Signals of opportunity (SoOp) reflectometry (SoOp-R) is a maturing field for geophysical remote sensing as evidenced by the growing number of airborne and spaceborne experiments. As this approach receives more attention, it is worth analyzing SoOp-R's capabilities to retrieve subsurface soil moisture (SM) by leveraging communication and navigation satellite transmitters. In this research, the Cramer–Rao lower bound (CRLB) is used to identify the effects of variable SoOp-R parameters on the best achievable estimation error for root-zone soil moisture (RZSM). This study investigates the use of multiple frequency, polarization, and incidence angle measurement configurations on a two-layered dielectric profile. The results also detail the effects of variable SM conditions on the capability of SoOp-R systems to predict subsurface SM. The most prevalent observation is the importance of using at least two frequencies to limit uncertainties from subsurface SM estimates. If at least two frequencies are used, the CRLB of a profile is retrievable within the root-zone depending on the surface SM content as well as the number of independent measurements of the profile. For a depth of 30 cm, it is observed that a CRLB corresponding to 4% RZSM estimation accuracy is achievable with as few as two dual-frequency-based SoOp-R measurements. For this depth, increasing number of measurements provided by polarization and incidence angle allow for sensing of increasingly wet SM profile structures. This study, overall, details a methodology by which SoOp-R receiver system can be designed to achieve a desired CRLB using a tradeoff study between the available measurements and SM profile.

中文翻译：

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基于 SoOp-R 的根区土壤水分遥感的 Cramer-Rao 下界

机会信号 (SoOp) 反射计 (SoOp-R) 是地球物理遥感的成熟领域，越来越多的机载和星载实验证明了这一点。随着这种方法受到越来越多的关注，值得分析 SoOp-R 通过利用通信和导航卫星发射机检索地下土壤水分 (SM) 的能力。在本研究中，Cramer-Rao 下限 (CRLB) 用于确定可变 SoOp-R 参数对根区土壤水分 (RZSM) 的最佳可实现估计误差的影响。本研究调查了在两层电介质剖面上使用多频率、极化和入射角测量配置。结果还详细说明了可变 SM 条件对 SoOp-R 系统预测地下 SM 能力的影响。最普遍的观察是使用至少两个频率来限制地下 SM 估计的不确定性的重要性。如果使用至少两个频率，则根据表面 SM 含量以及轮廓的独立测量次数，可以在根区内检索轮廓的 CRLB。对于 30 厘米的深度，据观察，只需进行两次基于双频的 SoOp-R 测量即可实现对应于 4% RZSM 估计精度的 CRLB。对于这个深度，越来越多的由偏振和入射角提供的测量允许检测越来越湿的 SM 轮廓结构。总的来说，这项研究详细介绍了一种方法，通过该方法可以使用可用测量和 SM 配置文件之间的权衡研究来设计 SoOp-R 接收器系统以实现所需的 CRLB。