首页> 外文期刊>IEEE Transactions on Geoscience and Remote Sensing >Validation of Near-Field Ground-Penetrating Radar Modeling Using Full-Wave Inversion for Soil Moisture Estimation
【24h】

Validation of Near-Field Ground-Penetrating Radar Modeling Using Full-Wave Inversion for Soil Moisture Estimation

机译:基于全波反演的土壤水分估算近场探地雷达模型的验证

获取原文
获取原文并翻译 | 示例

摘要

We present validation results of a new ground-penetrating radar (GPR) near-field model for determining the electrical properties and correlated water content of a sand using both frequency- and time-domain radars. The radar antennas are intrinsically characterized using an equivalent set of infinitesimal source/field points and characteristic functions of antennas, which were determined using measurements with the antenna at different distances from a copper plane. The antenna radiation was modeled using six source and field points, which was found to be a good compromise between high modeling accuracy and computing efficiency. We validated our model by inverting GPR data to predict the water content of a sand layer subject to seven levels of saturation. A soil dielectric mixing model was integrated into the full-wave GPR inverse modeling to directly estimate the water content and to account for the frequency dependence of the electrical properties. Although the quality of the fit slightly decreased as the antenna approached the sand surface, the results showed a close agreement between measured and modeled data, resulting in accurate estimation of the water content. The average errors of all water content estimates were 0.012 $hbox{cm}^{3}/hbox{cm}^{3}$ for the frequency domain and 0.016 $hbox{cm}^{3}/hbox{cm}^{3}$ for the time-domain GPR. However, the accuracy reduced when the sand became wet. By performing numerical simulations, we found that it is due to the vertical heterogeneity of soil moisture under the effect of the hydrostatic pressure. We also showed that the GPR inversion with the multilayered soil model could account for this heterogeneity and improved the agreement between the modeled and measured GPR data as well as the accuracy of soil moisture estimation. As for the frequency dependence of the electrical properties- in the frequency ranges of both GPR systems, while the dielectric permittivity was approximately constant, the apparent conductivity exponentially increased with increasing frequency. The success of the calibration and validation in laboratory conditions demonstrates a great potential for practical applications of the radar model, notably for the digital soil mapping and nondestructive testing of materials.
机译:我们提出了一种新的探地雷达(GPR)近场模型的验证结果,该模型可使用频域和时域雷达确定沙的电学特性和相关的含水量。雷达天线通过使用一组等效的无穷小源极/场点和天线的特征函数进行固有表征,这些特征是通过使用天线在距铜平面不同距离处的测量确定的。使用六个源点和场点对天线辐射进行建模,发现在高建模精度和计算效率之间取得了很好的折衷。我们通过反演GPR数据来预测砂层含水量受七个饱和度的影响来验证模型。将土壤电介质混合模型集成到全波GPR反演模型中,可以直接估计水含量并考虑电性能的频率依赖性。尽管随着天线接近沙子表面,拟合质量会略有下降,但结果表明,实测数据和建模数据之间存在紧密的一致性,从而可以准确估算出水含量。所有水含量估算值的平均误差在频域为0.012 $ hbox {cm} ^ {3} / hbox {cm} ^ {3} $,在频域为0.016 $ hbox {cm} ^ {3} / hbox {cm} ^ {3} $用于时域GPR。但是,当沙子变湿时,精度会降低。通过数值模拟,我们发现这是由于静水压力作用下土壤水分的垂直非均质性。我们还表明,利用多层土壤模型进行的GPR反演可以解决这种异质性,并改善了模型化GPR数据和实测GPR数据之间的一致性以及土壤水分估算的准确性。至于电性能的频率依赖性-在两个GPR系统的频率范围内,虽然介电常数近似恒定,但表观电导率随频率增加而呈指数增长。实验室条件下校准和验证的成功展示了雷达模型在实际应用中的巨大潜力,尤其是用于数字土壤制图和材料的无损检测。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号