J1.4 The CubeSat Radiometer Radio Frequency Interference Technology (CubeRRT) Validation Mission Operations and Development of Software Simulation Tools for Future Resource Constrained Observing Systems

Monday, 13 January 2020: 9:15 AM
251 (Boston Convention and Exhibition Center)
Chris Ball, Ohio State Univ., Columbus, OH; and M. Abu Shattal, J. DeLong, R. Linnabary, C. McKelvey, G. Smith, A. O'Brien, J. Johnson, S. Misra, J. R. Piepmeier, D. Laczkowski, and N. Monahan

The CubeSat Radiometer Radio Frequency Interference Technology Validation (CubeRRT) mission developed and deployed into orbit a 6U CubeSat to demonstrate radio frequency interference (RFI) mitigation technologies in support of future microwave radiometry missions. Microwave radiometers observe Earth’s natural thermal emissions and make important contributions to observing Earth’s atmosphere, oceans, and land surfaces including products such as atmospheric water vapor, temperature profiles, sea surface wind speed and direction, soil moisture, sea ice properties, and other products. Microwave radiometer measurements below 40 GHz exhibit increasing man-made RFI, having a degenerative impact on these important geophysical retrievals and potentially degrading the capabilities of future radiometer missions. To address the growing RFI problem, the CubeRRT mission was selected under ESTO’s In-space Validation of Earth Science Technologies (InVEST) program to demonstrate on-board, real-time RFI processing from 6-40 GHz. This talk summarizes CubeRRT operations, collected data, and lessons learned from over a year in orbit. The CubeRRT mission also serves as a valuable case study in the development of simulation tools for next generation, resource constrained small satellite observing systems. With funding from ESTO’s Advanced Information Systems Technology (AIST) program and building upon the lessons learned from the CubeRRT mission, the authors have produced the Simulation Toolset for Adaptive Remote Sensing (STARS) software library to support future Observing System Simulation Experiments for autonomous satellite-based Earth remote sensing missions. Specifically, STARS models and optimizes the performance of next generation adaptive sensors, resource constrained platforms (such as CubeSats), and constellations of collaborative satellites.
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