Generally available satellite images, e. g. from the MODIS sensor, provide data in spectral bands, which are suitable for
remote sensing applications and earth surface observations. However, for some applications different bands as well as
specific cloud formations for a certain region may be of interest, thus making the simulation of background data
essential. Therefore, the software MATISSE ("Advanced Modeling of the Earth for Environment and Scenes
Simulation") proved to be the appropriate tool. MATISSE is an infrared background scene generator developed by
ONERA for computing natural background spectral radiance images including atmosphere, sea, land and high and low
altitude clouds. In order to validate the model, comparisons with MODIS satellite data have been carried out using
images in available spectral bands. The investigations comprised selected surface structures like sea, desert, lowland
(dry) and highlands (humid). In general, the results on radiance images show a good correlation between MODIS image
and the MATISSE-simulation.
This paper focuses on comparing results between simulated MATISSE radiance images and the MODIS observations.
Based on this, possible sources of error and the limits of the model are discussed.
MATISSE (Advanced Modeling of the Earth for Environment and Scenes Simulation) is an infrared background scene
generator developed for computing natural background spectral radiance images. The code also provides atmospheric
radiatives quantities along lines of sight. Spectral bandwidth ranges from 0.4 to 14 μm. Natural backgrounds include
atmosphere, sea, land and high and low altitude clouds. The new version MATISSE-v2.0, released this year, has been
designed to treat spatial multi resolution in the generated images in order to be able to reach metric spatial variability in
pixels footprints. Moreover, MATISSE-v2.0 includes a new sea surface radiance model (water waves and surface optical
properties) which depends on wind speed, wind direction and fetch value. Preliminary validations using radiometric
measurements have been conducted concerning sea radiances and give promising results. In order to go further in the
validation process of MATISSE-v2.0, comparisons with MODIS satellite images have been led. The results of
comparing the simulated MATISSE images radiances with the MODIS observations show that the code is performing
well. This paper gives a description of MATISSE-v2.0 new functionalities and focus on first results on comparison
between MATISSE/MODIS images radiances.
Existing computer simulations of aircraft infrared signature do not account for the dispersion induced by uncertainty
on input data, such as aircraft aspect angles and meteorological conditions. As a result, they are of little
use to estimate the detection performance of IR optronic systems: in that case, the scenario encompasses a lot
of possible situations that can not be singly simulated. In this paper, we focus on low resolution infrared sensors
and we propose a methodological approach for predicting simulated infrared signature dispersion of poorly
known aircraft, and performing aircraft detection and classification on the resulting set of low resolution infrared
images. It is based on a Quasi-Monte Carlo survey of the code output dispersion, on a new detection test taking
advantage of level sets estimation, and on a maximum likelihood classification taking advantage of Bayesian
dense deformable template models estimation.
Airborne infrared limb-viewing sensors may be used as surveillance devices in order to detect dim military targets. These
systems' performances are limited by the inhomogeneous background in the sensor field of view which impacts strongly
on target detection probability. Consequently, the knowledge of the radiance small-scale angular fluctuations and their
statistical properties is required to assess the sensors' detection capacity. In the stratosphere and in clear-sky conditions,
the structured background is mainly due to inertia-gravity-wave and turbulence-induced temperature and density spatial
fluctuations. Moreover, in the particular case of water vapor absorption bands, the mass fraction fluctuations play a non
negligible role on the radiative field. Thereby, considering as a first approximation the temperature field and the water
vapor field as stationary stochastic processes, the radiance autocorrelation function (ACF) can be expressed as a function
of the temperature ACF and the water vapor mass fraction ACF.
This paper presents the model developed to compute the two-dimensional radiance angular ACF. This model requires the
absorption coefficients and their temperature derivatives, which were calculated by a line-by-line code dedicated to water
vapor absorption bands. An analytical model was also developed for a simple homogeneous case, in order to validate the
average values and the radiance fluctuation variance. The numerical model variance and variance distribution are also
compared to SAMM2 outputs, the AFRL radiance structure computation code. The influence of water vapor fluctuations
on radiance fluctuations is also discussed.
MATISSE which acronym means Advanced Modeling of the Earth for Environment and Scenes Simulation is an
infrared background scene generator developed by Onera since the mid 1990'. MATISSE main goal is to compute
radiance images of natural backgrounds and radiative quantities such as local illumination, spectral transmission, and
spectral radiance along lines of sight.
The new version MATISSE-v2.0 has been completed during the first quarter of 2010 and the public version is going to
be released in few weeks. This latest version uses a multi resolution spatial scheme in order to treat the natural
backgrounds with spatial footprint from kilometre sizes (satellite viewing) down to metric sizes. Up to now, this spatial
scheme has been used in order to generate infrared images of sea surface. The new sea surface model (water waves and
surface optical properties) has been partially validated by using a specific Mediterranean campaign. MATISSE-v2.0 is
also accompanied with a new set of GUI (graphical user interface) in order to help the user in defining its computational
case. The code is also designed in order to be interfaced with other applications.
Our presentation will be devoted to a description of MATISSE-v2.0 new features, with examples of sea surface scenes
exemplifying the new code functionalities.
Atmospheric radiance structures are induced by local temperature and density fluctuations. The design, development, and use of electro-optical surveillance systems require the knowledge of atmospheric radiance clutter at small spatial scales. A model is developed to study radiance fluctuations observed by an airborne IR sensor. This model uses intermediate results of the Air Force Research Laboratory background radiance code SAMM-2 and synthesizes an image of atmospheric background clutter according to the sensor characteristics. Inputs are a 3-D grid of temperature fluctuations and SAMM-2 transfer functions. We extend this code to calculate atmospheric limb viewing irradiance images for airborne and satellite sensors. We detail the irradiance extension of the clutter calculation code and present some results for satellite and airborne viewing conditions.
Infrared (IR) detectors can be used as airborne limb-viewing surveillance systems for missile detection. These systems'
performances are impacted by the atmospheric inhomogeneous background. In fact, the probability of target detection
can be heavily affected. Consequently, the knowledge of these radiance small-scale fluctuations and their statistical
properties is required to assess these systems' detection capability. A model of two-dimensional radiance spatial
fluctuations autocorrelation function (ACF) is developed. This model is dedicated to airborne limb-viewing conditions in
the thermal IR. In the stratosphere and in clear-sky conditions, the structured background is mainly due to
internal-gravity-wave-induced temperature and density spatial fluctuations. Moreover, in the particular case of water vapour
absorption bands, the mass fraction fluctuations play a non negligible role on the radiative field. Thereby, considering
the temperature field and the water vapour field as stochastic processes, the radiance ACF can be expressed as a function
of the temperature ACF and the water vapor mass fraction ACF. A local thermodynamic equilibrium model is sufficient
for stratospheric conditions and sunlight scattering is neglected in the thermal IR. In addition, determination of the
radiance fluctuations ACF requires the knowledge of the absorption coefficient and its first derivatives with respect to
the temperature and water vapour mass fraction. Thus, a line-by-line model specific to water vapor absorption bands has
been developed. This model is used to precalculate the absorption coefficients and their derivatives. This look-up table
method allows circumventing the computational cost of a line-by-line calculation. A detailed description of the radiance
fluctuations ACF model is presented and first results are discussed.
Airborne infrared limb-viewing detectors may be used as surveillance sensors in order to detect dim military targets. These systems' performances are limited by the inhomogeneous background in the sensor field of view which impacts strongly on target detection probability. SAMM-2 is an existing code able to model atmospheric structures and their impact on infrared limb-observed radiance. The AFRL background radiance code can be used to predict the radiance fluctuation as a result of a normalized temperature fluctuation, along a given line of sight (LOS). The existing code SIG was designed to compute the cluttered background which would be observed from a spaceborne sensor. However, this code was not able to compute accurate scenes as seen by an airborne sensor especially for LOS close to the horizon. Recently, we developed a new code called BRUTE3D adapted to airborne viewing conditions. This BRUTE3D code inputs a three-dimensional grid of temperature fluctuations and SAMM-2 transfer functions to synthesize an image of the atmospheric background clutter according to the sensor characteristics. This paper details the working principles of the code and presents some output results. The effects of the small-scale temperature fluctuations on infrared limb radiance as seen by an airborne sensor are highlighted.
In the spectral band typically lower than 290 nm, solar radiation doesn't reach the Earth surface due to ozone absorption. UV radiation of artificial sources can then be recorded with a high contrast, by day or night. Because of this property, this spectral domain is called "Solar Blind". Furthermore, many UV detectors work at ambient temperature and have high sensitivity. One can envisage to use UV sources as beacons, particularly to find one's way around in case of haze. Light scattering by atmospheric particulates and molecules gives rise to an aureole surrounding the source image which tends to reduce the contrast of the source with respect to the background. However, scattering phase functions of the haze droplets present a very important forward peak and spreading of detected signal is not as important as in case of a clear atmosphere where Rayleigh scattering predominates. Moreover, the range of UV radiation propagation is limited by the high ozone absorption cross section. All these physical phenomena have to be taken into account in order to evaluate UV radiation potential interest for landing aid under low visibility conditions. We present here different results on characterization of UV runway light, propagation of UV radiation in the atmosphere and on the use of different kinds of sensors that are necessary to assess this point.
In this paper we present MATISSE 1.1 a new background scene generator, whose goal is to compute spectral or integrated radiance images of natural background, as well as the transmission of a hot gas signature.
The spectral bandwidth for this version of the code is from 750 to 3300 cm<sup>-1 </sup>(3 to 13 μm) with a 5 cm<sup>-1 </sup>resolution. Gaseous absorption is computed by a Correlated K model. The spatial variability of atmospheric quantities (temperatures and mixing ratios, among others) is taken into account, using variable profiles along the line of sight.
Natural backgrounds include the atmospheric background, low altitude clouds and the Earth ground. The radiation models used are designed for observation at low spatial resolution of clouds and soils, so a texture model was developed to increase the high spatial resolution rendering in the metric range.
Intermediate outputs of the code deliver radiance and transmission restricted to a single line of sight, in which case atmospheric refraction effects are taken into account. Along this line of sight the transmission can also be computed using a line-by-line model, which is useful to propagate the radiation emitted by a hot gas source (fires, aircraft or missile plume).
MATISSE 1.1 was released in June 2002, so this paper is devoted to a presentation of the first results obtained with the code and some validation tests.
A new 3D radiative code is used to solve the radiative transfer equation in the UV spectral domain for a nonequilibrium and axisymmetric media such as a rocket plume composed of hot reactive gases and metallic oxide particles like alumina. Calculations take into account the dominant chemiluminescence radiation mechanism and multiple scattering effects produced by alumina particles. Plume radiative properties are studied by using a simple cylindrical media of finite length, deduced from different aerothermochemical real rocket plume afterburning zones. Assumed a log-normal size distribution of alumina particles, optical properties are calculated by using Mie theory. Due to large uncertainties of particles properties, systematic tests have been performed in order to evaluate the influence of the different input data (refractive index, particle mean geometric radius) upon the radiance field. These computations will help us to define the set of parameters which need to be known accurately in order to compare computations with radiance measurements obtained during field experiments.
MATISSE is a new atmospheric radiative transfer code currently under development at Onera. Its purpose is to compute background radiance images by taking into account atmospheric, cloud and ground radiation and the variability of atmospheric properties. Propagation is calculated using a Correlated K model (CK) developed at Onera. The spectral range is between 3 to 13 micrometers with a resolution of 5 cm<SUP>-1</SUP>. Weather forecast outputs and aerosol climatology are used as inputs to account for spatial variability of atmospheric properties in radiance computations. Partial stratocumulus cloud cover can be generated and the radiation computations use Independent Pixel Approximation (IPA) and Bidirectional Reflectivity Distribution Functions (BRDF). Ground emission and reflectance are computed from spectral emissivities, BRDF and a simple thermal model for the local ground temperature. Databases include a Digital Terrain Elevation (DTED) and a land use database with 30' spatial resolution. Texture models are used to add realistic ground and cloud clutter down to 10 meter resolution. A line-by-line model is included to compute the spectral intensity propagated from high temperature exhaust plumes. Refraction effects are computed, but only along one single line of sight.
In the atmosphere, light scattering by molecules, particulates and aerosols causes an aureole around point- like sources. In various meteorological conditions, the radiance field coming from this aureole can be a non- negligible part of the total detected signal by large Field Of View sensors. In the framework of aureole's study, we have developed a method based on Monte Carlo calculation. The corresponding code permits to deal with monochromatic point sources in the 240 to 300 nm spectral range. The source's intensity angular dependency is axisymmetric and the atmosphere is described as a plane-parallel medium composed of a user defined constituents profiles. Systematic tests have been performed in order to evaluate the influence of the different input data on aureole results, such as ozone and SO<SUB>2</SUB> concentration values or ozone and aerosols concentration profiles. These computations will help us to define the set of meteorological parameters which need to e known accurately in order to compare computations with detected signals recorded during field experiments.