KACST sets a road map for the miniaturized distributed space system for sciences and exploration in the future
King Abdulaziz City for Science and Technology (KACST) has set a road map for the Miniaturized Distributed Space System (MDSS) for sciences and exploration, to develop technology in the future on gradual stages in partnership with international universities and research centers including Stanford University and the Department of Aeronautics and Space Administration (NASA) within a strategic map that extends up to 2022.
This system comprehends a number of scientific experiments launched abroad Saudi Satellites, The first experiment of which, the Ultra-Violet Light Emitting Diode (UV LED) 2014, was successfully prepared and launched abroad the Saudi satellite (Saudi Sat 4) This experiment is considered a trailblazer experiment to control the charge buildup on the gravitational reference sensor (GRS), guidance control proof mass module using low-voltage, ultraviolet frequency LEDs. The remarkable success of this promising experiment led to adopting using Saudi Sat 4 platform in all future missions of the system.
The future plans of the MDSS comprises other experiments as well such as the Modular Gravitational Reference Sensor (MGRS- 2019) which is an aeronomy experiment performed in a 3-axis, small satellite GRS. This mission requires precise drag-free control and very accurate orbit determination. Technology is currently under development as part of the collaborating between KACST, Stanford and NASA. The experiment will be integrated as a payload of a Saudi Sat reconfigurable bus.
KACST would also launch the experiment of mSTAR (2021) that will be launched on a Saudi Sat 4 based bus that have precise thermal control to achieve the target accuracy of the experiment. This experiment is Kennedy-Thorndike special relativity one in a small satellite GRS, comparing the length of a rod measured by a laser beam to the rate of a ticking clock. This mission is a scientific and technological cooperation between KACST, DRL, NASA and Stanford.
In 2017, KACST will launch the mGRACE (2023) experiment which is a mini Gravity Recovery and Climate Experiment one. It is a geodesy experiment using two small satellites, each equipped with a telescope and laser interferometer pointing at the telescope and laser interferometer on the opposing satellite.
Within the MDSS, KACST will launch mDEOS (2025) experiment which is Miniaturized Distributed Earth Orbiting System that is composed of three or more miniaturized for motion flying distributed LEO satellites. KACST will also launch the mLISA (2027) (Laser Interferometer Space Antenna) which is an Earth-orbiting version of the original LISA experiment, with three identical GRS satellites, spaced 1 million kilometers apart at the corners of an equilateral triangle, with each satellite having a pair of telescopes and laser interferometers, one focused on the satellite ahead and the other focused on the satellite behind.
These plans come to complement the KACST’s extensive work with its international partners whereas a research team from KACST has completed work on the project of the Gravity Probe-B (GP-B) that was designed to measure two key predictions of Einstein’s general theory of relativity by monitoring the orientations of ultra-sensitive gyroscopes relative to a distant guide star. The two key predictions of this project are the geodetic effect (the amount by which the Earth warps the local space-time in which it resides) and the frame-dragging effect (the amount by which the rotating Earth drags its local space-time around with it.)
Within the framework of this project a team from KACST participated in the latest phases of data analysis with contributions that expedited the verification of the model. In particular, KACST team was involved in truth modeling, thermal modeling, parallel processing and data fusion and visualization. The experimental results are in agreement with Einstein’s theoretical predictions of the geodetic effect (0.28% margin of error) and the frame-dragging effect (19% margin of error).