偏移剖面,论证了正反向延拓方法在消除地表面影响方面的优势;应用不同飞行高度的模型分析正反向延拓方法对不同飞行高度机载探地雷达数据的效果。零偏移距逆时偏移成像结果显示,正反向延拓方法能有效地去除地表面的影响,但随着飞行高度的增加,偏移成像的分辨率会降低。模型数据的正演模拟和零偏移距逆时偏移成像分析认为,正反向延拓方法能有效地压制多次波干扰,清晰地反映平界面特征,但对倾斜界面成像较差。延拓计算和飞行高度会影响偏移成像的分辨率,不利于高分辨率探测,还需要进一步改善。
Abstract: The size, shape, and ice thickness of thermokarst lakes have obviously changed in the Tibetan Plateau permafrost region due to global climate changing. These changes have strong correlation with ice-permafrost and climate changing. Since thermokarst lakes have widely appeared and covered large area in Tibetan Plateau, it’s difficult to quickly monitor the change of ice thickness using ground-penetrating radar (GPR). Unmanned aerial vehicles (UAV) GPR can adapt to the complex area and realize the quickly and more times monitor, however, the ground surface as a strong reflection interface can generate the multiple waves, which will seriously impact on identification of ice thickness. In this paper, the researchers used the forward and reverse continuation method to eliminate the ground surface’s effect based on the widely appeared the ground surface’s effect for the UAV GPR data. Through comparison with the forward continuation and reverse continuation (FCRC) of zero-offset reverse time migration (RTM) and raw zero-offset RTM profile, the researchers demonstrate the FCRC method can eliminate the ground surface’s effect. From the zero-offset RTM profile of different elevation’s model, the researchers analyze the effectiveness of FCRC method for UAV GPR data with different flight altitude. The results of zero-offset RTM imaging show that the FCRC method can effectively eliminate the surface’s effect, however, with the increase of flight altitude, the resolution of migration imaging will decrease. From the result of forward modeling and zero-offset RTM imaging for models data, the researchers consider that the FCRC method can effectively eliminate multiple waves, better reflect the flat interface information, but cannot image the dip interface. The process of FCRC and flight altitude can decrease the UAV GPR resolution which will go against the high resolution detection; we still need make new progress for the process of UAV GPR data.
文章引用:鲁兴林, 刘雅琼, 宋翱, 王玉洁, 钱荣毅. 无人机载探地雷达数据消除地面影响的正反向延拓方法研究[J]. 计算机科学与应用, 2017, 7(1): 27-35. http://dx.doi.org/10.12677/CSA.2017.71004

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