A Python-based tool for constructing observables from the DSN’s closed-loop archival tracking data files

Radio science data collected from NASA’s Deep Space Networks (DSNs) are made available in various formats through Planetary Data System (PDS). The majority of these packed 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 files (ATDFs), produce Doppler and range observables, write an ASCII table along with ancillary information. ATDFs primitive radio products limited documentation. Early 2000s, DSN deprecated ATDF replaced it Tracking Navigation Service Files (TNF) keep up evolution system. Most processing software (e.g., orbit determination software) cannot use directly, thus limiting utilization data. As such, vast historical have not yet been processed modern our improved understanding solar preprocessing presented paper makes possible revisit such using techniques conduct crucial experiments.