A Novel Cross-Instrument Spectral Harmonization Approach for Mars In Situ LIBS Data

In situ detection on Mars can provide detailed information on the planet's topography and material composition while also validating the results obtained by orbiter probes. The laser-induced breakdown spectroscopy (LIBS) has emerged as a popular technology for Mars in situ exploration due to its fast response and high accuracy in identifying elements. The analysis of LIBS data obtained by different in situ scientific payloads onboard Mars rovers can help explain scientific problems related to about Martian geological genesis and history. However, it is essential to correct the data acquired by different instruments for joint analysis and to facilitate scientific discoveries due to variances in instrument specifications and data acquisition conditions. This article presents a novel cross-instrument spectral harmonization (CISH) approach that can eliminate differences in intensity and peak positions in LIBS spectra from different instruments. In particular, a peak position consistency correction (P2C2) method is proposed to correct cross-instrument peak position inconsistency by eliminating noise or irregular bumps presented in the LIBS spectra that may be incorrectly identified as characteristic peaks. The proposed CISH approach was validated using real Mars in situ LIBS data acquired by the chemistry and camera tool (ChemCam) and Mars surface composition detector (MarSCoDe). The experimental results demonstrate increased consistency in intensity and peak positions. Specifically, the average intensity difference decreased from 3.1287 to 2.1898, and the average peak position difference decreased from 0.1540 to 0.0335 nm. Meanwhile, the accuracy of inversion after consistency correction for the same calibration target (Norite) was also improved. The average root-mean-square error (RMSE) of eight oxides decreased from 5.18 to 3.37 by using a support vector machine (SVM) and from 18.80 to 7.07 using a partial least squares-submodel (PLS-SM). The proposed approach has the potential to establish a uniform benchmark for LIBS data acquired by different instruments at different times and locations, ensuring data consistency and comparability of identified material composition results.