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\begin{document}

\title{A Python-based tool for constructing observables from the DSN's
closed-loop archival tracking data files}



\author[1]{Ashok Verma}%
\affil[1]{University of California Los Angeles}%


\vspace{-1em}



  
  \date{May 30, 2024}


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\begin{abstract}
Radio science data collected from NASA's Deep Space Networks (DSNs) are
made available in various formats through NASA's Planetary Data System
(PDS). The majority of these data are packed in complex formats, making
them inaccessible to users without specialized knowledge. In this paper,
we present a Python-based tool that can preprocess the closed-loop
archival tracking data files (ATDFs), produce Doppler and range
observables, and write them in an ASCII table along with ancillary
information. ATDFs are the earliest closed-loop radio science products
with limited available documentation. Most data processing software
(e.g., orbit determination software) cannot use them directly, thus
limiting the utilization of these data. As such, the vast majority of
historical closed-loop radio science data have not yet been processed
with modern software and with our improved understanding of the solar
system. The preprocessing tool presented in this paper makes it possible
to revisit such historical data using modern techniques and software to
conduct crucial radio science experiments.%
\end{abstract}%



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