Quantifying the relationship between the measurement precision and specifications of a UV/visible sensor on a geostationary satellite

To investigate the feasibility of new satellite observations, including air quality (AQ) observations from geostationary (GEO) orbit, it is essential to link the measurement precision (ε) with sensor specifications in advance. The present study attempts to formulate the linkage between ε and specifications of a UV/visible sensor (signal-to-noise ratio (SNR), full width at half maximum (FWHM) of the slit function, and sampling ratio (SR)) on a GEO satellite. A sophisticated radiative transfer model (JACOSPAR) is used to calculate synthetic radiance spectra that would be measured by a UV/visible sensor observing the atmosphere over Tokyo (35.7°N, 139.7°E) from GEO orbit at 120°E longitude. The spectra, modified according to given sensor specifications, are analyzed by the differential optical absorption spectroscopy technique to estimate the ε for slant column densities of O₃ and NO₂. We find clear relationships: for example, the ε of the O₃ slant column density (molecules cm⁻²) and SNR at 330 nm are linked by the equation log(ε) = −1.06 · log(SNR) + 20.71 in the UV region, and the ε of the NO₂ slant column density and SNR at 450 nm are linked by log(ε) = −0.98 · log(SNR) + 18.00, at a FWHM = 0.6 nm (for the Gaussian slit function) and SR = 4. The relationships are mostly independent of other specifications (e.g., horizontal and temporal resolutions), as they affect ε primarily through SNR, providing constraints in determining the optimal SNR (and alternatively FWHM and SR) for similar UV/visible sensors dedicated for AQ studies.     

多频谱兼容隐身材料研究进展

多频谱兼容隐身材料具有明确的研究和应用背景。综述了国内外在红外及雷达兼容隐身材料、红外及可见光兼容隐身材料、红外与激光兼容隐身材料等多频谱兼容隐身材料技术的发展以及多频谱兼容隐身材料在热点领域如光子晶体、掺杂氧化物半导体等所取得的研究成果和进展,指出今后的多频谱隐身材料发展的方向和重点。     

利用多尺度区域权重的红外可见光图像融合

针对红外、可见光图像融合，提出了一种利用多尺度区域权重的方法，获得既具有良好视觉效果又能保留和继承特征细节的融合结果。首先，通过改变平滑滤波的参数构建多尺度分解，获得一系列具有不同细节的双波段图层；其次，基于每一图层生成区域权重图，实现双波段图层融合;最后，利用适当的系数对融合后的图层进行合成，获得最终的融合结果。通过对比实验结果的主客观评价分析，证明本文方法能够产生最佳视觉效果的融合图像，能保留和突出原始双波段图像中的细节与特征，并能获得最佳的客观评价指标。