Radiation and Dust Sensor for Mars Environmental Dynamic Analyzer Onboard M2020 Rover
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Date
2022-04-10Author
Apestigue, Victor
Gonzalo, Alejandro
Jiménez, Juan J.
Boland, Justin
Lemmon, Mark
de Mingo, Jose R.
García Menendez, Elisa
Rivas, Joaquín
Azcue, Joaquín
Bastide, Laurent
Andrés Santiuste, Nuria
Martínez Oter, Javier
González Guerrero, Miguel
Martin Ortega, Alberto
Toledo, Daniel
Alvarez Rios, Francisco Javier
Serrano, Felipe
Martín Vodopivec, Boris
Manzano, Javier
López Heredero, Raquel
Carrasco, Isaías
Aparicio, Sergio
Carretero, Ángel
MacDonald, Daniel R.
Moore, Lori B.
Alcacera, María Ángeles
Fernández Viguri, Jose A.
Martín, Israel
Yela, Margarita
Álvarez, Maite
Manzano, Paula
Martín, Jose A.
del Hoyo, Juan C.
Reina, Manuel
Urqui, Roser
Rodríguez Manfredi, José Antonio
de la Torre Juárez, Manuel
Hernandez, Christina
Cordoba, Elizabeth
Leiter, Robin
Thompson, Art
Madsen, Soren
Smith, Michael D.
Viúdez Moreiras, Daniel
Saiz Lopez, Alfonso
Gomez Martín, Laura
Martínez, Germán M.
Gómez Elvira, Francisco J.
Arruego, Ignacio
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Sensors 22(8) : (2022) // Article ID 2907
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.
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Except where otherwise noted, this item's license is described as 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
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