Solar radiation will be scattered by atmospheric molecules and aerosol particles when it transfers through the Earth atmosphere. The scattered radiance with different polarization state can be used to characterize atmospheric components. Based on the BHU-ATM presented in our previous work, an atmospheric radiative transfer model considering the polarization effects is developed in this paper, in which the parameter discretization method is used. To this end, the radiative transfer equation is adapted into the Stokes vector form, while the impacts of atmospheric molecules and aerosols on the polarization state of the scattered radiance are represented by means of the scattering phase matrix. The Curtis-Godson approximation and the two-stream approximation are used to obtain the analytical solution of the adapted radiative transfer equation. As the precise calculation of the scattering phase matrix varying with the scattering angle and the radiant wavelength is inefficient for the calculation of spectral path radiance, a novel aspect of this work is the efficient computation of the scattering phase matrix through a two-dimensional interpolation method, significantly reducing computational complexity while maintaining accuracy across a broad range of angles and wavelengths. The simulation results of the atmospheric transmittance, the spectral radiance and the degree of polarization (DOP) for an arbitrarily selected transfer path are given. As it can be seen, in the spectrum from the visible through the near infrared (VNIR), the polarization modeling showed a maximum transmittance difference of 0.0007 and a spectral radiance difference of 0.3W/m2/μm/sr. The DOP varied significantly, with a difference of up to 0.12 between urban and ocean aerosols. The developed polarization model can improve aerosol component identification in satellite-based remote sensing applications, aiding in more accurate air quality monitoring and enhancing climate models that account for aerosol scattering effects.
In this work, a cloud detection scheme is proposed to process the multispectral images of space-based Earth observational sensors. With the assumption that the spectral and the spatial characteristics of the ground covers are invariant through a relatively long period, physically-based imagery simulation model is adopted to generate clear sky images for the specified sensor under the similar observational geometry with the same scene parameters. As the spectral bands of the selected sensor locate in atmospheric windows, the atmospheric condition are arbitrarily set as typical values to simulate the clear sky images. The structure similarity (SSIM) of the measured and the simulated images are calculated in the pixel by pixel manner to generate the SSIM image, in which the pixels with smaller SSIM values indicate the higher possibility of cloudy region. The cloud mask image can be obtained via selecting a suitable SSIM threshold for binary detection. A set of data measured by the Fengyun(FY)-4B geostationary satellite is used to demonstrate the usefulness of the proposed scheme. The images of the spectral bands NO.5 (1.58~1.64μm) and NO.7 (3.50~4.00μm) are selected as examples to implement cloud detection using monochromatic image alone as well as color ratio data. The results of the cloud detection validate the usefulness and the interpretability of the proposed scheme.
Hyperspectral atmospheric radiative transfer model (HARTM) is an essential component for image calibration and explanation in remote sensing applications. A HARTM describes the interaction between electromagnetic radiation and the earth’s atmosphere, which affects the quality and radiative accuracy of the acquired data. The performance evaluation of the HARTM is crucial to ensure the reliability of the retrieved information from calibrated images. By comparing the simulated results with measured or other validated reference data, the accuracy of HARTM can be assessed. Currently used similarity metrics, such as the Euclidean distance (ED) and the spectral angle metric (SAM), are relatively one-sided and single-valued overall assessment in evaluating hyperspectral model. The IEEE standard 1597.1 proposed feature selective validation (FSV) method as the key mathematical tool which has been widely applied in electromagnetic model verification, validation and accreditation (VV&A). However, to the best of our knowledge, the applications of FSV method in evaluating hyperspectral similarity has not yet been proposed up to this point. This paper concentrates on developing a technique for HARTM evaluation by means of FSV. Specifically, a multi-resolution components fused evaluation is proposed to obtain a more flexible comparison between the model and the measured data. As an example, the proposed approach is applied to validate the BeiHang University-Atmospheric Transfer Model (BHU-ATM) using the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) data. Results of multi-resolution components fused evaluation show good consistency with the results of directly evaluating the original data.
In this paper, a target and background driven simulation procedure is developed for optimal band analysis and performance evaluation of multispectral sensors for dim target detection, in which the observation geometry, target and background radiant characteristics, and the influence of infrared sensor system are integrated into. With the specified sensor altitude, the BeiHang University - Atmospheric Transfer Model (BHU-ATM) is adopted to calculate spectral irradiances of space-variant sky background. When a target with an assumed altitude exists in one line of sight (LOS), the corresponding nadir angle is used to calculate the distance between the target and the sensor, which impacts the target spectral irradiance at the sensor aperture. To analyze the optimal band for target detection, a set of spectral response functions with different central wavelengths and bandwidths are designed to calculate the target-to-background contrasts as well as the signal-to-noise ratios (SNRs). To demonstrate the usefulness of the developed procedure, typical sensor parameters are used to analyze the optimal band for aircraft detection. The band achieving the highest SNR is selected and used in the radiant image simulation for performance evaluation. The results show that the detection performance is related to spectral band as well as the LOS direction.
The intensive emission of earth limb in the field of view of sensors contributes much to the observation images. Due to the low signal-to-noise ratio (SNR), it is a challenge to detect small targets in earth limb background, especially for the detection of point-like targets from a single frame. To improve the target detection, track before detection (TBD) based on the frame sequence is performed. In this paper, a new technique is proposed to determine the target associated trajectories, which jointly carries out background removing, maximum value projection (MVP) and Hough transform. The background of the bright earth limb in the observation images is removed according to the profile characteristics. For a moving target, the corresponding pixels in the MVP image are shifting approximately regularly in time sequence. And the target trajectory is determined by Hough transform according to the pixel characteristics of the target and the clutter and noise. Comparing with traditional frame-by-frame methods, determining associated trajectories from MVP reduces the computation load. Numerical simulations are presented to demonstrate the effectiveness of the approach proposed.
In this work, a fast calculation method of the scattered radiance for scenario involving both the earth surface and the earth-limb regions is proposed. The single scattering equation of typical two-stream approximate is adapted to compute atmospheric radiative transfer under the spherical-parallel atmosphere assumption. With specified atmospheric profiles, spectral band and observation geometry, a two-dimensional (2-D) matrix of the scattered radiance varying with incident zenith and viewing zenith angles are then calculated. Finally, the earth disk images are generated for different spectral bands by interpolating the calculated radiance matrices. Simulation results of multispectral earth disk images for space-based earth observation sensors are presented to demonstrate the usefulness of the proposed technique for high fidelity scene generation where both the earth surface and the earth-limb regions are observed.
In this work, we focus on developing the infrared (IR) sensor and performance analysis model for space-based IR
systems which are designed for detection of space targets in the earth and the earth-limb background. Corresponding to
the sensor observation geometry, a simplified transmittance calculation scheme applicable to large-scale scenes as well
as a mathematical model for pixel-by-pixel irradiance calculation is proposed. By defining the apparent contrast of
targets in simulated IR images, a model for detection performance analysis is developed for sensors operating in different
spectral bands. Typical simulation examples are presented to validate the current model and methodology.
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