Effects of ocean wave spectra on the polarized bidirectional reflectance distribution function matrix at Ku‐band and its implications on satellite backscattering simulations
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A polarized bidirectional reflectance distribution function (pBRDF) matrix is developed from two-scale roughness theory with the aim of providing more accurate simulations of microwave emissions and scattering required for ocean–atmosphere coupled radiative transfer models. The potential of the pBRDF matrix is explored for simulating the ocean backscatter at Ku-band. The effects of ocean wave spectra including the modified Durden and Vesecky (DV2), Elfouhaily, and Kudryavtsev spectra on the pBRDF matrix backscatter simulations are investigated. Additionally, the differences in backscattering normalized radar cross-section (NRCS) simulations between the Ku-band geophysical model function and pBRDF matrix are analyzed. The results show that the pBRDF matrix can reasonably reproduce the spatial distribution of ocean surface backscattering energy, but the distribution pattern and numerical values are influenced by ocean wave spectra. The DV2 spectrum is the best one for the pBRDF matrix to simulate horizontally polarized NRCSs, with the exception of scenarios where the incidence angle is below 35°, the wind speed is less than 10 m s−1, and in the cross-wind direction. Also, the DV2 spectrum effectively characterizes the wind speed and relative azimuth angle dependence for vertically polarized NRCSs. The Elfouhaily spectrum is suitable for simulating vertically polarized NRCSs under conditions of low wind speed (below 5 m s−1) and incidence angles under 40°. The Kudryavtsev spectrum excels in simulating vertically polarized NRCSs at high incidence angles (> 40°) and horizontally polarized NRCSs at low incidence angles (< 35°). 为提供微波海洋-大气耦合辐射传输模型所需的精确发射和散射, 基于双尺度粗糙度理论发展了极化双向反射分布函数 (pBRDF) 矩阵.本研究探讨了pBRDF矩阵是否能够表征ku波段洋面后向散射, 对比了三种常用海浪谱模型对pBRDF矩阵后向散射模拟的影响, 分析了ku波段地球物理模型函数 (GMF) 与pBRDF矩阵在后向散射归一化雷达截面 (NRCS) 模拟中的差异.结果表明, pBRDF矩阵能够准确再现洋面后向散射能量的空间分布, 但后向散射能量分布受海浪谱影响较大.Keywords:
Ku band
Parameters like the sun angle as well as the measurement angle mostly are not taken into account when simulating because their influence on the reflectivity is weak. Therefore the impact of a changing measurement and illumination angle on the reflectivity is investigated. Furthermore the impact of humidity and chlorophyll in the scenery is studied by analyzing reflectance spectra of different vegetative background areas. It is shown that the measurement as well as the illumination angle has an important influence on the absolute reflection values which raises the importance of measurements of the bidirectional reflectance distribution function (BRDF).
Reflection
Light reflection
Fresnel equations
Diffuse reflection
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Using measurements of real-world samples of metals, the proposed approach verifies predictions of bidirectional reflectance distribution function (BRDF) models. It employs ellipsometry to verify both the actual polarizing effect and the overall reflectance behavior of the metallic surfaces.
Ellipsometry
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A well understanding of topography effect on the forest reflectance is critical for biophysical parameters retrieval over rugged area. In this paper, a new hybrid bidirectional reflectance distribution function (BRDF) model coupled the geometric optical mutual shadowing (GOMS) and scattering from arbitrarily inclined leaves (SAIL) models with topography consideration (GOSAILT) for sloping forest was proposed.
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Signature prediction models have become an increasingly important tool for the ground combat vehicle designer in recent years. System designers have been successful in prototyping entire vehicles in each spectral band. With this success, focused efforts to improve the accuracy of these signature models have produced robust, validated performance for many operational conditions. One of the most recent improvement in prediction models for ground vehicle systems has been improvements in surface reflectance. Surface reflectance is central to the predicted performance of these models and range from simple to very complex. Simple surface reflectance models treats the surface as totally lambertiant has an advantage of being fast to calculate but does not take into account the specular nature which all surfaces posses. The bi-directional reflectance distribution function (BRDF) is a more complex representation which allows for a more accurate representation of surface reflectance phenomena. The input to the BRDF usually comes from a laboratory sample measured in a laboratory setting. These laboratory samples are made to be perfect so that comparisons can be made between variations in formulas for the coatings. The limitation of these inputs is that surfaces that are exposed to environments effects and normal daily use are the more representative of data we are interested in. Other effects such as the conditions under which the surface coatings are applied can cause reflectance variability as well. This paper explores the variability on real targets and compares them to laboratory samples. The implication of these variations to signature models will be explored.
Signature (topology)
Representation
Spectral signature
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Outline and in-orbit verification of a Ku-band transmitter installed in a Pico-satellite are described. We had successfully caught telemetry signals after eleven days of the satellite launch. Despite of a limited operation period, we have confirmed that a specially developed Ku-band transmitter was survived in space environment during eighteen days.
Ku band
Communications satellite
Orbit (dynamics)
Quasi-Zenith Satellite System
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Scene simulation has proved to be a valuable tool for analysing the images perceived by visible and infrared imaging systems. Accurate scene simulation requires accurate incorporation of the optical properties of all the materials within a scene, with reflectance incorporated with the bidirectional reflectance distribution function (BRDF) and emission incorporated through the directional emissivity or hemispherical directional reflectance (HDR). This paper compares the fit of various parameterised models to experimental BRDF data from a variety of surfaces representing the extremes of material properties found in the environment. One of the main aims is to infer the accuracy and validity of an in-house BRDF model called Mopaf using data representative of different sorts of isotropically reflecting materials. Where appropriate physical and semiempirical models and a novel parameter based BRDF model were compared with Mopaf and with BRDF data from a Surface Optics Corporation SOC-200 instrument. It was concluded that Mopaf might not be reliable for all the angular BRDF data, especially specularly reflecting surfaces or grazing incidence data. Likewise, the other BRDF models investigated tended to be limited to a range of physical conditions such as only diffuse reflection or to a range of surface roughness. It was shown that the proposed new BRDF model was more generally applicable from the visible to infrared wavelengths, over a wide range of reflection angles and for different sorts of surface material.
Reflection
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Two characteristics are critical in the understanding of target signatures, physical surface temperature and surface reflectance. An objects surface reflectance can be thought of as having two major components, the diffuse and specular components. The best way to understand these components is by examining the Bi-directional Reflectance Distribution Function (BRDF). The BRDF provides an understanding of the reflectance behavior of a surface from every incident angle and reflectance angle. With the BRDF one can provide an accurate computer model of how the material behaves. Databases of BRDF data are available for use in modeling and simulation of targets but are typically comprised of pristine samples that may not be representative of real world targets. This paper will provide methods, data and trends of the BRDF variability in the infrared regions. We will also explore appropriate data sets for use to represent typical fielded targets.
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This study examines the influence of non-Lambertian reflectance effects on the detection of subpixel vehicles in hyperspectral imagery. Object-level BRDF spectral signatures for an olive green sedan were simulated using a fast, radiometrically accurate 3D rendering model, and the signatures were embedded as subpixel targets of low fractional fill into the HyMap hyperspectral image provided in the Rochester Institute of Technology Blind Test dataset. Detection algorithms based on the ACE detector were run on the scene. The results demonstrate a significant improvement in detection performance when including the target's BRDF variation in the detection scheme through either a subspace ACE or a Bayesian selection (multiple ACE detector) method.
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