A “Skylight” Simulator for HWIL Simulation of Hyperspectral Remote Sensing

Even though digital simulation technology has been widely used in the last two decades, hardware-in-the-loop (HWIL) simulation is still an indispensable method for spectral uncertainty research of ground targets. However, previous facilities mainly focus on the simulation of panchromatic imaging. Therefore, neither the spectral nor the spatial performance is enough for hyperspectral simulation. To improve the accuracy of illumination simulation, a new dome-like skylight simulator is designed and developed to fit the spatial distribution and spectral characteristics of a real skylight for the wavelength from 350 nm to 2500 nm. The simulator’s performance was tested using a spectroradiometer with different accessories. The spatial uniformity is greater than 0.91. The spectral mismatch decreases to 1/243 of the spectral mismatch of the Imagery Simulation Facility (ISF). The spatial distribution of radiance can be adjusted, and the accuracy of the adjustment is greater than 0.895. The ability of the skylight simulator is also demonstrated by comparing radiometric quantities measured in the skylight simulator with those in a real skylight in Beijing.

[1]  Patrick Hostert,et al.  Simulation of Multitemporal and Hyperspectral Vegetation Canopy Bidirectional Reflectance Using Detailed Virtual 3-D Canopy Models , 2014, IEEE Transactions on Geoscience and Remote Sensing.

[2]  Shuai Li,et al.  Estimating mineral abundances of clay and gypsum mixtures using radiative transfer models applied to visible-near infrared reflectance spectra , 2016 .

[3]  Nadine Gobron,et al.  The fourth phase of the radiative transfer model intercomparison (RAMI) exercise: Actual canopy scenarios and conformity testing , 2015 .

[4]  Peter Takacs,et al.  Characterization and acceptance testing of fully depleted thick CCDs for the large synoptic survey telescope , 2016, Astronomical Telescopes + Instrumentation.

[5]  Nesrin Ozalp,et al.  Description and characterization of an adjustable flux solar simulator for solar thermal, thermochemical and photovoltaic applications , 2014 .

[6]  Stefan Nowy,et al.  Impact of Improved Calibration of a NEO HySpex VNIR-1600 Sensor on Remote Sensing of Water Depth , 2015, IEEE Transactions on Geoscience and Remote Sensing.

[7]  K. Itten,et al.  Advanced radiometry measurements and Earth science applications with the Airborne Prism Experiment (APEX) , 2015 .

[8]  Richard V. Morris,et al.  Mineralogical and chemical characterization of lunar highland soils: Insights into the space weathering of soils on airless bodies , 2010 .

[9]  Zhao Yingjun,et al.  Regional-scale mineral mapping using ASTER VNIR/SWIR data and validation of reflectance and mineral map products using airborne hyperspectral CASI/SASI data , 2014, Int. J. Appl. Earth Obs. Geoinformation.

[10]  R. Clark,et al.  Hapke modeling of Rhea surface properties through Cassini-VIMS spectra , 2011 .

[11]  Bill Beck.  Lasers light up the silver screen , 2014, IEEE Spectrum.

[12]  Jean-Yves Tourneret,et al.  Nonlinearity Detection in Hyperspectral Images Using a Polynomial Post-Nonlinear Mixing Model , 2013, IEEE Transactions on Image Processing.

[13]  Na Li,et al.  Simulation of Hyperspectral Scene with Full Adjacency Effect , 2008, IGARSS.

[14]  D. Liu,et al.  AN IMPROVED RADIATIVE TRANSFER MODEL FOR ESTIMATING MINERAL ABUNDANCE OF IMMATURE AND MATURE LUNAR SOILS , 2012 .

[15]  Qianjun Zhao,et al.  Examining Land Use and Land Cover Spatiotemporal Change and Driving Forces in Beijing from 1978 to 2010 , 2014, Remote. Sens..

[16]  Lawrence A. Maver,et al.  Multispectral imagery simulation , 1993, Electronic Imaging.

[17]  S. L. Ho,et al.  Interpolation simulation model of steady-state and dynamic characteristics for car automotive system , 2009 .

[18]  Zhiwei Sun,et al.  Time-resolved spectra of solar simulators employing metal halide and xenon arc lamps , 2015 .

[19]  Luis Guanter,et al.  EeteS—The EnMAP End-to-End Simulation Tool , 2012, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[20]  John R. Schott,et al.  Remote Sensing: The Image Chain Approach , 1996 .

[21]  Shasha Yang,et al.  Mineral mapping using ETM+,ASTER and Hyperion imagery in the Honghai area of Hami in Xinjiang, China , 2013 .

[22]  Hanscom Afb.  Air Force Research Laboratory Space Vehicles Directorate , 2017 .

[23]  Cheng Jiang,et al.  Simulation of hyperspectral radiance images with quantification of adjacency effects over rugged scenes , 2013 .

[24]  Yan Zhou,et al.  Community Global Observing System Simulation Experiment (OSSE) Package (CGOP): Description and Usage , 2016 .

[25]  Sohyun Kim,et al.  Target size prediction and verification by geometrical analysis and SE-WORKBENCH for ground target detection , 2014, 2014 14th International Conference on Control, Automation and Systems (ICCAS 2014).

[26]  Yi Cen,et al.  A nonlinear spectral unmixing method for abundance retrieval of mineral mixtures , 2016, Commercial + Scientific Sensing and Imaging.

[27]  Sabine Chabrillat,et al.  Prediction of Common Surface Soil Properties Based on Vis-NIR Airborne and Simulated EnMAP Imaging Spectroscopy Data: Prediction Accuracy and Influence of Spatial Resolution , 2016, Remote. Sens..

[28]  Edward J. Knight,et al.  Landsat-8 Operational Land Imager Design, Characterization and Performance , 2014, Remote. Sens..

[29]  Huijie Zhao,et al.  A Digital Sensor Simulator of the Pushbroom Offner Hyperspectral Imaging Spectrometer , 2014, Sensors.

[30]  Balvinder Kaur,et al.  Digital imaging and remote sensing image generator (DIRSIG) as applied to NVESD sensor performance modeling , 2016, SPIE Defense + Security.

[31]  A. K. Sen,et al.  Laboratory light scattering from regolith surface and simulation of data by Hapke model , 2015, 1512.02176.

[32]  Tran Quoc Khanh.  Lighting Quality for Automotive Lighting , 2014 .