Session
Swifty Session 3
Location
Utah State University, Logan, UT
Abstract
With limited opportunities and funding for deep space missions, there is increased pressure to build better, faster, and cheaper space-borne payloads. Smaller teams and limited tools provide a unique challenge for such development. This paper reviews the approach the Micro-Mission Systems (MMS) group at Malin Space Science Systems (MSSS) took in the development of the Mars Synchronous Orbiter (MSO) to streamline and automate various tasks so team members could focus their efforts on solving more difficult problems and minimize user induced errors.
The team utilized free tools to automate labor intensive and manual processes, run and monitor tests with little to no user intervention, and build complex flight operation scripts and timetables. Some of these tools were also integrated with commercial flight software systems to deepen the level of automation that could be accomplished and allow for a very lean staffing plan.
The integration of automation at every stage of development culminates within the spacecraft itself in two forms: an autonomous Fault Detection, Isolation, and Recovery (FDIR) system and on-board image processing in the infrared (IR) and visible range. These processes are not unprecedented in spacecraft; however, MSO pushes the envelope on the robustness of these processes in the application of deep space.
In the first autonomous process, the FDIR subsystem monitors key parameters of the spacecraft's health, reboots upon detection of major faults, and proceeds with its primary operations and science objectives on its own. It will only seek ground intervention if it cannot recover from faults autonomously. This subsystem allows routine reboots to be scheduled into nominal operations so that minor errors have less of a chance to accumulate into major errors.
In the second autonomous process, on-board payload image processing was designed to reduce the volume of downlinked data while still delivering products sufficient for science analysis. MSO implements multiple algorithms to improve signal-to-noise ratios for the IR products and to construct high-dynamic range (HDR) visible images that still retain accurate radiometric data. Compression using JPEG2000 results in a data reduction factor up to or exceeding 1000. Raw payload data and lossless final products are generally available - downlink permitting - allowing for a robust delivery system of imaging products.
Automation as a Mindset: An Approach to Streamlining Spacecraft Development and Operations
Utah State University, Logan, UT
With limited opportunities and funding for deep space missions, there is increased pressure to build better, faster, and cheaper space-borne payloads. Smaller teams and limited tools provide a unique challenge for such development. This paper reviews the approach the Micro-Mission Systems (MMS) group at Malin Space Science Systems (MSSS) took in the development of the Mars Synchronous Orbiter (MSO) to streamline and automate various tasks so team members could focus their efforts on solving more difficult problems and minimize user induced errors.
The team utilized free tools to automate labor intensive and manual processes, run and monitor tests with little to no user intervention, and build complex flight operation scripts and timetables. Some of these tools were also integrated with commercial flight software systems to deepen the level of automation that could be accomplished and allow for a very lean staffing plan.
The integration of automation at every stage of development culminates within the spacecraft itself in two forms: an autonomous Fault Detection, Isolation, and Recovery (FDIR) system and on-board image processing in the infrared (IR) and visible range. These processes are not unprecedented in spacecraft; however, MSO pushes the envelope on the robustness of these processes in the application of deep space.
In the first autonomous process, the FDIR subsystem monitors key parameters of the spacecraft's health, reboots upon detection of major faults, and proceeds with its primary operations and science objectives on its own. It will only seek ground intervention if it cannot recover from faults autonomously. This subsystem allows routine reboots to be scheduled into nominal operations so that minor errors have less of a chance to accumulate into major errors.
In the second autonomous process, on-board payload image processing was designed to reduce the volume of downlinked data while still delivering products sufficient for science analysis. MSO implements multiple algorithms to improve signal-to-noise ratios for the IR products and to construct high-dynamic range (HDR) visible images that still retain accurate radiometric data. Compression using JPEG2000 results in a data reduction factor up to or exceeding 1000. Raw payload data and lossless final products are generally available - downlink permitting - allowing for a robust delivery system of imaging products.
