Search

The majority of planetary missions return only one thing: data. The volume of data returned from distant planets is typically minuscule compared to Earth-based investigations, volume decreasing further from more distant solar system missions. Meanwhile, the data produced by planetary science instruments continue to grow along with mission ambitions. Moreover, the time required for decisional data to reach science and operations teams on Earth, and for commands to be sent, also increases with distance. To maximize the value of each bit, within these mission time and volume constraints, instruments need to be selective about what they send back to Earth. We envision instruments that analyze science data onboard, such that they can adjust and tune themselves, select the next operations to be run without requiring ground-in-the-loop, and transmit home only the most interesting or time-critical data. Recent developments have demonstrated the tremendous potential of robotic explorers for planetary exploration and for other extreme environments. We believe that science autonomy has the potential to be as important as robotic autonomy (e.g., roving terrain) in improving the science potential of these missions because it directly optimizes the returned data. On- board science data processing, interpretation, and reaction, as well as prioritization of telemetry, therefore, comprise new, critical challenges of mission design. We present a first step toward this vision: a machine learning (ML) approach for analyzing science data from the Mars Organic Molecule Analyzer (MOMA) instrument, which will land on Mars within the ExoMars rover Rosalind Franklin in 2023. MOMA is a dual-source (laser desorption and gas chromatograph) mass spectrometer that will search for past or present life on the Martian surface and subsurface through analysis of soil samples. We use data collected from the MOMA flight-like engineering model to develop mass-spectrometry- focused machine learning techniques. We first apply unsupervised algorithms in order to cluster input data based on inherent patterns and separate the bulk data into clusters. Then, optimized classification algorithms designed for MOMA’s scientific goals provide information to the scientists about the likely content of the sample. This will help the scientists with their analysis of the sample and decision-making process regarding subsequent operations. We used MOMA data to develop initial machine learning algorithms and strategies as a proof of concept and to design software to support intelligent operations of more autonomous systems in development for future exploratory missions. This data characterization and categorization is the first step of a longer-term objective to enable the spacecraft and instruments themselves to make real-time adjustments during operations, thus optimizing the potentially complex search for life in our solar system and beyond.

We use Mars Organic Molecule Analyzer engineering model data to develop mass-spectrometry-focused machine learning techniques. Initial results show that the preliminary categorization could permit autonomous operations, such as prioritizing example data and decisions about retuning parameters for specific samples.

The Neutral Gas and Ion Mass Spectrometer (NGIMS) of the Mars Atmosphere and Volatile Evolution Mission (MAVEN) is designed to measure the composition, struc- ture, and variability of the upper atmosphere of Mars. The NGIMS complements two other instrument packages on the MAVEN spacecraft designed to characterize the neutral upper atmosphere and ionosphere of Mars and the solar wind input to this region of the atmo- sphere. The combined measurement set is designed to quantify atmosphere escape rates and provide input to models of the evolution of the martian atmosphere. The NGIMS is designed to measure both surface reactive and inert neutral species and ambient ions along the space- craft track over the 125-500 km altitude region utilizing a dual ion source and a quadrupole analyzer.

The Neutral Mass Spectrometer (NMS) of the Lunar Atmosphere and Dust Environment Explorer (LADEE) Mission is designed to measure the composition and variability of the tenuous lunar atmosphere. The NMS complements two other instruments on the LADEE spacecraft designed to secure spectroscopic measurements of lunar composition and in situ measurement of lunar dust over the course of a 100-day mission in order to sample multiple lunation periods. The NMS utilizes a dual ion source designed to measure both surface reactive and inert species and a quadrupole analyzer. The NMS is expected to secure time resolved measurements of helium and argon and determine abundance or upper limits for many other species either sputtered or thermally evolved from the lunar surface.

The Rapid infrared IMAger-Spectrometer (RIMAS) is a rapid gamma-ray burst afterglow instrument that will provide photometric and spectroscopic coverage of the Y, J, H, and K bands. RIMAS separates light into two optical arms, YJ and HK, which allows for simultaneous coverage in two photometric bands. RIMAS utilizes two 2048 x 2048 pixel Teledyne HgCdTe (HAWAII-2RG) detectors along with a Spitzer Legacy Indium- Antimonide (InSb) guiding detector in spectroscopic mode to position and keep the source on the slit. We describe the software and hardware development for the detector driver and acquisition systems. The HAWAII- 2RG detectors simultaneously acquire images using Astronomical Research Cameras, Inc. driver, timing, and processing boards with two C++ wrappers running assembly code. The InSb detector clocking and acquisition system runs on a National Instruments cRIO-9074 with a Labview user interface and clocks written in an easily alterable ASCII file. We report the read noise, linearity, and dynamic range of our guide detector. Finally, we present RIMAS’s estimated instrument efficiency in photometric imaging mode (for all three detectors) and expected limiting magnitudes. Our efficiency calculations include atmospheric transmission models, filter models, telescope components, and optics components for each optical arm.

The Johns Hopkins University sounding rocket group is entering the final fabrication phase of the Far-ultraviolet Off Rowland-circle Telescope for Imaging and Spectroscopy (FORTIS); a sounding rocket borne multi-object spectro-telescope designed to provide spectral coverage of 43 separate targets in the 900 - 1800 Angstrom bandpass over a 30' x 30' field-of-view. Using "on-the-fly" target acquisition and spectral multiplexing enabled by a GSFC microshutter array, FORTIS will be capable of observing the brightest regions in the far-UV of nearby low redshift (z approximately 0.002 - 0.02) star forming galaxies to search for Lyman alpha escape, and to measure the local gas-to-dust ratio. A large area (approximately 45 mm x 170 mm) microchannel plate detector built by Sensor Sciences provides an imaging channel for targeting flanked by two redundant spectral outrigger channels. The grating is ruled directly onto the secondary mirror to increase efficiency. In this paper, we discuss the recent progress made in the development and fabrication of FORTIS, as well as the results of early calibration and characterization of our hardware, including mirror/grating measurements, detector performance, and early operational tests of the micro shutter arrays.

The Johns Hopkins University sounding rocket group is building the Far-ultraviolet Off Rowland-circle Telescope for Imaging and Spectroscopy (FORTIS), which is a Gregorian telescope with rulings on the secondary mirror. FORTIS will be launched on a sounding rocket from White Sand Missile Range to study the relationship between Lyman alpha escape and the local gas-to-dust ratio in star forming galaxies with non-zero redshifts. It is designed to acquire images of a 30' x 30' field and provide fully redundant "on-the-fly" spectral acquisition of 43 separate targets in the field with a bandpass of 900 - 1800 Angstroms. FORTIS is an enabling scientific and technical activity for future cutting edge far- and near-uv survey missions seeking to: search for Lyman continuum radiation leaking from star forming galaxies, determine the epoch of He II reionization and characterize baryon acoustic oscillations using the Lyman forest. In addition to the high efficiency "two bounce" dual-order spectro-telescope design, FORTIS incorporates a number of innovative technologies including: an image dissecting microshutter array developed by GSFC; a large area (~ 45 mm x 170 mm) microchannel plate detector with central imaging and "outrigger" spectral channels provided by Sensor Sciences; and an autonomous targeting microprocessor incorporating commercially available field programable gate arrays. We discuss progress to date in developing our pathfinder instrument.