红外遥感低温制冷器的进展

与红外探测器配套的低温制冷器是军用急需发展的高新技术产品，国内研制已接近国际先进水平，基本掌握了小型化、低振动、长寿命、细方形漆包线制作，间隙密封、消除电磁干扰等关键技术，介绍了研制的直线电机谐振压缩机的主要技术性能。希望主管、用户、研制、生产各方通力合作，在应用和改进过程中，实现我国低温制冷器的产业化。     

红外技术与应用XXVIII

用商业线性压缩机驱动的斯特林型脉管制冷器的研制(特邀论文)(G．Thummes等，德国自适应低温技术与传感器传递中心)     

CCD成象探测器液氮制冷器研制的新进展

ＣＣＤ成象探测器液氮制冷器研制的新进展兰州物理研究所葛瑞宏，毕龙生，曹慎诚，聂裕民，董长昆本文描述的这种ＣＣＤ成象探测器液氮制冷器是对已研制的ＴＷＤ—Ⅱ、ＴＷＤ—Ⅲ型天文望远镜用ＣＣＤ液氮制冷器的改进型，改进后的液氮制冷器在不改变原有接口尺寸的条件下...     

辐射制冷技术在中国气象卫星上的应用

配置红外探测通道的光学遥感仪器是气象卫星的主要载荷之一,我国太阳同步轨道和地球静止轨道气象卫星的光学载荷采用辐射制冷器冷却红外探测器及其后的光学部件,使其在规定的温度工作。概要介绍了我国风云系列气象卫星对制冷技术的要求以及近30年来所研制的不同型式辐射制冷器,给出了FY-1A～1D、FY-3A、FY-2A～2E气象卫星辐射制冷器的在轨飞行性能,阐述了辐射制冷技术在气象卫星上长期业务应用的关键技术和实际结果。探讨了辐射制冷技术在我国未来气象卫星上的应用前景。     

红外技术与应用ⅩⅩⅧ

一、探测器制冷器1.用商业线性压缩机驱动的斯特林型脉管制冷器的 研制(特邀论文)(G.Thummes等,德国自适应低 温技术与传感器传递中心)2.供斯特林低温制冷器使用的高级控制电子部件(I. Ruhlich等,德国AEG红外组件GmbH公司)     

低成本铅盐焦平面列阵

目前的中波红外探测器，如锑化铟、碲镉汞和硅化铂探测器，都需要使用昂贵的、笨重的和耗电的低温制冷器或者昂贵的多级热电制冷器。对于成本、功率、尺寸及可靠性都很重要的一些应用来说，这些探测器是不适合的。这些应用需要的是一种低成本的非致冷中波红外探测器。     

微型低温制冷技术的现状和发展趋势

介绍了目前典型的军用第二代、第三代焦平面探测器杜瓦制冷机组件中斯特林制冷机和节流制冷器的应用情况,从焦平面探测器芯片探测元尺寸的变化,提出了配接制冷机的冷指尺寸的变化,介绍了昆明物理研究所微型低温制冷技术的发展现状及微型低温制冷机向高可靠性、低成本、高工作温度的发展趋势。     

长波光导60元碲镉汞红外探测器通用组件

报道了工程化长波光导６０无碲镉汞红外探测器组件研制的结果，该组件由探测器芯片、杜瓦和制冷器组成。探测器组件的主要指标达到：ＤＢ＝１．７×１Ｏ１０ＣｍＨｚ１／２／ＷＶＢ＝１６×１０４Ｖ／Ｗ。组件的体积小，重量轻，并达到了国军标所规定的红外探测器高、低温实验，温度循环实验，振动实验和冲击等环境实验的要求。     

低温测量杜瓦研制

低温测量杜瓦研制航空工业总公司○一四中心王三煜本文论述了节流制冷器用测温杜瓦研制的具体内容，叙述了杜瓦制作的具体问题，给出了实验结果，并对杜瓦制作进行了分析。低温测量杜瓦研制@王三煜...     

半导体制冷器的进展

半导体制冷器具有微型化、轻量化、无振动、长寿命等许多重要优点。目前３００Ｋ室温下优值系数Ｚ最高的半导体制冷材料是Ｐ型Ａｇ０．５８ＣＵ０．２９Ｔｉ０．９４Ｔｅ四元合金,２００－３００Ｋ普冷范围内三元Ｂｉ２Ｔｅ３－Ｓｂ２Ｔｅ３－Ｓｂ２Ｓｅ３固溶体合仍然应用最广且性能优良,而２０－２００Ｋ低温下则是Ｂｉ－Ｓｂ合金热电性能最好,电臂材料是决定半导体制冷器性能的主要因素,但通过改进电臂结构,设计特殊的电臂联     

基于敏感薄膜的F-P光纤温度传感器的高温特性

根据薄膜型光纤温度传感器的感温原理及光学薄膜的应力特性,利用膜层干涉的特征矩阵分析了传感元件的传感特性,建立了薄膜型光纤温度传感器的热应力特性及其对传感特性影响的理论模型。通过对薄膜和光纤的热光效应和热膨胀特性的分析,对比了蓝宝石光纤、纯硅芯光纤和普通多模光纤三种光纤基底的热应力-温度特性,设计了高温传感器传感探头的薄膜膜系,分析了膜系中每层膜的热应力-温度特性,以及临界载荷应力特性,确定所选光纤基底脱膜的临界应力值。通过模拟不同应力作用下的光谱传感特性,为传感器薄膜敏感探头的稳定性和可靠性提供理论依据和支持,提高传感器研制的效率。     

Numerical Studies of Scattering Properties of Leaves and Leaf Moisture Influences on the Scattering at Microwave Wavelengths

This paper uses a 3-D finite-difference time-domain method to accurately calculate the single-scattering properties of randomly oriented leaves and evaluate the influence of vegetation water content (VWC) on these properties at frequencies of 19.35 and 37.0 GHz. The studied leaves are assumed to be thin elliptical disks with two different sizes and have various VWC values. Although leaf moisture causes considerable absorption in the scattering process, the effective efficiencies of extinction and scattering of leaves essentially linearly increase with VWC, which is critical for forest remote sensing. Calculated asymmetry factors and phase functions also indicate that there is a significant amount of scattered energy at large scattering angles at microwave wavelengths. This paper can improve the modeling of the radiative transfer by vegetation canopies at the higher frequencies of the microwave spectrum, which is important for passive microwave remote sensing.     

环境减灾卫星中国陆面多时相遥感数据NDVI产品的批处理方法研究

作为大范围、全天候、动态监测灾害时空变化的高技术手段,卫星遥感在灾害监测和环境保护中的应用日益 广泛。但在国内,产品化的遥感数据很少。因此,如何快速制作遥感数据产品是国内遥感数据是否能得到广泛应用的关键。 本文提出了一种快速自动化多时相遥感数据处理方法,该方法通过用ERDAS的Batch Command对NDVI数据产品进行批处理, 大大节省了人力和时间。该方法也可供类似的大数据量遥感影像处理借鉴。     

Efficient deployment quality analysis for intrusion detection in wireless sensor networks

The intrusion detection in a Wireless Sensor Network is defined as a mechanism to monitor and detect any intruder in a sensing area. The sensor deployment quality is a critical issue since it reflects the cost and detection capability of a wireless sensor network. The quality of deterministic deployment can be determined sufficiently by a rigorous analysis before the deployment. However, when random deployment is required, determining the deployment quality becomes challenging. In the intrusion detection application, it is necessary to define more precise measures of sensing range, transmission range, and node density that impact overall system performance. The major question is centred around the quality of intrusion detection in WSN, how we can guarantee that each point of the sensing area is covered by at least one sensor node, and what a sufficient condition to guarantee the network connectivity? In this paper, we propose an appropriate probabilistic model which provides the coverage and connectivity in k-sensing detection of a wireless sensor network. We have proved the capability of our approach using a geometric analysis and a probabilistic model.     

Recent Advances in Sensing Applications of Graphene Assemblies and Their Composites

Development of next‐generation sensor devices is gaining tremendous attention in both academia and industry because of their broad applications in manufacturing processes, food and environment control, medicine, disease diagnostics, security and defense, aerospace, and so forth. Current challenges include the development of low‐cost, ultrahigh, and user‐friendly sensors, which have high selectivity, fast response and recovery times, and small dimensions. The critical demands of these new sensors are typically associated with advanced nanoscale sensing materials. Among them, graphene and its derivatives have demonstrated the ideal properties to overcome these challenges and have merged as one of the most popular sensing platforms for diverse applications. A broad range of graphene assemblies with different architectures, morphologies, and scales (from nano‐, micro‐, to macrosize) have been explored in recent years for designing new high‐performing sensing devices. Herein, this study presents and discusses recent advances in synthesis strategies of assembled graphene‐based superstructures of 1D, 2D, and 3D macroscopic shapes in the forms of fibers, thin films, and foams/aerogels. The fabricated state‐of‐the‐art applications of these materials in gas and vapor, biomedical, piezoresistive strain and pressure, heavy metal ion, and temperature sensors are also systematically reviewed and discussed, and their sensing performance is compared.     

Electrochemical microsensors

A critical review of recent developments in electrochemical microsensors is presented. The main emphasis is on chemiresistors and potentiometric microsensors. Both types of sensors have reached a degree of considerable maturity. It appears that the main future thrust can be expected in development of microfabricated sensing arrays based on these two principles.     

Reduced delay sensitivity to process induced variability in current sensing interconnects

The effect of process induced variability in long global on-chip interconnects caused by critical dimension control and intrinsic fluctuation of transistor threshold voltage is analysed for current and voltage mode signalling. Projections in scaled CMOS technologies show that current sensing interconnects exhibit smaller mean delay and sensitivity to parameter fluctuations. The standard deviation of delay exhibits an increasing dependency on process variations at the low and high extremes of receiver to driver circuit resistance ratios. An experimental on-chip bus demonstrates the reduced delay variability in current sensing schemes.     

Non-reconstruction compressive detector for wideband spectrum sensing based on GLRT

Spectrum sensing is an essential ability to detect spectral holes in cognitive radio (CR) networks. The critical challenge to spectrum sensing in the wideband frequency range is how to sense quickly and accurately. Compressive sensing(CS) theory can be employed to detect signals from a small set of non-adaptive, linear measurements without fully recovering the signal. However, the existing compressive detectors can only detect some known deterministic signals and it is not suitable for the time-varying amplitude signal, such as spectrum sensing signals in CR networks. First, a model of signal detect is proposed by utilizing compressive sampling without signal recovery, and then the generalized likelihood ratio test (GLRT) detection algorithm of the time-varying amplitude signal is derived in detail. Finally, the theoretical detection performance bound and the computation complexity are analyzed. The comparison between the theory and simulation results of signal detection performance over Rayleigh and Rician channel demonstrates the validity of the performance bound. Compared with the reconstructed spectrum sensing detection algorithm, the proposed algorithm greatly reduces the data volume and algorithm complexity for the signal with random amplitudes.     

COGNITIVE RADIOS FOR DYNAMIC SPECTRUM ACCESS - Dynamic Frequency Hopping Communities for Efficient IEEE 802.22 Operation

One of the key challenges of the emerging cognitive radio-based IEEE 802.22 wireless regional area networks (WRANs) is to address two apparently conflicting requirements: ensuring QoS satisfaction for WRAN services while providing reliable spectrum sensing for guaranteeing licensed user protection. To perform reliable sensing, in the basic operation mode on a single frequency band (non-hopping mode), one must allocate quiet times, that is, periodically interrupt data transmission that could impair the QoS of WRAN. This critical issue can be addressed by an alternative operation mode proposed in 802.22 called dynamic frequency hopping (DFH), where WRAN data transmission is performed in parallel with spectrum sensing without interruptions. DFH community, as described in this article, is a mechanism that coordinates multiple WRAN cells operating in the DFH mode, such that efficient frequency usage and reliable channel sensing are achieved. The key idea of DFH community is that neighboring WRAN cells form cooperating communities that coordinate their DFH operations     

Spectrum inpainting: a new framework for spectrum status determination in large cognitive radio networks

In this paper, the problem of spectrum status determination is considered for large cognitive radio (CR) ad hoc networks. Spectrum sensing and spectrum decision are critical for cognitive radio network throughput and hence obtaining accurate knowledge of the spectrum status is vitally important to better spectrum usage decisions. The major challenge of this type of problem lies in the fact that for a network covering a large geographical area, only very limited measurements of spectrum occupancy during spectrum sensing may be obtained by the CR users for a certain location in any given time slot. This is due to both the hardware limitations as well as the tradeoff between spectrum sensing time and data throughput of the CR users. By representing the spectrum sensing results across the network as an image, spectrum status determination is formulated as an image recovery problem. The method of total variation inpainting is applied to solve the problem with low determination error. The proposed method takes advantage of the correlations in multiple dimensions and the numerical results demonstrate the effectiveness of the proposed scheme.