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The Deep Space Atomic Clock (DSAC), a NASA Technology Demonstration Mission, was launched into low-Earth orbit on June 25, 2019 as a hosted payload aboard General Atomics’ Orbital Test Bed (OTB) spacecraft. The DSAC mission has been conducting a two-year demonstration of a mercury ion atomic clock to characterize its space-based performance and to validate its utility for deep space navigation and radio science. Analysis of the collected data using JPL’s GIPSY-OASIS software has shown DSAC’s AD at one-day to be near 310-15; much better than required AD of 210-14. Such low spacecraft clock errors will enable one-way radiometric tracking data with precision equivalent to or better than current-day two way tracking data, allowing a shift to a more efficient and flexible one-way deep space navigation architecture. To verify this, an analog deep space navigation experiment was performed using JPL’s operational navigation software (Monte). The experiment recovered orbit solutions with reduced data sets and geometric variations that are more representative of deep space missions, and showed that orbit determination using DSAC derived data is on par with more traditional two-way datatypes. As a technology demonstrator, DSAC’s development focus has been on maturing the mercury ion trap clock technology rather than achieving the smallest size, weight, and power (SWaP). Over the course of DSAC’s development the project has identified numerous improvements that could be made to significantly reduce SWaP for DSAC’s next version. Indeed, DSAC-2 was recently selected by NASA for further demonstration on the VERITAS mission to Venus. This work will review the DSAC technology, mission, and results from its two-year mission.

Recent advances at JPL in experimentation and design for LISA interferometry include the demonstration of Time Delay Interferometry using electronically separated end stations, a new arm-locking design with improved gain and stability, and progress in flight readiness of digital and analog electronics for phase measurements., Comment: 11 pages, 9 figures, LISA 8 Symposium, Stanford University, 2010

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This paper will describe the TriG architecture, and how the new features will benefit the next-generation of global network instruments, as well as current test results.

TriG is the next generation NASA scalable space GNSS Science Receiver. It will track all GNSS and additional signals (i.e. GPS, GLONASS, Galileo, Compass and Doris). Scalable 3U architecture and fully software and firmware recofigurable, enabling optimization to meet specific mission requirements. TriG GNSS EM is currently undergoing testing and is expected to complete full performance testing later this year.

The L2C signal is a great step forward for civil applications of GPS, enabling high-accuracy dual-frequency measurements. Engineers from the Jet Propulsion Laboratory and ITT teamed to reprogram FPGA firmware and add tracking software on an orbiting receiver to track the new GPS L2C signal from SAC-C. SAC-C is an Argentinean science satellite and was launched in November 2000 with a BlackJack GPS receiver. This is a dual-frequency digital receiver with 48 tracking channels and four antennas. On SAC-C, it provides precise orbits, atmospheric occultation data, tests of GPS surface reflections, and serves as an orbiting test bed for new GPS development such as the L2C tracking reported here.

ROCSat-3's primary instrument is the GPS Occultation Receiver (GOX) and is based on the Jet Propulsion Laboratory's (JPL) proven BlackJack GPS Receiver. The COSMIC GOX receivers will demonstrate an important new operational data type for near-real-time assimilation into weather models by providing over 2500 atmospheric profiles per day with a global distribution.

Two sections of an introductory educational psychology course given at the University of Akron were restructured using some nontraditional elements. Student evalutions of the course's content and structure and student achievement measures were used to analyze the effectiveness of the changes. The statistical analyses are detailed. The results are used to design clusters of elements to be used as predictors of academic success, which can in turn be used to personalize instruction in the course. Appended to the description of the study are some of the statistical results and the questionnaire given to the students. (MSE)