학술논문

Mars 2020 SHERLOC On-Board Data Processing Algorithms for Improved Mission Operations
Document Type
Conference
Source
2024 IEEE Aerospace Conference Aerospace Conference, 2024 IEEE. :1-8 Mar, 2024
Subject
Aerospace
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineering Profession
General Topics for Engineers
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Space vehicles
Mars
Fluorescence
Data processing
Extraterrestrial measurements
Manipulators
Time measurement
Language
Abstract
The Scanning Habitable Environments with Raman & Luminescence for Organics & Chemicals (SHERLOC) instrument on the Mars Perseverance Rover robotic arm is a deep UV Raman and fluorescence mapping spectrometer, generating rich hyperspectral datasets co-located with high resolution context images. SHERLOC is equipped with a suite of on-board data processing algorithms, which can be employed to identify regions of interest within a SHERLOC hyperspectral map for immediate follow-up observations of the most astrobiologically interesting targets. Autonomous on-board target selection improves operation efficiency by reducing the number of human decision loops, and potentially decreases the amount of time an abraded surface is exposed to solar UV radiation and arid Martian conditions before SHERLOC makes informed, high resolution measurements, preserving volatiles and potential organics from alteration.In this manuscript, we discuss each of SHERLOC’s on-board data processing algorithms, ground testing, the potential for improved science return, and how surface operations benefit from the implementation of on-board data processing.