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\begin{document}

\title{Remote Sensing of the water cycle using Signals of Opportunity:
challenges and opportunities}



\author[1]{James Garrison}%
\author[2]{Manuel Vega}%
\author[3]{Rashmi Shah}%
\author[4]{Rajat Bindlish}%
\author[5]{Mehmet Kurum}%
\author[1]{Benjamin Nold}%
\author[1]{Seho Kim}%
\affil[1]{Purdue University}%
\affil[2]{NASA Goddard Space Flight Center}%
\affil[3]{Jet Propulsion Laboratory}%
\affil[4]{Goddard Earth Sciences Technology and Research}%
\affil[5]{Mississippi State University}%


\vspace{-1em}



  
  \date{May 21, 2024}


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\begin{abstract}
Recent proof-of-concept experiments have demonstrated the potential
utility of Signals of Opportunity (SoOp) in remote sensing. SoOp methods
involve the re-use of existing satellite transmissions as sources in
bistatic radar, applying fundamental physical principles to estimate
surface and scattered medium properties from reflectivity and phase
observables in the reflected signal. Through utilizing signals intended
for communications, SoOp methods can make these observables using
frequencies that are not allocated or protected for scientific use. Two
promising applications in hydrology have been studied: Sub-canopy
root-zone soil moisture (RZSM) using satellite communications signals
below 500 MHz and snow water equivalent (SWE) retrieval from the
observed phase different through propagation through the snow layer.
Signals of Opportunity P-band Investigation (SNOOPI) is a NASA Cubesat
technology demonstration mission to test forward scattering models and
validate a prototype instrument for SoOp reflectometry in 250-380 MHz
range. Contribution to the panel discussion will focus on the expected
contributions of the SoOp techniques validated in the SNOOPI mission and
the existing challenges in the full utilization of SoOp methods for both
RZSM and SWE remote sensing. Multiple frequencies are required in order
to solve the inverse problem and estimating a sub-surface profile. In
the case of SoOp, this may require combining observations with diverse
geometry due to the different orbits of the potential sources. This
presents new challenges in the development of retrieval algorithms and
may possibly require the integration of additional data sources. Another
important challenge for SWE retrieval is the need for repetitive
coverage to extract phase differences between subsequent passes, coupled
with orbit determination for the non-cooperative sources. In contrast to
GNSS reflectometry (in which high-precision orbits are publicly
available for use in positioning), communication satellite orbits are
not known to the required meter-level accuracy. Even geostationary
sources frequently have a small inclination which results in motion
relative to the surface of the Earth. Finally, antenna calibration is a
substantial contribution to the error budget.%
\end{abstract}%



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