Mineral analysis is one of the most vital missions in Mars exploration. Laser-induced breakdown spectroscopy (LIBS) is suitable for in situ analysis of minerals on Mars because of its ability to substantially remove dust and analyze most major elements. However, the longevity of active LIBS technology is susceptible to the Martian atmosphere and environmental temperature. Assuming that the LIBS laser had a malfunction, reflectance spectra of surface materials could be acquired in passive mode to analyze minerals and rocks, as is done on the ChemCam and SuperCam instruments on the Mars Science Laboratory and Mars 2020 rover missions, respectively. In addition, passive reflectance can provide constraints on the mineral structure and depositional environment of the rocks encountered by the rover. In this work, we present a passive reflectance spectra method based on the MarSCoDe ground simulator using the spectrometer module of the prototype system to test its ability to acquire visible reflectance spectra. The work presents the reflectance spectra of 24 National Reference Materials from which we computed the spectral parameters of minerals and rocks. Chemometrics based on particle swarm optimization-support vector classification (PSO-SVC) are used to accomplish the recognition of various materials. The results show that the passive spectral method could acquire targeted visible reflectance information and identify materials effectively.

中文翻译：

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MarSCoDe 火星矿物的被动反射光谱分析

矿物分析是火星探索中最重要的任务之一。激光诱导击穿光谱 (LIBS) 适合对火星上的矿物进行原位分析，因为它能够大幅去除灰尘并分析大多数主要元素。然而，主动 LIBS 技术的寿命容易受到火星大气和环境温度的影响。假设 LIBS 激光器出现故障，可以在被动模式下获取表面材料的反射光谱来分析矿物和岩石，就像分别在火星科学实验室和火星 2020 漫游车任务中的 ChemCam 和 SuperCam 仪器上所做的那样。此外，被动反射可以对火星车遇到的岩石的矿物结构和沉积环境提供约束。在这项工作中，我们提出了一种基于MarSCoDe地面模拟器的被动反射光谱方法，使用原型系统的光谱仪模块来测试其获取可见反射光谱的能力。这项工作提供了 24 种国家标准物质的反射光谱，我们从中计算了矿物和岩石的光谱参数。采用基于粒子群优化-支持向量分类（PSO-SVC）的化学计量学来完成对各种材料的识别。结果表明，被动光谱方法能够获取有针对性的可见光反射率信息，有效识别物质。