Dual-Spectroscopy Platform for the Surveillance of Mars Mineralogy Using a Decisions Fusion Architecture on Simultaneous LIBS-Raman Data

Abstract

A single platform, integrated by a laser-induced breakdown spectroscopy detector and a Raman spectroscopy sensor, has been designed to remotely (5 m) and simultaneously register the elemental and molecular signatures of rocks under Martian surface conditions. From this information, new data fusion architecture at decisions level is proposed for the correct categorization of the rocks. The approach is based on a decision-making process from the sequential checking of the spectral features representing the cationic and anionic counterparts of the specimen. The scrutiny of the LIBS response by using a moving-window algorithm informs on the diversity of the elemental constituents. The output rate of emission lines allows projecting in a loop the elements as the cationic counterpart of the rock. In parallel, the Raman response of the unknown is compared with all the molecular counterparts of the hypothesized cation that are stored in a spectral library. The largest similarity rate unveils the final identity of the unknown. The identification capabilities of the architecture have been underscored through blind tests of 10 natural rocks with different origins. The great majority of forecasts have matched with the real identities of the inspected targets. The strength of this platform to simultaneously acquire the multielemental and the molecular information from a specimen by using the same laser events greatly enhances the "on-surface" missions for the surveillance of mineralogy.

Low‐level LIBS and Raman data fusion in the context of in situ Mars exploration

“…The challenge for this type of data fusion in contrast to low‐level data fusion is to decide which are the relevant information from each technique that will be combined for the final decision. A successful example of how such a decision tree can look like is given in Moros et al() where a routine is used to first identify the cationic component of minerals with the LIBS data. Subsequently, the measured Raman spectrum is compared with possible Raman spectra of minerals containing that cation, which are stored in an appropriate database.…”

“…There exists one recently published study of LIBS and Raman data fusion in the context of Martian geological in situ analysis where the authors used an advantageous method that measures both signals simultaneously on the same spot with one laser event. () They successfully identified the majority of unknown rocks on the basis of a decision tree corresponding to high‐level data fusion.…”

“…High‐level fusion (or decision level fusion) applies analytical methods to the data of both techniques separately and combines their outcomes to obtain the final result. Decision trees as used by Moros et al() belong to this level of data fusion. In most low‐level data fusion cases, MVA techniques are employed to build classification or regression models.…”

Pulsed laser-induced heating of mineral phases: Implications for laser-induced breakdown spectroscopy combined with Raman spectroscopy

“…Because the two techniques use a similar instrumental architecture based on the same principal components (a laser, a spectrometer and a detector), several combined LIBS-Raman customized setups have been elaborated. Some setups were designed for analysis at the microscale [1,2] while other setups were developed for remote analysis [3][4][5][6][7][8] in particular for field measurements. Notably, most of these instruments were developed with the motivation of designing a compact LIBS-Raman instrument for future planetary exploration.…”

Fast and Simultaneous Determination of Soil Properties Using Laser-Induced Breakdown Spectroscopy (LIBS): A Case Study of Typical Farmland Soils in China

“…The LIBS technique has many merits for sample analysis, including the fact that it is rapid, less destructive, cost-effective, environmentally friendly, little to no sample preparation is required, and simultaneous multi-element detection can be achieved [11][12][13]. Because of these outstanding advantages, the LIBS technique has been widely applied in various fields including space exploration [14][15][16], geological surveying [11,17,18], archaeological investigation [19][20][21], environmental monitoring [22][23][24][25], materials characterization [26][27][28], food detection [29][30][31], agriculture monitoring [32][33][34], and industry monitoring [35,36].…”