IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (Jan 2023)

A Novel Adaptive Spectral Drift Correction Method for Recalibrating the MarSCoDe LIBS Data in China's Tianwen-1 Mars Mission

  • Sicong Liu,
  • Haofeng Zeng,
  • Hongpeng Wang,
  • Xiaohua Tong,
  • Hui Zhao,
  • Kecheng Du,
  • Jie Zhang

DOI
https://doi.org/10.1109/JSTARS.2023.3281852
Journal volume & issue
Vol. 16
pp. 5430 – 5440

Abstract

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The Tianwen-1 mission, China's first interplanetary endeavor and Mars mission, touched the surface of the Red Planet on May 15, 2021. With the successful landing of the Zhurong rover on the southern Utopian Planitia of Mars, the Mars Surface Composition Detector (MarSCoDe) on board the rover has started to analyze the material composition of the Martian surface by using the laser-induced breakdown spectroscopy (LIBS). However, changes in instrument temperature and external environment during operation will cause spectral drift in LIBS data, leading to inaccurate material composition inversion results due to shifts in elemental characteristic peak positions. To address this problem, an adaptive spectral drift correction (ASDC) approach is proposed. By considering the distribution of characteristic peaks and drift differences between different elements, the proposed ASDC method corrects the spectral drift in LIBS science data according to an adaptive spectral segmentation strategy. Experimental results obtained on 36 real LIBS science data acquired over 19 exploration activities confirmed the effectiveness of the proposed approach in terms of lower average drift values, by comparing it with two reference methods. Taking the onboard calibration data as a reference, the average spectral drift values of the LIBS science data before and after applying ASDC decreased from 0.1012 nm to 0.0179 nm, 0.0926 nm to 0.0158 nm, and 0.1697 nm to 0.0103 nm in three LIBS channels, respectively. Furthermore, the resulting decrease in the standard deviation and rms error of the average drift values also proved the robustness of the proposed method.

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