Abstract:The purpose of multi-angle polarization detection technology and its developing status at home and abroad are presented. The technical scheme, polarization calibration test, air flight test and in-orbit flight test of the TG-2 multi-angle polarization imager, the first space multi-angle polarization detection instrument of our country, are described in detail. The evaluation conclusion is given.

Abstract:Large imaging plane middle wave infrared continuous zoom optical systems were studied. A large imaging plane mechanical positive group compensated continuous zoom optical system was designed. The system had its operation waveband of 3.7 to 4.8 m, the focal length of 50 to 580 mm, the F number of 4.5 and the image plane diameter of 24.6 mm. It was suitable for the newly launched 1280×1024 pixel, 15 m pitch middle wave infrared cooled detectors. The system could keep a large field of view and effectively improve the ability of airborne electro-optical systems to search and identify targets while achieving long focal length and high resolution. The design result showed that the system had high imaging quality and its modulated transfer function value is close to 0.2 at the spatial frequency of 30 lp/mm.

Abstract:The microstructure height is one of the important parameters of Diffractive Optical Elements (DOEs). On the basis of the relationship of Polychromatic Integral Diffraction Efficiency (PIDE) with the microstructure heights of Double-layer Diffractive Optical Elements (DLDOEs), the optimal design method was analyzed and presented. Under the premise of satisfying the performance requirements of the optical system, the reduction of the microstructure height can be realized by reducing PIDE. The DLDOEs operating in the visible light band, long-wave infrared band and two infrared bands were simulated and analyzed respectively. The analytical results showed that the microstructure height of the DLDOE operating in the long-wave infrared band could be reduced by more than 55% when its 1.9% PIDE was sacrificed with this method. This conclusion was of great significance to the fabrication and application of DLDOEs.

Abstract:Deep blurring is a kind of expression feature of blurred infrared images. The accurate extraction of the deeply blurred region in infrared images is the foundation of extracting blurry infrared targets. On the basis of the excellent characteristics of recognition, learning, memory, tolerance and coordination exhibited by biological immune systems in antigen detection, extraction and elimination, a deeply blurred infrared target extraction algorithm based on optimal immune field neural immune network is proposed by combining the relationship between the nervous system and the immune system in biological immunity. The algorithm can provide a guiding role for the immune network in target and background classification of blurred infrared images by designing a neural network. By relying on the function of prior knowledge of neural network independent of the immune system, an optimal immune field neural immune network is designed and accurate extraction of blurred infrared targets is implemented. The experimental results show that the algorithm can extract targets in blurred infrared target images more effectively and accurately than other traditional target extraction algorithms for blurred infrared target images.

Abstract:To overcome the shortcoming of traditional ground-based methods of which the observation is limited, the method of inverting aerosol optical depth (AOD) by remote sensing image is gradually emerging. Compared with the traditional inversion methods, the Simplified Aerosol Retrieval Algorithm (SARA) is more universal. To further improve the accuracy, a nonlinear optimization method which uses multi-parameters to invert aerosol from Moderate-resolution Imaging Spectroradiometer (MODIS) is proposed. By treating the aerosol optical depth inverted by SARA as the initial value, the method optimizes the optical thickness, single scattering albedo (ω), asymmetry factor (g) and surface reflectance fitting parameter (ρ′s=k*ρs+b) simultaneously, so as to obtain the optimal solution. The results show that under the same conditions, the nonlinear optimization method is obviously superior to the SARA. The correlation coefficient of the nonlinear optimization method for single point precision verification is 0.8118, which is better than the 0.2624 of SARA. Compared with the inversion values from MODIS aerosol product (MOD04), for the case of July 6, the correlation coefficient of the nonlinear optimization method is 0.7612, which is better than 0.5916 of SARA. For the case of May 3, the correlation coefficient of nonlinear optimization method is 0.9036, which is better than 0.8788 of SARA.

Abstract:The temperature distribution characteristics of the patients with somatization symptoms were obtained by infrared thermal imaging technology, which can provide clinical indicators for identifying somatization symptoms. By using the self-rating scale of somatization symptoms, 162 patients with somatization symptoms were screened. These patients were taken as an observation group and 145 patients with non-somatization symptoms were taken as a control group. All patients were examined by the standardized infrared thermography. Five frames of images were captured from each person, and the characteristics and abnormal images were identified and compared between the two groups. The results of the images of the patients in the observation group were as follows: 3 patients were normal, 107 patients (66.%) were mild abnormal, 42 patients (26%) were moderate abnormal and 10 patients (6.2%) were severe abnormal. In the control group, 127 cases (87.6%) were normal, 18 cases (12.4%) were mild abnormal. 0 case (0%) was moderate abnormal, and 0 case (0%) was severe abnormal. The total abnormal rate of infrared thermal image temperature distribution in the observation group was 98%. The abnormal temperature distribution images of the patients could be used as an index to identify somatization symptoms.