Literature DB >> 33154788

Cramer-Rao Lower Bound for SoOp-R-Based Root-Zone Soil Moisture Remote Sensing.

Dylan Ray Boyd1, Ali C Gurbuz1, Mehmet Kurum1, James L Garrison2, Benjamin R Nold2, Jeffrey R Piepmeier3, Manuel Vega3, Rajat Bindlish3.   

Abstract

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 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 2 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 trade-off study between the available measurements and SM profile.

Entities:  

Keywords:  Cramer-Rao Lower Bound; Signals of Opportunity (SoOp); bistatic; multilayer; reflectometry; root-zone; soil moisture; specular

Year:  2020        PMID: 33154788      PMCID: PMC7641095          DOI: 10.1109/jstars.2020.3029158

Source DB:  PubMed          Journal:  IEEE J Sel Top Appl Earth Obs Remote Sens        ISSN: 1939-1404            Impact factor:   3.784


  2 in total

1.  Response of GNSS-R on Dynamic Vegetated Terrain Conditions.

Authors:  Orhan Eroglu; Mehmet Kurum; John Ball
Journal:  IEEE J Sel Top Appl Earth Obs Remote Sens       Date:  2019-05       Impact factor: 3.784

2.  Derivation of the Cramér-Rao Bound in the GNSS-Reflectometry Context for Static, Ground-Based Receivers in Scenarios with Coherent Reflection.

Authors:  Miguel Angel Ribot; Cyril Botteron; Pierre-André Farine
Journal:  Sensors (Basel)       Date:  2016-12-05       Impact factor: 3.576

  2 in total

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