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Radiation and Dust Sensor for Mars Environmental Dynamic Analyzer Onboard M2020 Rover

Authors :
Victor Apestigue
Alejandro Gonzalo
Juan J. Jiménez
Justin Boland
Mark Lemmon
Jose R. de Mingo
Elisa García-Menendez
Joaquín Rivas
Joaquín Azcue
Laurent Bastide
Nuria Andrés-Santiuste
Javier Martínez-Oter
Miguel González-Guerrero
Alberto Martin-Ortega
Daniel Toledo
Francisco Javier Alvarez-Rios
Felipe Serrano
Boris Martín-Vodopivec
Javier Manzano
Raquel López Heredero
Isaías Carrasco
Sergio Aparicio
Ángel Carretero
Daniel R. MacDonald
Lori B. Moore
María Ángeles Alcacera
Jose A. Fernández-Viguri
Israel Martín
Margarita Yela
Maite Álvarez
Paula Manzano
Jose A. Martín
Juan C. del Hoyo
Manuel Reina
Roser Urqui
Jose A. Rodriguez-Manfredi
Manuel de la Torre Juárez
Christina Hernandez
Elizabeth Cordoba
Robin Leiter
Art Thompson
Soren Madsen
Michael D. Smith
Daniel Viúdez-Moreiras
Alfonso Saiz-Lopez
Agustín Sánchez-Lavega
Laura Gomez-Martín
Germán M. Martínez
Francisco J. Gómez-Elvira
Ignacio Arruego
Source :
Sensors, Vol 22, Iss 8, p 2907 (2022)
Publication Year :
2022
Publisher :
MDPI AG, 2022.

Abstract

The Radiation and Dust Sensor is one of six sensors of the Mars Environmental Dynamics Analyzer onboard the Perseverance rover from the Mars 2020 NASA mission. Its primary goal is to characterize the airbone dust in the Mars atmosphere, inferring its concentration, shape and optical properties. Thanks to its geometry, the sensor will be capable of studying dust-lifting processes with a high temporal resolution and high spatial coverage. Thanks to its multiwavelength design, it will characterize the solar spectrum from Mars’ surface. The present work describes the sensor design from the scientific and technical requirements, the qualification processes to demonstrate its endurance on Mars’ surface, the calibration activities to demonstrate its performance, and its validation campaign in a representative Mars analog. As a result of this process, we obtained a very compact sensor, fully digital, with a mass below 1 kg and exceptional power consumption and data budget features.

Details

Language :
English
ISSN :
14248220
Volume :
22
Issue :
8
Database :
Directory of Open Access Journals
Journal :
Sensors
Publication Type :
Academic Journal
Accession number :
edsdoj.f4626cf711de4e01ab8959263abd2bdf
Document Type :
article
Full Text :
https://doi.org/10.3390/s22082907