Abstract:The characteristics and key parameters of various temperature sensors in three categories commonly used in the packaging structures of infrared photodetectors and focal plane arrays are summarized. On this basis, the measurement and control accuracy and error of different types of sensors are analyzed. Finally, the factors which need to be considered in the selection of temperature sensors for the packages in different temperature zones and the matters which need attention in practical application are discussed in detail.

Abstract:With the development of HgCdTe infrared focal plane arrays toward super-large sizes and small pixels, the requirements of blind pixel rate, especially continuous blind pixel and uniformity, are increasing. The surface defect has become an important factor to inhibit the application of Si-based HgCdTe molecular beam epitaxy (MBE). By solving three key problems of MBE-grown HgCdTe, namely, beam stability, beam measurement accuracy and growth temperature control stability, and by optimizing the growth parameters through orthogonal experiments, the defect density of Si-based HgCdTe materials is controlled within 500 cm^-2 and the optimal value is 57.83 cm^-2.

Abstract:With the development of infrared technology, infrared detectors will develop toward mK or sub-mK sensitivity infrared detection systems in the future. Since traditional detectors are difficult to meet these development requirements, the responsivity of photoelectric detectors needs to be improved urgently. On the basis of the unique energy band structure, ultra-high carrier mobility and ultra-wide spectral absorption characteristics of graphene materials, a new generation of graphene-based composite infrared detection materials with extremely high infrared radiation responsivity and ultra-wide spectral response range are studied in combination with the extremely high quantum efficiency of HgCdTe photoelectric detection materials.

Abstract:To overcome the shortcomings of high cost, low precision and inconvenient placement of traditional gas sensors, a set of opposite laser humidity sensing system is constructed. The system uses a semiconductor laser as a light source. A light transmitting unit and a light receiving unit are respectively arranged on both sides of a measuring cabinet. When a laser beam passes through the measuring portion in the middle of the measuring cabinet, the humidity value of the portion can be measured. The experimental results show that the calibration coefficient R2 of the opposite sensing system is 0.9976. The retesting errors of the humidity content and the theoretical calculation value in the three-meter optical path are 0.82%, 0.46%, 0.44%, and 0.42% respectively. Within the 40-minute test after the instrument stabilizes, the humidity content range in the actual test cabinet is fluctuated to a maximum of 30. The standard deviation is 7.88 and the relative error is 0.4%.

Abstract:Infrared images have the disadvantages of narrow dynamic range, low contrast and being easy to be polluted by noise. However, traditional infrared image denoising algorithms may filter out image details while removing noise. A new infrared image denoising method based on sparse representation is proposed. The method firstly clusters an original infrared image; secondly decomposes each cluster sub-image into a dictionary; and then the denoised infrared image is reconstructed from the sparse coefficient matrix. The experimental results show that this method can retain image details better than the traditional infrared image denoising algorithm and the visual effect is ideal.

Abstract:According to the radiative transfer characteristics and spatial distribution characteristics of dust particles, the occurrence, scope and strength of dust weather can be monitored effectively by using meteorological satellite data, and the quantitative information can be calculated. Generally, monitoring methods include the monitoring method based on the characteristics of satellite bands and the monitoring method based on satellite image visual interpretation. The dust monitoring module of the Satellite Monitoring Analysis and Remote Sensing Application Toolkit (SMART) can be used to achieve the annual statistics of dust monitoring results. The statistical data show that there are three high frequency dust weather areas which are xinjiang region; western Inner Mongolia and hexi corridor region; central and eastern Inner Mongolia, northeast and north China region. The cumulative coverage of dust areas monitored by satellite in 2007, 2010, 2012 and 2015 is larger, reaching over 5 million square kilometers. FY-4A, one of the new generation of stationary meteorological satellites, has exhibited its huge potential in dust monitoring. This will be beneficial to satellite image interpretation of dust weather.

Abstract:A correction and analysis method for the spectral data collected by a specific infrared spectrum integrated system is presented. In the experiment, the infrared spectral data of a blackbody at a known specific temperature are firstly classified and sorted. The signal noises are eliminated as much as possible with different filtering algorithms and filter window widths on condition that the characteristic signals are maximally reserved. Then, the signals obtained are corrected by a partial least square algorithm so as to let them agree with the theoretical value. Finally, the correction results are used to construct a mathematical model and the concept of confidence is taken into account to verify the accuracy of the model. It is found in data analysis that the spectral data collected by the integrated infrared spectrum integrated system are close to the theoretical value after being corrected by the partial least-squares algorithm and the function relationship between the corrected series and the wave number can be fitted and is less affected by temperature.

Abstract:Radar detection of in-shore targets has been a difficult problem in target recognition for a long time. It is difficult to detect and identify in-shore low-speed ship targets. However, ship targets have better infrared radiation characteristics which can be fully utilized in the detection process. According to these characteristics, an image processing method based on Top-hat transformation and OTSU is proposed. After open-operation reconstruction, the Top-hat transformation is used to enhance the contrast between the target and the background in an infrared image. To detect targets, the threshold values of the image are segmented by OTSU according to the gray-scale characteristics of the image. The experimental results show that the algorithm can effectively detect in-shore ship targets and is of a certain practical significance to the recognition of in-shore targets.