As aerospace detection technology evolves, limb optical detection is increasingly becoming a focal point of research, attributed to its high spatial coverage and elevated vertical resolution. Based on the SCIATRAN limb atmospheric radiation model, simulation analyses of limb radiation transmission characteristics in the middle and upper atmosphere were conducted for both clear and cloudy conditions in the visible to near-infrared spectrum. The study results indicate that observational tangent height and solar zenith angle are important parameters affecting limb radiation brightness in the middle and upper atmosphere, with limb radiation brightness showing a decreasing trend as tangent height increases; in the visible light spectrum, it gradually weakens with increasing solar zenith angle, but in the near-infrared spectrum, it first decreases and then increases. The presence of aerosols and cirrus clouds significantly affects the mid-to-high altitude atmospheric limb radiation brightness. Under stratospheric aerosol conditions, radiation brightness can increase up to 2744.31% compared to background conditions, and under cirrus clouds with an optical thickness of 1, the increase in radiation brightness can be up to 13.78 times compared to clear sky conditions. The study delves into and analyzes the impact of particle optical properties on limb atmospheric background radiation, offering theoretical and data foundations for comprehending its spectral characteristics and designing limb detectors.
The total atmospheric transmittance of the South China Sea was measured using a Fourier Transform Infrared Spectroradiometer. After measuring the direct solar spectrum data in 1.1-2μm using the Spectroradiometer, the Langley method was employed to extract the atmospheric spectral transmittance of the South China Sea. The Langley method was utilized to extract atmospheric spectral transmittance at different altitudes and angles, and the variation in atmospheric transmittance over the South China Sea was analyzed extensively. The Combined Atmospheric Radiative Transfer (CART) model was used on the above data, to simulate the atmospheric transmittance under similar circumstances and draw a comparison with the previously obtained results. The data obtained from the Spectroradiometer indicates that the slant path atmospheric transmittance is in coherence with the model simulation results, with a negligible absolute error of less than 2.3%. Furthermore, as the solar zenith angle increases, there is a gradual decrease in the transmittance of the entire measurement band. The short-wave atmosphere attenuates rapidly; however, the long-wave attenuation is slow.
The imaging equipment working in the atmosphere will not only be limited by the performance of the imaging system, but also be affected by turbulence. In the fields of astronomical observation, ground-based remote sensing and remote monitoring, there is an urgent need for corresponding methods and technologies to eliminate the impact of atmospheric turbulence and obtain clear images. With the development of computer technology, atmospheric optics theory and image processing technology, more and more researchers hope to combine deep learning technology with atmospheric turbulence theory to reduce the impact of turbulence on imaging and obtain clear and stable images. In this paper, a turbulence image restoration technique based on Generative Adversarial Networks (GAN) is proposed, which is divided into generator network and discriminator network. The generator network is used to convert blurred images affected by turbulence into clear images. The discriminator network is used to compare the converted image with the real clear image to determine whether the image is real or generated. After the whole GAN is optimized and trained, the image transformed by the generator and the real and clear image cannot be distinguished from each other. Because the training of the GAN requires a large number of corresponding samples, it is difficult to obtain the images affected and unaffected by turbulence at the same time in real life, so this paper uses the statistical characteristics of turbulence to simulate a large number of images affected by turbulence. We used the trained GAN model to simulate turbulence image restoration and got some achievements.
Aerosol optical depth (AOD) is one of the basic parameters used to analyze physical properties of regional aerosols, but the in-situ observation or remote sensing AOD dataset could be scarce especially in ocean area. The Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) reanalysis has the longest temporal span, and its accuracy in China sea area is to be evaluated. This study provides a validation of MERRA-2 AOD products’ applicability in the eastern and southern China sea based on Aerosol Robotic Network (AERONET). The results indicated that the MERRA-2 AOD with 1-hour temporal resolution agreed with the time averaged AERONET AOD well, for its correlation coefficient is 0.887, root mean square error (RMSE) is 0.096, and mean absolute error (MAE) is 0.056. Presented analysis also revealed a systematic underestimation of AOD that MERRA-2 made, and that deviation tended to increase in higher AOD which demonstrated a slope of -0.26 when utilized linear fitting technics, but the mean bias (MB) of test dataset was only -0.001 because the AOD concentrated on lower than 0.2. These results illustrated the suitability of using MERRA-2 AOD product in aerosol researches of the China sea area.
In this paper, we investigate that the effects of weather, turbulence and pointing errors on laser beams, and establish a joint channel statistical model, then derive the performance parameters of free space optical communication system based on OOK modulation, such as average bit error rate, average channel capacity and outage probability, and finally derive their new expressions by using Meijer’s G function and H function. For an atmospheric laser communication system with a wavelength of 1550 nm and a link length of 1 km, the performance parameters of the system are simulated and analyzed. The results show that when the standard deviation of jitter is small, the communication system is obviously affected by turbulence, and the performance of communication system with different turbulence can be significantly improved by the aperture average effect; aperture averaging can also significantly compensate for the deterioration of the communication system performance due to the decrease of atmospheric visibility; when the standard deviation of jitter is large, the system performance is limited by the average aperture effect.
The gradient of the refractive index of the atmosphere causes the route to bend when the light propagates in the atmosphere, thereby the propagation path will change. For the applications of optical atmospheric detection and star-light navigation positioning, in order to obtain the precise position of the target, the influence of atmospheric refraction needs to be considered. This paper introduces a widely-used refractive index calculation model. The relationships between the index of atmospheric refraction and wavelength, atmospheric pressure, temperature and water vapor content are analyzed. Based on the limb detection method, the effect of atmospheric refraction on the line of sight is calculated and analyzed. At the condition of the 1km tangent height, ignoring the atmospheric refraction will cause the limb line path length up to 148.3 km added. In the limb detection mode, the deflected angle caused by atmospheric refraction decreases rapidly as the pitch angle increases. The difference of the tangent height caused by atmospheric refraction increases rapidly with the decreasing observation point height. When the observing point height is 7 km, variation of the tangent height caused by atmospheric refraction is 0.282 km and the deflected angle is 0.195°. Which indicates that the atmospheric refraction has a great influence on the path of limb observation, especially for tangent height below 30 km.
At present, when the infrared sensor detects the targets remotely, the target appears as a spot in the image plane, the geometry information is difficult to obtain, and the surface brightness temperature becomes an effective feature for the target recognition. However, due to the long distance of the target, the weak signal and the complex transmission path, the temperature features are difficult to extract accurately, which brings great uncertainty to the target recognition. Based on the principle of multi-spectral infrared radiation temperature measurement, this paper establishes a BP network model to estimate the point target temperature. Experiments show that the accuracy of extracting the faint targets temperature characteristics can be effectively improved, which shows great support for target recognition.
Synthetic aperture laser radar (inverse) combines the technology of laser radar with synthetic aperture, which has high imaging resolution, strong anti-interference, and good concealment. Due to the short laser wavelength and fast imaging time, the tiny vibrations of the moving target may achieve the target inverse synthetic aperture (range -Doppler) imaging in a very short time, which increases identification characteristics compared to the traditional optical remote point target detection and recognition; it reduces the complexity of data processing compared to radar, and optical imaging is easier to understand. Therefore, synthetic aperture laser radar has the advantages of both optics and radar, and has attracted more and more attention in long-distance target detection and recognition. Since 1960's, MIT Lincoln Laboratory has conducted research on the long-range target tracking and identification using laser radar. In this paper, the micro-motion feature extraction and recognition method for inverse synthetic aperture laser radar after target imaging is studied. The target images of different micro-motion form are analyzed by range-Doppler imaging model, and the geometric features of the target are extracted by the optical target segmentation algorithm. The Hough transform theory is used to extract the characteristics of the micro-motion period, and the micro-motion angle is inversed through the change of the target geometric features. The simulation test in field shows that this method can effectively extract the micro-motion characteristics of the target and lay a foundation for the micro-motion target recognition of synthetic aperture laser radar.
High-resolution remote sounding instruments have thousands of channels usually, the similarity between channels will cause redundancy, and may lead to the non-convergence of retrieval algorithm. In this paper, the channel selection of temperature retrieval is discussed based on air-borne High-spectral resolution Interferometer Sounder. The results show that, for the total 1724 channels of HIS 600-1075cm-1 band, the selected 45 channels contain 70% of the total information content,97 channels contain 80% of the total information content, greatly reducing the number of channels involved in retrieval algorithm, then using selected channels simulated for the measurements of HIS is discussed, the average absolute deviation between the retrieved temperature profile and the truth is 0.74K/Km. The result demonstrates that stepwise iterative method is possible to select channels for the airborne high-spectral infrared data.
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