The performance of an atmospheric water vapor radio path delay measurement and correction is reported using observations of the Juno Spacecraft during gravity field mapping of Jupiter. The Juno Gravity Science instrument measures the Doppler shift on the radio signals between the Juno spacecraft and the Earth‐based observing stations of NASA's Deep Space Network (DSN) during times of closest approach to Jupiter in order to map Jupiter's gravity field. These Doppler measurements are affected by noise sources between the spacecraft and DSN which include charged particles plasma and Earth's troposphere. A pair of redundant Advanced Water Vapor Radiometers (AWVR) co‐located at the DSN's DSS‐25 antenna in Goldstone, CA measure the brightness temperatures at the 22.2, 23.8 and 31.4 GHz spectral lines for water vapor content in Earth's atmosphere. The measurements of water vapor content are reduced into a measurement of radio path delay, which provides high‐precision calibrations of tropospheric noise on the radio links. Analyses of AWVR measurements show that spacecraft tracking errors, after removing other measurable errors from charged particles, are reduced by 46% on average and by as much as 70%, depending on local weather conditions near the Goldstone site.
NASA's Deep Space Network currently bas a ranging system that uses a sequence of square wave tones to determine spacecraft distance. This ranging system correlates tones received from the spacecraft with those it transmitted. The phase shift that maximizes the correlation value is then related to the round trip light time distance. A new ranging system is being developed that can be configured to use sequential square wave tones or to use repeating pseudonoise tones. This allows more flexibility and possibly better performance.The tradeoffs between the two types of ranging are presented. A detailed derivation of the ranging performance as a function of configuration, signal strength, and other variables is given. The ranging performance for the two ranging types is compared. A configuration for pseudo-noise ranging that provides better performance is provided. Operational issues and simplifications resulting from using pseudo-noise ranging are also discussed.
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