The C1XS X-ray Spectrometer on Chandrayaan-1

Grandé, M.; Maddison, B. J.; Howe, C.; Kellett, B. J.; Sreekumar, P.; Huovelin, J.; Crawford, Ian; d’Uston, C.; Smith, David R.; Anand, M.; Bhandari, N.; Cook, A. C.; Fernandes, V. A.; Foing, B. H.; Gasnaut, O.; Goswami, J. N.; Holland, Andrew D.; Joy, K. H.; Kochney, D; Lawrence, D. J.; Maurice, S.; Okada, T.; Narendranath, S.; Pieters, C. M.; Rothery, David A.; Russell, S. S.; Shrivastava, Anurag; Swinyard, Bruce; Wilding, Martin C.; Wieczorek, M. A.

doi:10.1016/j.pss.2009.01.016

Cited by 55 publications

(17 citation statements)

References 11 publications

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“…For the analysis of Earth‐based and orbital radar data, several regolith parameters can be estimated using other data sets. For example, the FeO+TiO 2 content (and hence the loss tangent) of the lunar regolith can be obtained from gamma ray, X‐ray or optical spectroscopy data [ Lucey et al , 2000; Lawrence et al , 2002; Grande et al , 2009], and the large‐scale surface slope and roughness can be obtained by high‐resolution surface topography, such as from laser altimetry [ Araki et al , 2009; Huang et al , 2010; Smith et al , 2010]. The most difficult parameters to constrain from nonradar observations are the size‐frequency distribution of buried rocks, the shape of the buried rocks, the subsurface roughness, and regolith thickness.…”

Section: Simulation Results and Analysismentioning

confidence: 99%

Modeling polarimetric radar scattering from the lunar surface: Study on the effect of physical properties of the regolith layer

Wieczorek

Heggy

2011

J. Geophys. Res.

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[1] A theoretical model for radar scattering from the lunar regolith using the vector radiative transfer theory for random media has been developed in order to aid in the interpretation of Mini-SAR data from the Chandrayaan-1 and Lunar Reconnaissance Orbiter missions. The lunar regolith is represented as a homogeneous fine-grained layer with rough upper and lower parallel interfaces that possesses embedded inclusions with a different dielectric constant. Our model considers five scattering mechanisms in the regolith layer: diffuse scattering from both the surface and subsurface, volume scattering from buried inclusions, and the interactions of scattering between buried inclusions and the rough interfaces (both the lunar surface and subsurface). Multiple scattering between buried inclusions and coherent backscatter opposite effect are not considered in the current model. The modeled radar scattering coefficients are validated using numerical finite difference time domain simulations and are compared with incident angle-averaged Earth-based radar observations of the Moon. Both polarized and depolarized radar backscattering coefficients and the circular polarization ratio (CPR) are calculated as a function of incidence angle, regolith thickness, surface and subsurface roughness, surface slope, abundance and shape of buried rocks, and the FeO+TiO 2 content of the regolith. Simulation results show that the polarized (opposite sense) radar echo strength at S and X bands is mostly dominated by scattering from the rough surface and buried rocks, while the depolarized (same sense) radar echo strength is dominated by scattering from buried rocks or ice inclusions. Finally, to explore the expected polarimetric signature of ice in the polar permanently shadowed areas, four parametric regolith models are considered and the possibility of detecting diffuse ice inclusions by the CPR is addressed. Our study suggests that detection of ice inclusions at the lunar poles using solely the CPR will be difficult given the small dielectric contrast between the regolith and ice.Citation: Fa, W., M. A. Wieczorek, and E. Heggy (2011), Modeling polarimetric radar scattering from the lunar surface: Study on the effect of physical properties of the regolith layer,

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Section: Simulation Results and Analysismentioning

confidence: 99%

Modeling polarimetric radar scattering from the lunar surface: Study on the effect of physical properties of the regolith layer

Wieczorek

Heggy

2011

J. Geophys. Res.

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“…C1XS (Howe et al, 2009;Grande et al, 2009), onboard Chandrayaan-1, was designed to map the abundances of major rock-forming elements on the lunar surface using the XRF technique. The extended solar minimum that prevailed during the Chandrayaan-1 mission time-frame (Nov'08 -Aug'09), left C1XS with only a handful of solar flares (a few C, B and A class flares) during which quantitative analysis could be carried out.…”

Section: Overview Of C1xsmentioning

confidence: 99%

“…Gamma-ray spectroscopy is also used to record gamma-ray spectra from rock-forming and radio-active elements (Lawrence et al, 1998). X-ray fluorescence (XRF) spectroscopy through remote sensing has a long history in studying the chemical composition of atmosphere-free solar system bodies (for example, Apollo 15 (1971), Apollo 16 (1972 (Adler & Gerard, 1972;Adler et al, 1973a,b), Smart-1 (2003) (Grande et al, 2003), Kaguya (2007) (Okada et al, 2008), Change-1 (2007) (Huixian et al, 2005) and Chandrayaan-1 (2008) (Grande et al, 2009) for the Moon, Near Earth Asteroid Rendezvous (NEAR) (1996) for the asteroid Eros (Trombka, 2000;Nittler et al, 2001), HAYABUSA (2003) for the asteroid 25143 Itokawa (Okada et al, 2006)). Solar X-rays excite surface elements of these bodies to yield characteristic emission lines.…”

Section: Introductionmentioning

confidence: 99%

C1XS results—First measurement of enhanced sodium on the lunar surface

Athiray

Narendranath

Sreekumar

et al. 2014

Planetary and Space Science

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We describe the first unambiguous evidence of enhanced Sodium on the lunar surface revealed by the Chandrayaan-1 X-ray Spectrometer (C1XS). The C1XS onboard the Chandrayaan-1 spacecraft was designed to map the surface elemental chemistry of the Moon using the X-ray fluorescence (XRF) technique. During the nine months of remote sensing observations (Nov'2008-Aug'2009), C1XS measured XRF emission from the Moon under several solar flare conditions. A summary of entire C1XS observations and data selection methods are presented. Surface elemental abundances of major rock-forming elements viz., Mg, Al, Si and Ca as well as Na derived from C1XS data corresponding to certain nearside regions of the Moon are reported here. We also present a detailed description of the analysis techniques including derivation of XRF line fluxes and conversion to elemental abundances. The derived abundances of Na (2-3 wt%) are significantly higher than what has been known from earlier studies. We compare the surface chemistry of C1XS observed regions with the highly silicic compositions (intermediate plagioclase) measured by the Diviner Radiometer instrument onboard Lunar Reconnaissance Orbiter(LRO) in those regions.

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“…An array of twenty-four SCDs (CCD54) with a geometric area of ∼1 cm 2 each was used in the Chandrayaan-1 X-ray Spectrometer (C1XS) experiment Grande et al 2009) onboard the Chandrayaan-1 spacecraft. Chandrayaan-1 was launched successfully on 28 October 2008 with eleven scientific experiments to study the Moon in multiwavelengths.…”

Section: Introductionmentioning

confidence: 99%

Simulating charge transport to understand the spectral response of Swept Charge Devices

Athiray

Sreekumar

Narendranath

et al. 2015

A&A

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Context. Swept Charge Devices (SCD) are novel X-ray detectors optimized for improved spectral performance without any demand for active cooling. The Chandrayaan-1 X-ray Spectrometer (C1XS) experiment onboard the Chandrayaan-1 spacecraft used an array of SCDs to map the global surface elemental abundances on the Moon using the X-ray fluorescence (XRF) technique. The successful demonstration of SCDs in C1XS spurred an enhanced version of the spectrometer on Chandrayaan-2 using the next-generation SCD sensors. Aims. The objective of this paper is to demonstrate validation of a physical model developed to simulate X-ray photon interaction and charge transportation in a SCD. The model helps to understand and identify the origin of individual components that collectively contribute to the energy-dependent spectral response of the SCD. Furthermore, the model provides completeness to various calibration tasks, such as generating spectral matrices (RMFs -redistribution matrix files), estimating efficiency, optimizing event selection logic, and maximizing event recovery to improve photon-collection efficiency in SCDs. Methods. Charge generation and transportation in the SCD at different layers related to channel stops, field zones, and field-free zones due to photon interaction were computed using standard drift and diffusion equations. Charge collected in the buried channel due to photon interaction in different volumes of the detector was computed by assuming a Gaussian radial profile of the charge cloud. The collected charge was processed further to simulate both diagonal clocking read-out, which is a novel design exclusive for SCDs, and event selection logic to construct the energy spectrum. Results. We compare simulation results of the SCD CCD54 with measurements obtained during the ground calibration of C1XS and clearly demonstrate that our model reproduces all the major spectral features seen in calibration data. We also describe our understanding of interactions at different layers of SCD that contribute to the observed spectrum. Using simulation results, we identify the origin of different spectral features and quantify their contributions.

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The C1XS X-ray Spectrometer on Chandrayaan-1

Cited by 55 publications

References 11 publications

Modeling polarimetric radar scattering from the lunar surface: Study on the effect of physical properties of the regolith layer

Modeling polarimetric radar scattering from the lunar surface: Study on the effect of physical properties of the regolith layer

C1XS results—First measurement of enhanced sodium on the lunar surface

Simulating charge transport to understand the spectral response of Swept Charge Devices

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