Minimum Noise Fraction analysis of ExoMars/TGO-NOMAD LNO channel nadir data: SNR enhancement and application

The Nadir and Occultation for MArs Discovery (NOMAD, Neefs et al., 2015) instrument suite on board the Exomars Trace Gas Orbiter (TGO) spacecraft is capable to observe the Martian atmosphere at high spectral resolution with different observing modes. The data acquired in nadir observing geometry by the infrared Limb, Nadir and Occultation (LNO) channel of NOMAD are characterized by a signal to noise ratio (SNR) that is mostly limited by the instrument’s operative temperature, in turn impacting integration times.

In this study we apply to LNO nadir data the Minimum Noise Fraction (MNF) technique (Green et al., 1988; Lee et al., 1990; Boardman and Kruse, 1994), usually adopted to enhance the SNR of remotely sensed hyperspectral imaging datasets (e.g. Lee et al., 1990; Amato et al, 2009; Bjorgan and Randeberg, 2015; Luo et al., 2016). In practice, the MNF projects the original data in a space in which the noise component is minimized. Such a projection is achieved by means of two consecutive Principal Component (PC) transforms (see Jolliffe and Cadima, 2016, for a comprehensive review) providing eigenvalues for the data reconstruction that are ordered with increasing noise.

As first step of the analysis, we perform tests on ensembles of synthetic spectra in order to evaluate the theoretical performances of the technique in different frameworks of analysis. For example, we investigate the application of the MNF on spectral features characterized by different depth, width, correlation with other bands, and spatial dependencies, verifying that all these factors impact its effectiveness. Then, we evaluate the MNF performances on specific LNO spectral orders, in order to assess the SNR improvement for studies related to the Martian surface and aerosols/clouds (e.g. Oliva et al., 2022) and to trace gases.

A limiting factor in the SNR enhancement is the presence of systematic noise linked to spectral artifacts introduced by the MNF itself. In order to remove these artifacts, the number of transform eigenvalues, and hence the noise, needs to be increased in the reconstruction of the denoised observations. Nevertheless, as result from this preliminary analysis, we report an average SNR improvement of about 20% and reaching a maximum of 50%.

Acknowledgements

ExoMars is a space mission of the European Space Agency (ESA) and Roscosmos. The NOMAD experiment is led by the Royal Belgian Institute for Space Aeronomy (IASB-BIRA), assisted by Co-PI teams from Spain (IAA-CSIC), Italy (INAF-IAPS), and the United Kingdom (The Open University). This project acknowledges funding by the Belgian Science Policy Office (BELSPO), with the financial and contractual coordination by the ESA Prodex Office (PEA 4000103401, 4000121493), by Spanish Ministry of Science and Innovation (MCIU) and by European funds under grants PGC2018-101836-BI00 and ESP2017-87143-R (MINECO/FEDER), as well as by UK Space Agency through grants ST/V002295/1, ST/V005332/1 and ST/S00145X/1  and Italian Space Agency through grant 2018-2-HH.0. This work was supported by the Belgian Fonds de la Recherche Scientifique – FNRS under grant number 30442502 (ET_HOME). The IAA/CSIC team acknowledges financial support from the State Agency for Research of the Spanish MCIU through the ‘Center of Excellence Severo Ochoa’ award for the Instituto de Astrofísica de Andalucía (SEV-2017-0709). US investigators were supported by the National Aeronautics and Space Administration. Canadian investigators were supported by the Canadian Space Agency.

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