Characterizing DSN System Frequency Stability with Spacecraft Tracking Data

This paper describes a recent effort in characterizing frequency stability performance of the ground system in the National Aeronautics and Space Administration (NASA) Deep Space Network (DSN). Unlike the traditional approach where performance is obtained from special calibration sessions that are time consuming and require manual setup, the new method taps into the daily spacecraft tracking data. This method significantly increases the amount of data available for analysis, roughly by two orders of magnitude; making it possible to conduct trend analysis with reasonable confidence. To make it possible to process the continual stream of daily incoming data without much effort and to quickly understand the results, the processing needs to be automated and the data summarized at high level. Comparison of observed data against expected performance is also given.