Feasibility study of rock identification at the surface of Mars by remote laser-induced breakdown spectroscopy and three chemometric methods

The ChemCam instrument that will equip the Mars Science Laboratory (MSL) rover uses laser-induced breakdown spectroscopy (LIBS) to remotely identify Martian rocks in the proximity of the rover, and to quantitatively assess their composition. Sample identification is then the first step of the chemical analysis, as a decision aid for monitoring the rover and/or before a subsequent composition measurement. In this paper we analyze our experimental spectra obtained in the laboratory by three chemometric methods—principal components analysis (PCA), soft independent modeling of class analogy (SIMCA) and partial least-squares discriminant analysis (PLS-DA)—to investigate the feasibility of rocks classification by remote LIBS. If PCA is very interesting for data visualization, SIMCA and PLS-DA enable the making of automatic predictions. We show that SIMCA is less sensitive than PLS-DA, but also more robust when it encounters spectra of an unknown rock. The instrument accuracy during MSL operations will benefit from a combination of the two approaches.