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Article

Initial Drift Correction and Spectral Calibration of MarSCoDe Laser-Induced Breakdown Spectroscopy on the Zhurong Rover

1
School of Physics and Optoelectronic Engineering, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310024, China
2
Key Laboratory of Space Active Opto-Electronics Technology, Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai 200083, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2022, 14(23), 5964; https://doi.org/10.3390/rs14235964
Submission received: 8 October 2022 / Revised: 11 November 2022 / Accepted: 21 November 2022 / Published: 25 November 2022

Abstract

:
The Mars Surface Composition Detector (MarSCoDe) carried by the Zhurong rover of China’s Tianwen-1 mission uses Laser-Induced Breakdown Spectroscopy (LIBS) to detect and analyze the material composition on Martian surfaces. As one extraterrestrial remote LIBS system, it is necessary to adopt effective and reliable preprocessing methods to correct the spectral drift caused by the changes in environmental conditions, to ensure the analysis accuracy of LIBS scientific data. This paper focuses on the initial spectral drift correction and estimates the accuracy of on-board wavelength calibration on the LIBS calibration target measured by the MarSCoDe LIBS. There may be two cases during the instrument launch and landing, as well as the long-term operation: (a) the initial wavelength calibration relationship can still apply to the on-board LIBS measurement; and (b) the initial wavelength calibration relationship has been changed, and a new on-board calibration is needed to establish the current relationship. An approach of matching based on global iterative registration (MGR) is presented in respect to case (a). It is also compared with the approach of particle swarm optimization (PSO) for case (b). Furthermore, their accuracy is estimated with the comparison to the National Institute of Standards and Technology (NIST) database. The experimental results show that the proposed approach can effectively correct the drift of the on-board LIBS spectrum. The the root-mean-square error (RMSE) of the internal accord accuracy for three channels is 0.292, 0.223 and 0.247 pixels, respectively, compared with the corrected Ti-alloy spectrum and the NIST database, and the RMSE of the external accord accuracy is 0.232, 0.316 and 0.229 pixels, respectively, for other samples. The overall correction accuracy of the three channels is better than one-third of the sampling interval.

Graphical Abstract

1. Introduction

After the first Laser-Induced Breakdown Spectroscopy (LIBS) was used in an extraterrestrial environment in 2012, the ChemCam of NASA’s Curiosity rover was used to investigate the Martian geochemistry [1]. In addition, as a subsequent instrument, the SuperCam of the Perseverance rover, also with LIBS, landed on 18 February 2021 [2]. In China’s first Mars exploration Tianwen-1 mission, the lander taking the Zhurong rover successfully landed in the southern part of the Martian Utopian plain on 15 May 2021. As one of the six scientific payloads, the Mars Surface Composition Detector (MarSCoDe) instrument uses LIBS and Short-Wave Infrared (SWIR) spectroscopy to perform he in situ detection of the Martian surface minerals, rocks and soils [3].
LIBS technology can make use of the wavelength and intensity of the characteristic lines of elements in the laser-induced plasma spectrum produced by the ablation of samples to analyze the chemical composition of the target qualitatively and quantitatively and determine the element concentration in the sample. It is necessary to accurately identify the wavelength position of the emission lines for each element in the spectrum. The spectral line of the LIBS spectrum is not a strict geometric line. The experimental results show that these spectral lines have certain shapes, such as the Doppler broadening, the Lorentz broadening, the self-absorption broadening, Stark broadening and so on [4]. These broadening mechanisms make the spectral peaks follow Gaussian distribution or Lorentz distribution. There may be overlap between different spectral peaks, which affects our judgment of the intensity of the spectral peaks. Among them, Stark broadening not only broadens the spectral line, but also leads to the shift of the peak position [5]. The Stark broadening of the Fe I 538.34 nm emission line can be 0.01–0.06 nm for an electron density between (4–15) × 1016 cm−3 [6]. This affects the identification of elements. In addition, the change in environment or the status of the instrument also cause the position of the spectral lines to drift, which greatly reduces the accuracy of the spectral determination, especially in the extraterrestrial LIBS system. Therefore, we need to adopt suitable data-processing methods to correct the wavelength of the LIBS spectrum, improve the accuracy of the position of the characteristic spectral lines of elements, and help to distinguish the emission lines that may be overlapped.
For LIBS in the Mars environment, the main influence factor of the wavelength uncertainty comes from the environmental difference between the extraterrestrial and the Earth. The change in pressure leads to changes in the intensity of the spectral lines. From low pressure to high pressure, the intensity of the spectral lines increases at first and then decreases [7,8,9]. The change in temperature interferes with the structure of the spectrometer, thus affecting the accuracy of spectral measurement [10]. The changes in temperature and atmosphere between Mars and Earth make it possible to change the position and intensity of the characteristic spectral lines of the elements. The maximum expected drift of the ChemCam spectrometer is about three channels for a ~20 °C operational temperature range. When the temperature changes greatly, it produces a larger offset [11]. The average surface temperature of the Utopian plain can change from 180 K to 240 K in a year. The temperature varies widely and is much lower than the ambient temperature of the ground laboratory. The huge environmental differences make it difficult to directly use the data model established by the laboratory to analyze the in situ exploration data on Mars. The mast unit of the ChemCam is wrapped in a protective cover to ensure that it can run in the range of −40–35 °C [12], greatly reducing the interference of the Martian ambient temperature on the instrument. The mast unit of the SuperCam has independent heaters that enable it to work at temperatures above −40 °C [13]. The Zhurong rover is powered by solar energy and does not have enough power to control the temperature of the MarSCoDe. Therefore, compared with the ChemCam and SuperCam, the MarSCoDe has to go through a more severe test of the Martian environment and adapt to the low temperature on the Martian surface. This may increase the uncertainty of the spectral wavelengths. A lot of research has been carried out to compensate the spectral wavelength drift. Carter et al., proposed a guideline of how to effectively use the polynomials commonly used in spectrometer correction software to convert the number of pixels into wavelength or wavenumber [14]. Holy analyzed the main reason for spectrometer drift and optimized the calibration equation [15]. Asimellis et al., proposed a technique of wavelength calibration based on the inverse numerical solution of the grating dispersion function, which can be used in LIBS and other spectral analyses [16]. Song et al., proposed an efficient and accurate automatic wavelength correction scheme, which improves the calibration accuracy [17]. With respect to correcting the influence of extraterrestrial environment changes on the LIBS spectrum, Wiens et al., used a partial matched filtering technique to calibrate the spectra of the ChemCam to the vacuum wavelengths in the National Institute of Standards and Technology (NIST) LIBS database and correct the wavelength drift [11]. Anderson et al., adopted an optimized ChemCam spectral calibration approach to calibrate the wavelength of the SuperCam’s on-board spectrum. In addition to Ti, they also used two additional targets, one of which is a mixture of ilmenite and hematite, and the other one is a mixture of clinozoisite quartz and orthoclase [18]. Xu et al., studied the temperature-dependent trend of LIBS spectra collected by the MarSCoDe at different temperatures [19]. They selected a certain number of characteristic peaks in each of the three channels of the LIBS spectrometer. With the change in temperature, the pixel drift of each characteristic peak is roughly equal in the same channel. Wan et al., proposed an elastic particle swarm optimization (PSO) approach to fulfill the on-board spectrum calibration of the MarSCoDe [20]. Through the iteration of the particle swarm, the corresponding relationship between wavelengths and pixels is optimized. However, there may be two cases during the instrument launching and landing: (a) the initial wavelength calibration relationship (calibrated on the ground) can still apply to the on-board LIBS measurement, and there is just global drift for each of the three channels; and (b) the initial wavelength calibration relationship is changed, and a new on-board calibration is needed to find the current relationship. In addition, their performance needs further verification.
In this project, two spectral drift correction methods on the MarSCoDe LIBS are presented to deal with the two cases, respectively, and the initial LIBS spectra on the calibration target are conducted and compared. With respect to case (a), a spectrum matching based on the global iterative registration (MGR) approach is presented to identify the amount of spectral drift for each channel and correct the number of pixels, and then calculate the wavelength by the initial relationship. With respect to case (b), a PSO algorithm is verified to build the new relationship and then convert each pixel to the corresponding wavelength. Firstly, the main situation of the MarSCoDe and experimental data set are introduced. Secondly, the spectral calibration method of the LIBS spectrometer is presented. The MGR correction method is proposed for case (a) and the PSO algorithm is described for case (b). Thirdly, the spectral drift correction is carried out by a Ti-alloy calibration sample in the early detection schemes, and the internal accord accuracy is evaluated, while the calibration parameter is also conducted on another eleven calibration samples, and the external accord accuracy is evaluated. Finally, some qualitative and quantitative analysis are compared and discussed.

2. Data Set

2.1. Previous Work Brief

The Zhurong rover left the Tianwen-1 lander and began to inspect and explore on 22 May 2021. As the main payload on-board the rover, the MarSCoDe is an instrument suite and has been described in detail in Xu et al. [19], which takes LIBS to provide an active spectroscopy over 240–850 nm, with a stand-off distance of 1.6~7 m. 1064 nm laser pulses, with the energy of about 23 mJ, at frequency of 1–3 Hz fire the sample. The LIBS spectra within the three channels were recorded using 1800 pixels of the three CCDs, and the spectrum ranges covered by channel 1 (CH-1), channel 2 (CH-2) and channel 3 (CH-3) were 240–340 nm, 340–540 nm and 540–850 nm, respectively. A set of 12 LIBS calibration samples (including Ti-alloy, norite, andesite, basalt, montmorillonite, nontronite, olivine, hypersthene, K-feldspar, gypsum, dolomite and apatite) is mounted on the antenna mast at the rear deck of the rover and about ∼1.7 m from a two-dimensional (2D) pointing mirror. Prior to the launch, we calibrated the relationship between the pixels and the wavelength using four standard lamps (including Mercury–Argon, Zinc, Cadmium and Neon), and tested the amount of spectral drift at different temperatures [19]. The main components in the calibration samples were also analyzed by X-ray fluorescence, where the main elements contain Ti, Al, Si, Fe, Mn, Mg, Ca, Na, K, O, P and S, etc.
The brief workflow of the MarSCoDe LIBS in situ detection is to point the laser to the calibration sample through the 2D pointing mirror for the on-board calibration, and then point to the scientific target for the in situ detection. LIBS measurements for each scientific target or calibration sample include 60 consecutive laser shots at frequency of 3 Hz, with an integration of 1 ms and without delay after the laser shot; another 180 passive spectra without laser shots were collected with identical exposure settings and there was a dark background for each observation. Up to 21 February 2022, a total of 89 LIBS spectra on Level 2B were first released, including 51 spectra of calibration samples and 38 spectra of scientific targets.

2.2. Data Source

In each exploration scheme, the Ti-alloy is first measured and provides on-board wavelength calibration, and then two or three other calibration samples are selected to assess the real-time instrument status, before the scientific detection. We assume that the drift of the spectrum collected by MarSCoDe LIBS in one working cycle is the same. We calibrated the LIBS spectra of each calibration sample collected in the extraterrestrial environment for the first time. A total of 17 spectra were selected from the published on-board calibration data, including six spectra of Ti-alloy and 11 spectra of another eleven samples. The parameters of the LIBS data, collection time and sample name are listed in Table 1. The pressure and temperature come from the data of the Mars Climate Station on the Zhurong rover. Except for the Ti-alloy and norite samples, each spectrum is the first data of these samples measured by the MarSCoDe on Mars. According to the spectra of the calibration samples collected at different times, we selected six Ti-alloy spectra for correction. The abnormality and poor quality of the first norite LIBS spectrum may reduce the accuracy of the qualitative analysis, so we use the second scheme data of norite for the drift correction calculation.
The spectrum relevance to LIBS in the Atomic Spectra Database (ASD) of NIST [21] is used as the standard to correct the on-board data. The ASD contains data for radiative transitions and energy levels in atoms and atomic ions. For a given electron temperature and electron density, the level populations and radiative transition probabilities are calculated, and then the spectrum is determined. The default values of electron temperature and electron density are 1eV and 1017 cm−3. The parameters are roughly set on the basis of the plasma temperature and density of the ChemCam spectrum for the validation of the proposed method [22]. We download the emission lines of nine main elements (such as Ti, Al, Si, Fe, Mg, Ca, Na, K and O), two minor elements (Mn, P) and one trace element (S) in the 220 nm–870 nm range under vacuum conditions from the NIST database website as the standard wavelength. Some of the main characteristic peaks used in the spectral calibration approach are shown in Table A1 and Table A2 in Appendix A. We do not use the wavelength values in air in the database because the Martian pressure is about 700 Pa, which is closer to a vacuum. According to the Ritz principle, the wavenumber of an emitted or absorbed photon is equal to the difference between the upper and lower energy levels. The value of wavelengths in vacuum is equal to the inverse of wavenumber, where wavenumber is in cm−1 and wavelength is in nm.
In addition, the MGR algorithm proposed in this paper selects a reference spectrum to identify the wavelength drift between the on-board spectrum and this reference spectrum, to improve the efficiency and accuracy of wavelength correction. The reference spectrum is the LIBS spectrum of the Ti-alloy sample collected by the MarSCoDe in a simulated Martian environment before the launching. The Ti-alloy is placed in a vacuum chamber filled with CO2 at a pressure of 874 Pa and a temperature of 24 °C. The MarSCoDe was exposed to the laboratory environment and the spectrum was collected at a distance of 1.7 m from the sample.

3. Methodology

The conversion relationship between responded pixel and spectral wavelength is assumed, and it was determined by the spectral calibration with four standard lamps prior to launch. There are some spectral drifts with the temperature change, due to the limited temperature control of the equipment. There are two main cases: (a) the initial wavelength calibration relationship (calibrated on the ground) can still apply to the on-board LIBS measurement, which means there is just global drift for each of the three channels; and (b) the initial wavelength calibration relationship is changed through impact during launch or landing and the long-term flight environment.

3.1. The Principle of Wavelength Calibration

Spectral calibration of the spectrometer is the premise and basis for the quantitative analysis of LIBS. With respect to the wavelength calibration on the MarSCoDe LIBS spectrometer, the standard lamp with more characteristic spectral lines is used as the input signal for the spectrometer to mark the pixel position corresponding to the specific spectral line, and then the polynomial function fits the relationship between the response pixel and a given wavelength, so as to establish the conversion relationship between all the pixels and the wavelength. The appropriate characteristic spectral lines are selected so that they can evenly cover the wavelength range of each channel. Suppose the wavelength of the characteristic spectral line is λ = [ λ 1 , λ 2 , λ 3 , , λ n ] , n denotes the number of characteristic lines, and the corresponding pixel index is P = [ p 1 , p 2 , p 3 , , p n ] , then the pixel–wavelength relationship can be expressed as
λ n = a 0 + a 1 p 1 + a 2 p 2 2 + + a j p n j
where a j is the coefficient of the polynomial and j is the order of the polynomial. In the experiment, the quadratic function is used in the three channels to describe the relationship between pixel and wavelength. The calibration coefficients in the three channels of the spectrometer are calculated in Table 2 [19].

3.2. Spectral Drift Corrected by MGR Algorithm

When the MarSCoDe works, the average temperature on Mars is −16 °C, the pressure is about 840 Pa, and the gas is mainly composed of CO2, including a small amount of N2, Ar and so on [23]. With respect to case (a), the wavelength of the characteristic lines of elements collected in the Martian environment drift to a certain extent compared with the corresponding lines in the NIST database. In addition, the relative intensity and number of characteristic lines also change, which makes it more difficult to correct the drift of on-board data.
The wavelength drift caused by temperature shows the law of overall drift in the same channel, as demonstrated in Xu et al. [19]. Based on this assumption, we propose the MGR approach for the wavelength correction of MarSCoDe LIBS. The drift situation within the channel is determined by the amount of responded pixel drift of the characteristic spectral lines, and then the drift correction of the LIBS measurements can be obtained. The drift correction of the LIBS measurements can be realized by adding a correction to the responded pixel. Through several iterations of spectral matching, the correction pixel with an optimal matching degree is selected.
In order to correct the spectral drift more conveniently and accurately, the reference spectrum is used as the bridge between the standard spectrum and the on-board data. Firstly, the drift between the reference spectrum and the standard spectrum is calculated, denoted as Δ p 1 . The reference spectra were qualitatively analyzed, and the corresponding standard spectral wavelength values of the main characteristic peaks were determined. The approximate pixel drift value of the reference spectrum can be obtained according to the sampling interval wavelength, and the reference spectrum can be moved within a certain range. At each drift, the root-mean-square error (RMSE) of the matching peak between the reference spectrum and the standard spectrum was calculated and used as the optimization standard. The correction pixel with an optimal matching degree is Δ p 2 . Secondly, the drift between the reference spectrum and the on-board spectrum is calculated, denoted as Δ p 2 . Like the calculation process of Δ p 1 , the reference spectrum is matched with the on-board Ti-alloy spectrum, and the approximate pixel drift is calculated. The on-board spectrum is moved within a certain range, and the correction pixel is selected with the optimal matching degree, namely Δ p 2 . The formula of RMSE is
RMSE = 1 n i = 1 n ( λ 1 i λ 2 i ) 2
where λ 1 i and λ 2 i represent the wavelength values of the matched peaks of the two spectra to be compared, respectively, and n indicates the number of matching peaks. Finally, through the data transmission of the reference spectrum, the on-board data can be associated with the NIST database. The correction formula for wavelength drift is
λ = a 0 + a 1 ( p + Δ p 1 + Δ p 2 ) + a 2 ( p + Δ p 1 + Δ p 2 ) 2

3.3. Spectral Drift Corrected by Particle Swarm Optimization (PSO) Algorithm

With respect to case (b), the PSO algorithm test in Wan et al. [20] is used here to conduct the on-board calibration of MarSCoDe LIBS. The PSO algorithm is a bionic swarm intelligence algorithm proposed by American scholars Kennedy and Eberhart in 1995, inspired by the foraging behavior of birds [24]. It completes the update and optimization by searching the individual optimal solution of the particle and the global optimal solution of the particle population. For the spectrum set in each channel, a particle swarm that contains several particles is set up. Each particle moves freely in the solution space. The position of the particle represents the coefficient in Formula (1). Bringing it into Formula (1), the new spectral coordinates are obtained and recorded as the particle wavelength set (PWS). The RMSEs of the matching peaks between the PWS and the standard spectrum are calculated. After many iterations, the particle position with the minimum error, that is, the optimal wavelength calibration coefficient, is calculated.

3.4. Comparison and Evaluation

Based on the wavelength values in the NIST database, the on-board data are corrected by MGR and PSO. In order to verify the accuracy and reliability of the calibration approach, the calibration results are evaluated from two aspects: internal accord accuracy and external accord accuracy. In the internal accord accuracy, the corrected parameter of the Ti-alloy spectrum is first determined by the correction approach and referencing the NIST wavelength, and then used for the drift correction of this spectrum; the wavelength accuracy of the characteristic lines in the corrected spectrum is compared to the NIST database. In the external accord accuracy, the corrected parameter is used to correct the spectrum of the other 11 calibration samples, and then the wavelength accuracy of the characteristic lines is compared to the elemental spectral lines in the samples from the NIST database. Referencing the NIST database, the indicators of absolute mean error (AME) and RMSE on the corrected spectra are used to quantitatively analyze the correction accuracy.

4. Results and Discussion

4.1. The Results of MGR Algorithm

In the calculation of Δ p 1 , the reference spectrum is preprocessed, including dark background subtraction, noise filtering, cubic spline interpolation fitting and min–max normalization. According to the initial wavelength calibration coefficient in Table 2, the initial wavelength sampling intervals of the three channels are 0.0667 nm, 0.1324 nm and 0.2033 nm, respectively. Figure 1 shows the variation in RMSE obtained by moving the reference spectrum each time. It can be obviously observed that the RMSE shows a parabolic trend with the change in the number of corrected pixels. The abscissa corresponding to the minimum RMSE is the drift of the reference spectrum with respect to the standard spectrum. The spectral drift correction amounts of the three channels are 1.40, 1.39 and 0.45 pixels, respectively, with an RMSE of 0.0258, 0.0362 and 0.0550 nm, respectively.
In the calculation of Δ p 2 , the on-board spectra need to be preprocessed in the same way as the reference spectra. The published on-board data have been subject to dark background subtraction and radiation calibration, so we only need to perform cubic spline interpolation fitting and min–max normalization on the on-board spectrum. The spectra of the Ti-alloy collected by MarSCoDe LIBS on different Martian days are compared with the reference spectrum after the same processing. Taking the Ti-alloy spectrum collected on 25 June 2021 as an example, Figure 2 shows the changes in the spectrum before and after correction and the change diagram of the RMSE. The length of both the reference spectrum and the on-board spectrum is 5400 pixels, so the position of the peak position in calculation is the pixel rather than the wavelength when the peaks are matched. The RMSE is also measured in pixels. As can be seen from Figure 2, the matching peaks in each channel are distributed as evenly as possible. The corrected spectrum is in good agreement with the reference spectrum. The change in RMSE is also a parabola trend. The position of the minimum RMSE is the best correction amount. Table 3 shows the Δ p 2 and RMSE of six Ti-alloy spectra. The mean RMSE for the three channels is 0.138, 0.119 and 0.163 pixels, respectively. The RMSEs of all three channels are better than 0.2 pixels. The corrections of the Ti-alloy spectra collected at different times are different. This has to do with the different environment and instrument states at each probe. The drift of the first channel and the second channel is small, and the drift of the third channel is the largest.

4.2. The Results of PSO Algorithm

We use the PSO algorithm to correct the drift of on-board Ti-alloy spectra and obtain the new relationship between the responded pixel and wavelength. The on-board spectrum is performed by cubic spline interpolation fitting and min–max normalization before correction. The wavelength calibration coefficient after correction is shown in Table 4. The correction coefficients of the spectra collected at different times are different. Taking the Ti-alloy spectrum collected on 25 June 2021 as an example, Figure 3 shows the change in RMSE with the number of iterations during the iteration process. In the previous iterative calculation, the matching error decreased rapidly. With the increase in the number of iterations, the rate of error reduction becomes slower and slower, which indicates that it is close to the optimal solution.

4.3. Comparison of the Two Methods

4.3.1. Internal Accord Accuracy

Referencing the NIST database, the total wavelength drift of the on-board Ti-alloy spectrum obtained by the MGR method is shown in Table 5. The drift of the spectrum is different at different times. For example, in the spectrum set of CH-1, the minimum drift is only 0.24 pixels, and the maximum drift is 4.04 pixels; in the spectrum set of CH-2, the minimum drift is only 1.43 pixels, and the maximum drift is 3.91 pixels; and in the CH-3, the minimum drift is only 12.72 pixels, and the maximum drift is 12.97 pixels. This is related to the changes in environment on Mars. As can be seen from Table 1, the temperature and air pressure are different every day. We carry Δ p 1 and Δ p 2 into Equation (3) to obtain the corrected on-board spectral wavelength. Table 6 shows the AME and RMSE of two different spectral wavelength drift correction approaches. For the accuracy of MGR, the mean errors in the first, second and third channel is 0.016 nm, 0.022 nm and 0.040 nm, and the RMSE is 0.020 nm, 0.030 nm and 0.050 nm, respectively. According to the sampling interval wavelength value corresponding to each pixel, the mean error is 0.232 pixels, 0.166 pixels and 0.195 pixels, and the RMSE is 0.292 pixels, 0.223 pixels and 0.247 pixel, respectively. Furthermore, the maximum error is 29.2% of the pixel (on the RMSE of CH-1), so that the overall accuracy is better than one-third of the pixel. For the accuracy of the PSO, the mean error in the first, second and third channel is 0.017 nm, 0.031 nm and 0.021 nm, and the RMSE is 0.023 nm, 0.039 nm and 0.026 nm, respectively. According to the sampling interval wavelength value corresponding to each pixel, the mean error is 0.255 pixels, 0.230 pixels and 0.104 pixels, and the RMSE is 0.342 pixels, 0.291 pixels and 0.104 pixels, respectively. In addition, the maximum error is 34.2% of the pixel (on the RMSE of CH-1), so that the overall accuracy is nearly one-third of the pixel. The errors may come from the limitation of spectral resolution, which makes it impossible for us to accurately determine the position of the spectral peaks. In addition, Stark broadening is also one of the important factors affecting the correction effect. The collision of atoms with ions and electrons shifts the position of the spectral peak. Since the spectral resolution of the three channels of the MarSCoDe is nearly 0.19 nm, 0.31 nm and 0.45 nm, respectively, which is much higher than the shift range of spectral lines caused by Stark broadening, in this study, we ignore the influence of spectral line drift caused by Stark broadening and focus on the spectral drift caused by environmental changes. We do not analyze the Stark shift of the spectrum, which may be one of the sources of the final error. It should also be noted that, in this paper, we assume that the MarSCoDe LIBS spectrum satisfies the local thermal equilibrium, which is consistent with the data in the NIST database. However, we do not have strong data to support this hypothesis. This may also be one of the sources of error. From the results of the RMSE, the effect of the MGR method is better than that of the PSO algorithm in the first and second channel, and slightly inferior to the PSO method in the third channel. This may be due to the low resolution of the third channel spectrometer. The uncertainty of the position of the characteristic peaks makes the fitting calibration relationship more accurate. In Table 5, the number of matching peaks selected by the MGR and PSO methods for spectral correction is counted. Due to the change in environment, the intensity value of the Ti-alloy spectrum collected at different times changes, and the number of characteristic peaks is also different. As many characteristic peaks as possible were selected in each channel for spectral correction and accuracy evaluation. Taking the Ti-alloy spectrum collected on 12 July 2021 as an example, Figure 4 shows the spectra before and after wavelength drift correction by the MGR and PSO methods. As can be seen from the figure, the number of characteristic lines in the third channel is much smaller than that in the first and second channels. After correction, the two methods can solve the problem of spectral drift well.

4.3.2. External Accord Accuracy

The correction amount or correction coefficient obtained from the Ti-alloy spectrum is carried into other samples’ spectra to realize the drift correction. We used MGR and PSO approaches to correct the spectra of another 11 calibration samples and calculated the mean error and RMSE of the matching peaks, as shown in Table 7. For the accuracy of MGR, the mean errors in the first, second and third channel is 0.012 nm, 0.033 nm and 0.040 nm, and the RMSE is 0.015 nm, 0.042 nm and 0.0460 nm, respectively. According to the sampling interval wavelength value corresponding to each pixel, the mean error is 0.183 pixels, 0.253 pixels and 0.195 pixels, and the RMSE is 0.232 pixels, 0.316 pixels and 0.229 pixels, respectively. Furthermore, the maximum error is 31.6% of the pixel (on the RMSE of CH-2), so that the overall accuracy is also better than one-third of the pixel. For the accuracy of the PSO, the mean error in the first, second and third channel is 0.012 nm, 0.040 nm and 0.052 nm, and the RMSE is 0.017 nm, 0.047 nm and 0.066 nm, respectively. According to the sampling interval wavelength value corresponding to each pixel, the mean errors is 0.179 pixels, 0.305 pixels and 0.254 pixels, and the RMSE is 0.251 pixels, 0.357 pixels and 0.326 pixels, respectively. In addition, the maximum error is 35.7% of the pixel (on the RMSE of CH-2), so that the overall accuracy is also nearly one-third of the pixel. Using RMSE as the evaluation mechanism of the correction approach, the effects of the two methods are almost the same in the first channel. The MGR correction results of individual samples are better, such as Andesite, Montmorillonite and Hypersthene. In the second and third channels, the RMSE of most samples of the MGR algorithm is lower, which shows that its correction effect is better than that of the PSO algorithm. The MGR algorithm is more universal and can be applied to the spectral correction of different samples. Figure 5 shows the on-board spectra of 11 samples before and after wavelength drift correction. The spectra corrected by the two approaches match the NIST database well. Many elements such as Mg, Si, K, Ca, Na, O and C can be identified. Table 7 counts the number of characteristic lines used in the calibration process of the on-board spectra. In some samples, such as gypsum, the number of characteristic peaks is small, but they are uniformly distributed throughout the wavelength range of the spectrometer.

5. Conclusions

As one extraterrestrial LIBS system, MarSCoDe LIBS also has some spectral drift with the changes in the environmental conditions. Elaborate LIBS spectral calibration is the crucial foundation for realizing accurate qualitative and quantitative analysis, even for sophisticated deep learning based chemometrics [25,26]. There may be two cases during the instrument launch and landing, as well as the long-term operation: (a) the initial wavelength calibration relationship can still apply to the on-board LIBS measurement; and (b) the initial wavelength calibration relationship is changed, and a new on-board calibration is needed to find the current relationship.
In this project, two spectral drift correction approaches of MGR and PSO are presented to deal with the two cases, respectively, and the initial on-board LIBS spectra of the LIBS calibration targets are conducted and compared. Firstly, the main situation of the MarSCoDe and the experimental data are introduced. Secondly, the spectral calibration approach of the LIBS spectrometer is presented. The MGR correction method is proposed for case (a), and the PSO algorithm is described for case (b). Thirdly, the spectral drift correction is carried out using the Ti-alloy calibration sample, and the internal accord accuracy is evaluated, while the calibration parameter is also conducted on other calibration samples, and the external accord accuracy is evaluated. Finally, some qualitative and quantitative analyses are estimated with a comparison to the NIST database. The experimental results show that the proposed approach can effectively correct the drift of the on-board LIBS spectrum, and the RMSE of the internal accord accuracy for the three channels is about 0.292, 0.223 and 0.247 pixels, respectively, compared with the corrected spectrum and the NIST database, and the RMSE of the external accord accuracy is about 0.232, 0.316 and 0.229 pixels, respectively. The overall accuracy of the three channels is better than one-third of sampling interval. Compared with the PSO method, MGR has a better correction effect in the first and second channels. The correction effect of MGR in the third channel is worse, which may be caused by the low spectral resolution in the third channel. When the calibration model obtained from the Ti-alloy spectrum is tested in the spectra of other calibration samples, the MGR method performed better than the PSO method in the three channels. The maximum internal accord accuracy errors of the MGR and PSO methods are about 29.2% and 34.2% of pixels, respectively (on the RMSE of CH-1). The maximum external accord accuracy errors of the MGR and PSO methods are about 31.6% and 35.7% of pixels, respectively (on the RMSE of CH-2). The internal and external accord accuracy of MGR is higher.

Author Contributions

Conceptualization, X.L. and L.J.; methodology, X.L. and W.X.; validation, L.J. and Z.C.; resources, X.X. and L.L.; data curation, L.J. and Z.L.; writing—original draft preparation, L.J.; writing—review and editing, X.L.; supervision, R.S. All authors have read and agreed to the published version of the manuscript.

Funding

This work was funded by the National Natural Science Foundation of China (NSFC) (No. 11904378), the grant from the Key Laboratory of Space Active Opto-electronics Technology, CAS (No. CXJJ-22S019), the Key Laboratory of Lunar and Deep Space Exploration, CAS (No. LDSE201904), and the Natural Science Foundation of Shanghai (No. 22ZR1472400); support was received from the China National Space Administration (CNSA) and the National Natural Science Foundation (No. U1931211), and the Pre-research Project on Civil Aerospace Technologies (No. D020102).

Data Availability Statement

The data are available upon request from the author.

Conflicts of Interest

The authors declare no conflict of interest.

Appendix A

Table A1. The standard wavelength used in spectral calibration with Ti-alloy. Ei and Ek are the upper and lower energy levels of electron transitions, respectively.
Table A1. The standard wavelength used in spectral calibration with Ti-alloy. Ei and Ek are the upper and lower energy levels of electron transitions, respectively.
IonWavelength (nm)Ei (cm−1)Ek (cm−1)IonWavelength (nm)Ei (cm−1)Ek (cm−1)
Ti-II245.117712,758.259753,554.9903Ti-II364.23669975.999437,430.6814
C-I247.931021,648.030061,981.8321Ti-II370.727112,628.845539,602.8645
Ti- II251.81891087.356140,798.4333Ti- II372.26954628.657131,490.9177
Al-II252.724495,350.6000134,919.4000Ti-II374.27021700.000012,758.2597
Al-II254.0945106,920.5600146,276.0000Ti-II376.23894628.657131,207.5111
Ti-II255.675529,734.620668,846.6990Ti-II381.56634628.657130,836.4250
Ti-II256.516838,425.990077,424.4500Ti-I388.399216,458.671042,205.3770
Ti-II264.686240,027.200177,807.7864Ti-I390.2064170.132825,797.5950
Ti-II269.924643,740.767880,788.1500Ti-I391.5443386.874025,926.7710
Ti-II273.165031,756.640668,364.5454Ti-I396.39720.000025,227.2220
Ti-II274.735531,207.511167,606.1621Ti-II402.947715,257.552740,074.6707
Ti-II275.242031,490.917767,822.5867Ti-II405.496615,265.700139,926.8192
Ti-II276.56328744.340644,902.4455Ti-I407.96228602.344133,114.4200
Ti-II280.564629,544.454065,186.8680Ti-I416.530515,108.111039,115.9570
Ti-II281.11269975.999445,548.9273Ti-II417.308020,951.755144,914.8733
Ti-II281.864429,968.330465,446.3822Ti-I429.14229395.802032,698.1022
Ti-I282.88966742.756042,092.2360Ti-I430.17646661.006029,907.2860
Ti-II284.27704897.717940,074.6707Ti-II430.90779395.802032,602.6265
Ti-II285.19399851.014544,914.8733Ti-I431.55576742.756029,914.7370
Ti- II285.692330,240.939665,243.6290Ti-II433.91348710.567531,756.6406
Ti-II286.31609975.999444,902.4455Ti-II436.888020,891.789843,780.9533
Ti-II287.82798997.787443,740.7678Ti- II439.62668744.340631,490.9177
Ti-II288.49489118.284943,780.9533Ti-II441.89549395.802032,025.5915
Ti-II294.270931,113.676465,095.9741Ti-II444.50488710.567531,207.5111
Ti-II295.543434,748.506268,584.4792Ti-II445.17318744.340631,207.5111
Ti-II301.806212,774.816845,908.6592Ti-II446.97479118.284931,490.9177
Ti-II302.454934,543.379967,606.1621Ti-II448.958325,192.965047,466.7479
Ti-II303.061012,677.105045,673.7641Ti-II450.25328997.787431,207.5111
Ti-II304.702443,780.953376,599.8564Ti-I453.60486742.7560 28,788.3800
Ti-II305.876132,767.196165,460.1706Ti- II455.089712,774.816834,748.5062
Ti-II306.710994.114232,698.1022Ti- II456.50379851.014531,756.6406
Ti-II307.335229,734.620662,272.3881Ti- II457.325312,677.105034,543.3799
Ti-II307.9538225.703932,698.1022Ti-II480.643616,625.244137,430.6814
Ti-II308.8922393.445932,767.1961Ti-II491.256625,192.965045,548.9273
Ti- II309.80819930.776642,208.8232Ti-I498.31206842.962026,910.7090
Ti-II310.470315,257.552747,466.7479Ti-I499.24586742.756026,772.9680
Ti-I311.157412,118.393044,257.0980Ti-I500.08986661.006026,657.4160
Ti-II311.85719930.776641,996.7498Ti-I501.56756556.833026,494.3300
Ti-II313.170694.114232,025.5915Ti-I503.786811,639.810931,489.4760
Ti-I314.466516,458.671048,262.7050Ti- II519.013212,758.259732,025.5915
Ti-II315.65821087.356132,767.1961Ti- II522.7994128,433.4000147,562.1400
Ti-II316.2684983.915732,602.6265Ti- II542.027412,758.259731,207.5111
Ti-II316.94351215.832932,767.1961Ti-I548.293319,421.580037,659.9920
Ti-II319.17958744.340640,074.6707Ti-I549.167311,776.812029,986.1990
Ti-II320.34608710.567539,926.8192Ti-I551.587511,531.761029,661.2500
Ti- II321.919512,677.105043,740.7678Ti-I556.701918,037.213036,000.1480
Ti-II322.516812,774.816843,780.9533Ti-I564.570018,287.554036,000.1480
Ti-II323.01220.000030,958.5846Ti-I566.445420,006.039037,659.9920
Ti-II323.70538710.567539,602.8645Ti-I567.698618,593.947036,208.9290
Ti-II324.29180.000030,836.4250Ti-I576.792626,564.400043,901.6548
Ti-II325.3844225.703930,958.5846Ti-I578.758426,772.968044,051.3351
Ti-II326.252515,257.552745,908.6592Ti-I580.586926,910.709044,134.6580
Ti-II327.259110,024.800940,581.6301Ti-I586.80778602.344125,643.7010
Ti-II327.92329930.776640,425.7183Ti-II594.198965,095.974181,924.1270
Ti-II328.860115,265.700145,673.7641Ti-I595.480915,220.393032,013.5440
Ti-II330.97561087.356131,301.0653Ti-I598.01971000.000015,108.1110
Ti-II331.62769872.899040,027.2001Ti-II600.406765,186.868081,842.2440
Ti-II332.38901215.832931,301.0653Al-II704.402491,274.5000105,470.9300
Ti-II333.04111087.356131,113.6764Ti-I721.142311,776.812025,643.7010
Ti-II333.6150983.915730,958.5846Ti-I724.685111,639.810925,438.9080
Ti-I334.28360.000029,914.7370Ti-I725.370811,531.761025,317.8140
Ti-II335.0365393.445930,240.9396Ti-II729.933068,584.479282,284.3670
Ti-I336.2178170.132829,912.2860Ti-II731.531668,331.159982,001.1090
Ti- II337.376294.114229,734.6206O-I777.408373,768.200086,631.4540
Ti-II338.47300.000029,544.4540O-I794.9734101,135.4070113,714.4440
Ti-II339.554794.114229,544.4540Ti-I795.133812,118.393024,694.8920
Ti-II350.602244,914.873373,437.2269Ti-I798.101015,220.393027,750.1350
Ti-II351.184415,265.700143,740.7678Ti-I838.48346598.765018,525.0590
Ti-II352.125916,515.935944,914.8733Ti-I842.88236661.006018,525.0590
Ti-II353.641816,625.244144,902.4455Ti-I843.72726842.962018,695.1340
Ti-II359.70734897.717932,698.1022O-I844.868076,794.978088,631.1460
Table A2. The standard wavelength used in spectral validation with other calibration samples. Ei and Ek are the upper and lower energy levels of electron transitions, respectively.
Table A2. The standard wavelength used in spectral validation with other calibration samples. Ei and Ek are the upper and lower energy levels of electron transitions, respectively.
IonWavelength (nm)Ei (cm−1)Ek (cm−1)IonWavelength (nm)Ei (cm−1)Ek (cm−1)
Fe-II240.5162 862.6118 42,439.8511 Si-I390.6629 15,394.3700 40,991.8840
Fe-II240.5617 667.6829 42,237.0575 S-II393.4378 131,187.1900 156,604.1700
Fe-II241.1252 862.6118 42,334.8444 K-II393.5520 201,957.6000 227,367.2000
Na-II242.4442 331,186.7000 372,433.3000 Al-I394.5122 0.0000 25,347.7560
Fe-II242.4881 22,637.1950 63,876.3250 C-I396.2524 61,981.8321 87,218.2750
Si-I243.5893 6298.8500 47,351.5540 Al-I396.2641 112.0610 25,347.7560
Fe-II244.5256 20,830.5534 61,726.0690 Ca-II396.9591 0.0000 25,191.5100
Fe-II244.5847 41,968.0698 82,853.7040 Fe-I404.6955 11,976.2390 36,686.1760
Fe-II246.2028 26,055.4120 66,672.3360 K-I404.8356 0.0000 24,701.3820
C-I247.9310 21,648.0300 61,981.8321 Si-II407.7931 79,338.5000 103,860.7400
Fe-II248.3616 44,784.7859 85,048.6550 Fe-I407.9505 21,038.9870 45,551.7670
Na-II249.3900 268,762.9600 308,860.8000 Na-II408.8747 268,762.9600 293,220.3300
Fe-II249.9651 21,581.6151 61,587.2050 Al-III408.9765 178,470.3200 202,921.6000
Si-I250.7652 77.1150 39,955.0530 Si-II413.2059 79,355.0200 103,556.0300
Si-I251.6870 223.1570 39,955.0530 K-II418.7412 162,502.7000 186,383.8000
Si-I251.9960 77.1150 39,760.2850 Ca-I422.7918 0.0000 23,652.3040
Si-I252.4867 77.1150 39,683.1630 Al-II422.8006 121,483.5000 145,135.3100
Si-I252.9268 223.1570 39,760.2850 Fe-I422.8617 26,874.5500 50,522.9440
p-I253.6374 18,748.0100 58,174.3660 C-II426.8202 145,549.2700 168,978.3400
Fe-II253.9561 21,430.3564 60,807.2390 Fe-I427.2962 11,976.2390 35,379.2080
Fe-II253.9672 21,581.6151 60,956.7810 Ca-I430.3738 15,315.9430 38,551.5580
Ca-III254.2262 242,547.1900 281,882.2400 Ca-I431.9866 15,315.9430 38,464.8080
Fe-II255.0160 23,031.2829 62,244.5150 Fe-I432.6978 12,968.5540 36,079.3720
Fe-II255.0227 22,939.3512 62,151.5540 C-I435.0190 64,089.8990 87,077.4020
Si-III255.9963 165,765.0000 204,828.0600 Mg-II438.5869 80,619.5000 103,420.0000
Fe-II256.3304 7955.3186 46,967.4751 Fe-I441.6362 12,968.5540 35,611.6250
Fe-II256.4244 8391.9554 47,389.8090 Ca-I443.6202 15,210.0630 37,751.8670
Si-I256.4446 6298.8500 45,293.6290 Na-II445.5977 332,841.9300 355,283.7000
Mg-I257.5713 21,911.1780 60,735.3800 Na-II445.6481 332,841.9300 355,281.1600
Mg-I258.6327 21,870.4640 60,535.3400 Mg-II448.2383 71,490.1900 93,799.7500
Fe-II258.6649 0.0000 38,660.0537 Na-II453.0524 342,971.0000 365,043.5000
Fe-II260.0172 0.0000 38,458.9934 Na-II455.3050 331,873.9300 353,837.2300
Mg-I260.7398 21,911.1780 60,263.5830 Si-III455.3898 153,377.0500 175,336.2600
Fe-II260.7866 667.6829 39,013.2160 Ca-III455.4568 339,198.0900 361,154.0700
Na-II261.2591 293,220.3300 331,496.5100 Si-III456.9121 153,377.0500 175,263.1000
Fe-II261.8399 65,580.0650 103,771.3420 Na-II459.2222 308,860.8000 330,636.7500
Fe-II262.6450 384.7872 38,458.9934 K-I464.3175 0.0000 21,536.9880
Fe-II263.1831 862.6118 38,858.9696 Al-II464.9911 124,794.1300 146,299.9200
Si-I263.2066 15,394.3700 53,387.3340 Mg-I470.4307 35,051.2640 56,308.3810
Fe-II263.2107 667.6829 38,660.0537 Ca-III470.4917 323,003.5600 344,257.9200
Fe-II272.8191 25,428.7893 62,083.1180 C-I504.3203 64,090.9935 83,919.6632
Fe-II272.8346 8391.9554 45,044.1916 K-II505.7657 163,432.1000 183,204.1000
Fe-II274.0358 7955.3186 44,446.9051 C-I505.9088 69,744.0521 89,510.4600
Fe-II274.4008 8846.7837 45,289.8248 Mg-I516.8761 21,850.4050 41,197.4030
Fe-II274.4033 42,401.3198 78,844.0310 Mg-I517.4125 21,870.4640 41,197.4030
Fe-II274.9994 8680.4706 45,044.1916 Mg-I518.5048 21,911.1780 41,197.4030
Fe-II275.0134 8391.9554 44,753.8179 Ca-I527.1737 20,371.0000 39,340.0800
Na-II275.0451 332,841.9300 369,199.6000 Ca-I551.4512 23,652.3040 41,786.2760
Fe-II275.6551 7955.3186 44,232.5398 Mg-I552.9940 35,051.2640 53,134.6420
Fe-II276.8329 42,114.8380 78,237.7090 P-II558.9852 106,001.2500 123,890.8100
Mg-I278.0641 21,870.4640 57,833.4000 Ca-I559.0301 20,371.0000 38,259.1240
Mg-II279.1600 35,669.3100 71,491.0600 Si-II569.0396 114,414.5800 131,988.0500
Mg-II279.6352 0.0000 35,760.8800 Al-III569.8184 126,164.0500 143,713.5000
Mg-II279.8823 35,760.8800 71,490.1900 Al-III572.4318 126,164.0500 143,633.3800
Mg-II280.3531 0.0000 35,669.3100 Si-III574.1326 159,069.6100 176,487.1900
Al-II281.7014 59,852.0200 95,350.6000 Ca-I585.9074 23,652.3040 40,719.8470
Mg-I285.2964 0.0000 35,051.2640 Na-I589.1583 0.0000 16,973.3662
Si-I288.2423 6298.8500 40,991.8840 Na-I589.7558 0.0000 16,956.1703
Mg-II292.9490 35,669.3100 69,804.9500 C-I598.2894 64,086.9696 80,801.2889
Mg-II293.7369 35,760.8800 69,804.9500 S-II610.3955 114,804.3700 131,187.1900
Mg-I293.7600 21,850.4050 55,891.8000 Ca-I610.4412 15,157.9010 31,539.4950
Na-II298.5061 298,165.4400 331,665.5900 Ca-I612.3912 15,210.0630 31,539.4950
Fe-I302.1370 704.0070 33,801.5720 S-II612.5090 113,461.5400 129,787.8300
Al-I308.3046 0.0000 32,435.4530 Ca-I616.3878 15,315.9430 31,539.4950
Si-III308.7132 142,943.7400 175,336.2600 Ca-I617.1270 20,371.0000 36,575.1190
Na-II308.7953 298,165.4400 330,549.3500 Mg-III624.5745 548,720.7000 564,731.6000
Mg-I309.3884 21,870.4640 54,192.2940 Si-II634.8864 65,500.4700 81,251.3200
Mg-I309.7790 21,911.1780 54,192.2560 Si-II637.3133 65,500.4700 81,191.3400
Na-II315.0187 268,762.9600 300,507.1100 Ca-I644.0855 20,371.0000 35,896.8890
Ca-II315.9783 25,191.5100 56,839.2500 Ca-I645.1591 20,335.3600 35,835.4130
Mg-II316.6795 80,619.5000 112,197.1700 Ca-I646.4353 20,349.2600 35,818.7130
Na-II317.9975 299,189.9600 330,636.7500 Ca-I647.3450 20,371.0000 35,818.7130
Si-III323.4887 175,263.1000 206,176.0800 Ca-I649.5576 20,335.3600 35,730.4540
Mg-III336.2362 534,923.6000 564,664.6000 C-II657.9869 116,537.6500 131,735.5200
Ca-III337.3647 242,547.1900 272,188.7000 C-I658.0586 72,610.7353 87,806.9500
Fe-I357.1273 22,650.4160 50,651.6320 P-I671.9256 64,239.5910 79,122.1900
K-II358.7586 187,527.0000 215,400.9000 Ca-I671.9536 21,849.6340 36,731.6150
Al-III360.2954 115,958.5000 143,713.5000 Al-II704.4024 91,274.5000 105,470.9300
Fe-I368.7046 23,711.4560 50,833.4380 K-I766.7009 0.0000 13,042.8960
Mg-III370.7796 561,798.7000 588,768.9000 K-I770.1084 0.0000 12,985.1857
Al-III371.4179 143,713.5000 170,637.3500 O-I777.4083 73,768.2000 86,631.4540
C-I373.6840 60,352.6584 87,113.2390 Mg-II789.8539 80,650.0200 93,310.5900
Ca-II373.7964 25,414.4000 52,166.9300 Ca-III790.0592 327,922.8700 340,580.1500
Al-II373.9074 105,470.9300 132,215.5170 O-I794.9354 101,147.5260 113,727.1650
S-II373.9261 133,360.8600 160,104.1100 O-I794.9734 101,135.4070 113,714.4440
Fe-I375.0551 7376.7640 34,039.5160 Na-I818.5505 16,956.1703 29,172.8870
Fe-I376.1118 19,390.1680 45,978.0080 Ca-III819.7588 347,344.3700 359,543.0800
Si-III379.7202 175,263.1000 201,598.2800 O-I822.4084 101,135.4070 113,294.8160
Si-III380.7606 175,336.2600 201,599.4800 K-I825.2432 21,534.6800 33,652.3200
Fe-I380.8618 17,927.3820 44,183.6280 K-I825.4004 21,536.9880 33,652.3200
Mg-I383.3391 21,870.4640 47,957.0270 O-I844.8568 76,794.9780 88,631.3030
Mg-I383.9381 21,911.1780 47,957.0450 O-I844.8680 76,794.9780 88,631.1460
Si-II385.7111 55,325.1800 81,251.3200 Ca-II850.0358 13,650.1900 25,414.4000
Si-II386.3691 55,309.3500 81,191.3400

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Figure 1. RMSE of reference spectrum calibrated with different drift amounts. RMSE of the corrected reference spectrum varies with the number of drifted pixels. (ac) represent the change law of RMSE in the CH-1, CH-2 and CH-3, respectively.
Figure 1. RMSE of reference spectrum calibrated with different drift amounts. RMSE of the corrected reference spectrum varies with the number of drifted pixels. (ac) represent the change law of RMSE in the CH-1, CH-2 and CH-3, respectively.
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Figure 2. On-board spectra before and after drift correction using the reference spectrum as a reference. The reference spectrum is the spectrum of the Ti-alloy collected by the MarSCoDe in a simulated Martian environment before launch. (ac) show the three channels’ spectra of the on-board Ti-alloy before and after Δ p 2 correction and corresponding reference spectrum. The position of the matching peaks is circled. The spectrum intensity is offset for clarity. (df) show the RMSE change diagram of the on-board spectrum during the translation iterative. The spectrum was collected by the MarSCoDe on 25 June 2021.
Figure 2. On-board spectra before and after drift correction using the reference spectrum as a reference. The reference spectrum is the spectrum of the Ti-alloy collected by the MarSCoDe in a simulated Martian environment before launch. (ac) show the three channels’ spectra of the on-board Ti-alloy before and after Δ p 2 correction and corresponding reference spectrum. The position of the matching peaks is circled. The spectrum intensity is offset for clarity. (df) show the RMSE change diagram of the on-board spectrum during the translation iterative. The spectrum was collected by the MarSCoDe on 25 June 2021.
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Figure 3. The change trend of RMSE with the number of iterations in the iteration process of the PSO algorithm. Blue, orange and green represent the spectra of the first, second and third channels, respectively.
Figure 3. The change trend of RMSE with the number of iterations in the iteration process of the PSO algorithm. Blue, orange and green represent the spectra of the first, second and third channels, respectively.
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Figure 4. The spectrum of on-board Ti-alloy before and after wavelength drift correction using the MGR approach and PSO approach. (ac) represent the spectrum in the CH-1, CH-2 and CH-3, respectively. (df) are the local spectra in the three channels, respectively. The spectrum intensity is offset for clarity.
Figure 4. The spectrum of on-board Ti-alloy before and after wavelength drift correction using the MGR approach and PSO approach. (ac) represent the spectrum in the CH-1, CH-2 and CH-3, respectively. (df) are the local spectra in the three channels, respectively. The spectrum intensity is offset for clarity.
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Figure 5. The before and after drift correction spectra of 11 calibration samples obtained by using MGR and PSO. (A) is the spectrum in the three channels, and (B) is the local spectrum. The vertical dashed lines represent the standard spectra. The blue lines represent the spectra corrected by the MGR method. The orange lines represent the spectra corrected by the PSO method. The red lines represent the uncorrected on-board spectra. The spectrum intensity is offset for clarity.
Figure 5. The before and after drift correction spectra of 11 calibration samples obtained by using MGR and PSO. (A) is the spectrum in the three channels, and (B) is the local spectrum. The vertical dashed lines represent the standard spectra. The blue lines represent the spectra corrected by the MGR method. The orange lines represent the spectra corrected by the PSO method. The red lines represent the uncorrected on-board spectra. The spectrum intensity is offset for clarity.
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Table 1. On-board LIBS spectral information for drift correction. CAL indicates that the sample is a calibration target.
Table 1. On-board LIBS spectral information for drift correction. CAL indicates that the sample is a calibration target.
Martian DayUTC TimeData TypeTarget No.Target NamePressure (Pa)Temperature (°C)
Sol 412021-06-25T03:15:49CALLC-008Ti-alloy825.46−6.98
Sol 412021-06-25T03:17:15CALLC-005Norite 825.46−6.98
Sol 412021-06-25T03:18:37CALLC-003Andesite825.46−6.98
Sol 432021-06-26T23:26:17CALLC-008Ti-alloy833.07−27.53
Sol 432021-06-26T23:27:43CALLC-011Basalt833.07−27.53
Sol 452021-06-29T07:05:03CALLC-008Ti-alloy826.47−11.28
Sol 452021-06-29T07:06:29CALLC-010Olivine826.47−11.28
Sol 452021-06-29T07:07:51CALLC-009Montmorillonite826.47−11.28
Sol 472021-07-01T02:03:37CALLC-008Ti-alloy830.68−30.41
Sol 472021-07-01T02:05:03CALLC-012K-feldspar830.68−30.41
Sol 472021-07-01T02:06:25CALLC-001Gypsum830.68−30.41
Sol 582021-07-12T08:45:41CALLC-008Ti-alloy824.74−30.78
Sol 582021-07-12T08:47:07CALLC-007Dolomite824.74−30.78
Sol 582021-07-12T08:48:29CALLC-004Nontronite824.74−30.78
Sol 652021-07-19T16:15:56CALLC-008Ti-alloy814.315−12.44
Sol 652021-07-19T16:17:22CALLC-002Hypersthene814.315−12.44
Sol 652021-07-19T16:18:44CALLC-006Apatite814.315−12.44
Table 2. The wavelength calibration coefficient in the three channels of the spectrometer (referenced from the Level 2B data).
Table 2. The wavelength calibration coefficient in the three channels of the spectrometer (referenced from the Level 2B data).
Channel a 0 a 1 a 2
CH-1223.46160.0682−8.1556 × 10−7
CH-276.75350.1386−1.1347 × 10−6
CH-3−257.64740.2225−2.1432 × 10−6
Table 3. Δ p 2 and RMSE of Ti-alloy spectra collected by the MarSCoDe at different times.
Table 3. Δ p 2 and RMSE of Ti-alloy spectra collected by the MarSCoDe at different times.
Martian DayCH-1 (Pixel)RMSE (Pixel)CH-2 (Pixel)RMSE (Pixel)CH-3 (Pixel)RMSE (Pixel)
Sol 41−0.240.106−1.430.119−12.720.147
Sol 43−3.580.158−3.450.116−16.650.173
Sol 45−0.340.108−1.570.117−12.890.139
Sol 47−3.670.156−3.510.114−16.780.170
Sol 58−4.040.158−3.910.119−16.970.170
Sol 65−1.520.144−2.250.131−15.480.176
Mean0.1380.1190.163
Table 4. The wavelength calibration coefficients of different Ti-alloy spectra corrected by PSO.
Table 4. The wavelength calibration coefficients of different Ti-alloy spectra corrected by PSO.
Martian DayChannel a 0 a 1 a 2
Sol 41CH-1223.51970.0682−8.3685 × 10−7
CH-277.08730.1383−1.0898 × 10−6
CH-3−257.69250.2212−1.9791 × 10−6
Sol 43CH-1223.30080.06822−8.3661 × 10−7
CH-276.85820.1383−1.0852 × 10−6
CH-3−257.94390.2209−1.9492 × 10−6
Sol 45CH-1223.51260.0682−8.3584 × 10−7
CH-277.07610.1383−1.0889 × 10−6
CH-3−255.29520.2201−1.8639 × 10−6
Sol 47CH-1223.29760.0682−8.3146 × 10−7
CH-276.87820.1382−1.0789 × 10−6
CH-3−260.36010.2221−2.0919 × 10−6
Sol 58CH-1223.27420.0682−8.3067 × 10−7
CH-276.85630.1382−1.0751 × 10−6
CH-3−258.12590.2210−1.9634 × 10−6
Sol 65CH-1223.43290.0682−8.3679 × 10−7
CH-276.92650.1383−1.0990 × 10−6
CH-3−253.59510.2191−1.7539 × 10−6
Table 5. Total drift amount and RMSE by MGR method of Ti-alloy spectra and the number of characteristic peaks used in the spectral correction of each channel.
Table 5. Total drift amount and RMSE by MGR method of Ti-alloy spectra and the number of characteristic peaks used in the spectral correction of each channel.
Martian DayCH-1CH-2CH-3
Drift Amount (Pixel)Number of Characteristic LinesDrift Amount (Pixel)Number of Characteristic LinesDrift Amount (Pixel)Number of Characteristic Lines
Sol 41−0.2468−1.4350−12.7223
Sol 43−3.5868−3.4529−16.6524
Sol 45−0.3470−1.5753−12.8927
Sol 47−3.6778−3.5151−16.7842
Sol 58−4.0475−3.9150−16.9745
Sol 65−1.5269−2.2554−15.4824
Table 6. The absolute mean error (AME) and RMSE of the corrected Ti-alloy spectrum. Two methods of MGR and PSO are used to correct the on-board spectrum.
Table 6. The absolute mean error (AME) and RMSE of the corrected Ti-alloy spectrum. Two methods of MGR and PSO are used to correct the on-board spectrum.
Martian DayMethodCH-1 (nm)CH-2 (nm)CH-3 (nm)
AMERMSEAMERMSEAMERMSE
Sol 41MGR0.0150.0190.0210.0290.0310.040
PSO0.0170.0240.0290.0380.0160.021
Sol 43MGR0.0150.0190.0210.0290.0400.050
PSO0.0170.0240.0310.0380.0230.029
Sol 45MGR0.0150.0190.0230.0310.0400.051
PSO0.0180.0240.0300.0390.0250.030
Sol 47MGR0.0170.0210.0230.0300.0450.057
PSO0.0190.0250.0320.0400.0300.035
Sol 58MGR0.0160.0200.0230.0300.0470.058
PSO0.0180.0250.0330.0410.0240.029
Sol 65MGR0.0150.0190.0210.0280.0350.045
PSO0.0130.0150.0280.0350.0090.010
MeanMGR0.016 0.020 0.022 0.030 0.040 0.050
PSO0.017 0.023 0.031 0.039 0.021 0.026
Table 7. The absolute mean error (AME) and RMSE of corrected on-board spectra and the number of characteristic peaks used in the spectral correction of each channel. In the table, “Number” represents the number of characteristic peaks.
Table 7. The absolute mean error (AME) and RMSE of corrected on-board spectra and the number of characteristic peaks used in the spectral correction of each channel. In the table, “Number” represents the number of characteristic peaks.
SampleCorrection MethodCH-1CH-2CH-3
AME (nm)RMSE (nm)NumberAME (nm)RMSE (nm)NumberAME (nm)RMSE (nm)Number
NoriteMGR0.0130.018500.0380.045150.0410.04721
PSO0.0130.018500.0380.045150.0400.04621
AndesiteMGR0.0130.006490.0080.044140.0370.04417
PSO0.0120.017490.0470.054140.0380.04717
BasaltMGR0.0130.017430.0320.036240.0390.04826
PSO0.0130.018430.0400.047240.0490.06326
OlivineMGR0.0110.016340.0350.038180.0410.04511
PSO0.0110.016340.0390.046180.0400.05211
MontmorilloniteMGR0.0130.018260.0350.039150.0440.05218
PSO0.0140.020260.0440.052150.0370.05318
K-feldspar MGR0.0110.015210.0420.047290.0250.03717
PSO0.0110.015210.0480.055290.0850.10617
GypsumMGR0.0120.01730.0380.04750.0420.04820
PSO0.0120.01730.0410.04950.0690.08920
DolomiteMGR0.0130.017180.0270.032130.0460.05120
PSO0.0120.017180.0270.032130.0520.06520
NontroniteMGR0.0140.018290.0440.051130.0370.04417
PSO0.0120.017290.0460.053130.0370.04617
HyperstheneMGR0.0110.014350.0420.050330.0400.04627
PSO0.0110.015350.0440.053330.0660.08727
ApatiteMGR0.0110.01460.0270.03190.0430.04923
PSO0.0100.01460.0300.03490.0550.07523
MeanMGR0.012 0.015 0.033 0.042 0.040 0.046
PSO0.012 0.017 0.040 0.047 0.052 0.066
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Jia, L.; Liu, X.; Xu, W.; Xu, X.; Li, L.; Cui, Z.; Liu, Z.; Shu, R. Initial Drift Correction and Spectral Calibration of MarSCoDe Laser-Induced Breakdown Spectroscopy on the Zhurong Rover. Remote Sens. 2022, 14, 5964. https://doi.org/10.3390/rs14235964

AMA Style

Jia L, Liu X, Xu W, Xu X, Li L, Cui Z, Liu Z, Shu R. Initial Drift Correction and Spectral Calibration of MarSCoDe Laser-Induced Breakdown Spectroscopy on the Zhurong Rover. Remote Sensing. 2022; 14(23):5964. https://doi.org/10.3390/rs14235964

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Jia, Liangchen, Xiangfeng Liu, Weiming Xu, Xuesen Xu, Luning Li, Zhicheng Cui, Ziyi Liu, and Rong Shu. 2022. "Initial Drift Correction and Spectral Calibration of MarSCoDe Laser-Induced Breakdown Spectroscopy on the Zhurong Rover" Remote Sensing 14, no. 23: 5964. https://doi.org/10.3390/rs14235964

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