Abstract:A very high quantum efficiency InAs/GaSb T2SL mid-wavelength infrared （MWIR） photodetector has been grown by molecular beam epitaxy （MBE）. The T2SL detector structure material exhibited smooth surface with step-flow growth and excellent structural homogeneity. The 50% cut-off wavelength was about 5.5 μm. The peak current responsivity was 2.6 A/W corresponding to a quantum efficiency over 80% at 77 K， which was comparable to that of MCT. At 77 K， the dark current density at -50 mV bias was 1.8×10^-6 A/cm² and the resistance-area product （RA） at maximum （-50 mV bias） was 3.8×10⁵ Ω·cm². The peak detectivity was calculated to be 6.1 × 10¹² cm Hz^1/2/W.

Abstract:The optical constants for the absorbing layer material， satisfying high efficiency of the photon-to-heat conversion of a four-layer structure from ultraviolet to near-infrared wavelength range， are theoretically studied. By employing the effective medium approximation （EMA） model， the measured optical properties of the composite materials （cermet） show in great agreement with that of the simulated ones. Furthermore， a four-layer film structure with high photon-to-heat conversion efficiency using Ti-MgF₂ cermet as the absorption layer is proposed to have a high absorptance of about 95.1% achieved in the wavelength range of 300~1 600 nm. The research results provide a new method to realize high-efficiency photon-to-heat conversion devices and show excellent application prospects.

Abstract:This paper proposes a 3- mid-infrared band polarization-independent and CMOS-compatible graphene modulator， which mainly includes two parts： the mode conversion structure and the graphene modulator. This modulator not only fulfills the requirement of compatibility with CMOS， but also can achieve polarization-independent modulation of the fundamental mode. Simulation results show that this modulator can achieve an extinction ratio（ER） higher than 20 dB in the mid-infrared band from 2.95 to 3.05 ， the insert loss for both TE and TM modes are less than 1.3 dB， and polarization-dependent loss is less than 1.09 dB. Through the calculation， the 3 dB bandwidth up to 9.47 GHz can be obtained when the length of the device is 420 .

Abstract:We report the preparation and photoresponse of MoS₂ films with different layers grown on c-Al₂O₃ by pulsed laser deposition （PLD）. The phonon modes and crystallographic orientation discussed by Raman scattering and X-ray diffraction （XRD） prove that the MoS₂ films are of pure 2H-phase. The S/Mo ratio of film is identified as 1.92：1 derived by X-ray photoelectron （XPS） experiments. The blue and red shifts of the Mo 3d peaks for XPS data indicate the existence of oxidation and sulfur defects in the films. Moreover， by Raman and photoluminescence （PL） mapping， the film thickness is proven to be uniform. The temperature-dependent photoresponse of monolayer MoS₂ film indicates that the temperature plays an important role in the photoresponse intensity and response time. The present results can provide a reference for further improving the performance of MoS₂-based photodetectors.

Abstract:Finite element analysis software was used to analyze the stress distribution of the original detector module and the detector module adding Kovar equilibrium layer. The simulation results showed that the thermal stress of the detector HgCdTe epitaxial layer decreased to some extent after adding the equilibrium layer， while the low-temperature warpage variable at the center of the detector chip surface decreased significantly. Without changing the material of the equilibrium layer， when the thickness of the equilibrium layer is 0.2 mm， 0.5 mm， 1 mm， 1.5 mm and 2 mm， the maximum stress on the HgCdTe chip first decreases greatly and then increases slightly with the increase of the thickness of the equilibrium layer. When the value of thickness is 1 mm， the maximum thermal stress on the detector chip is the lowest. Thermal stress level of large infrared detector chip can be improved by adding Kovar equilibrium layer.

Abstract:The enhanced visible-near infrared light absorber has important application potentials in many fields such as photoelectric signal conversion， detection， communication， and sensing. In this paper， based on the principle of Gires-Tournois resonator resonance absorption， an all-aluminum-based planar thin-film stacked metamaterial light wave absorber is proposed. The device is composed of a sub-wavelength Al/Al₂O₃/Al three-layer film structure. Through optimal selection of appropriate parameters， the absorption peak position is continuously adjustable from visible to near infrared， the absorption peak is close to 100%， and the variable angle reflection spectra show that the device is not sensitive to the incident angle. The theoretical calculation results are in perfect agreement with the experimental results. The absorber with a perfect absorption wavelength near 500 nm heats up rapidly under 532 nm laser irradiation， and the maximum temperature can reach 55.4 °C， indicating potential applications in the field of photothermal conversion.

Abstract:The superconductivity in InN is the foundation for the all III-V semiconductor based superconductor/semiconductor integration. To study the flux pinning properties of InN superconductor， the I-V relationships， R-B transitions， and R-T transitions are investigated. The scaling results of I-V curves indicate there is a vortex glass-liquid transition. The R-T curves are well fitted by thermally activated flux flow （TAFF） model. The TAFF activated energy satisfies a power-law relationship with magnetic field， but it has two different exponents under the low magnetic field and high magnetic field. We explain it as the result of a transition from single flux pinning to collective flux pinning which also leads to the rapid attenuation of critical current as the magnetic field increases. By analyzing the temperature dependence of critical current， we found the dominant δL-pinning mechanism. Furthermore， the dependence of pinning force on magnetic field is analyzed using the Dew-Hughes model， and the results show that the main pinning center is the point pinning. Our work paves the way for studying III-nitrides based hybrid superconductor-semiconductor devices.

Abstract:In this paper， the RF power performance and surface temperature distributions for a multi-finger power hetero-junction bipolar transistor （HBT） with non-uniform emitter finger spacing （NUEFS） without the use of emitter-ballasting-resistor （EBR） are measured， and are compared with a multi-finger power HBT with EBR. The experiment results show that for the multi-finger power HBT with NUEFS， the highest surface temperature is lowered， the uniformity of surface temperature distributions measured by US QFI Infrared TMS is improved， the RF power gain and power-added-efficiency （PAE） are increased compared with the multi-finger power HBT with EBR respectively. These results could be attributed to the improvement in positive thermoelectric feedback and thermal coupling effects among the fingers， and the riddance of adverse impact from emitter-ballasting-resistor used in traditional power HBT.

Abstract:Aiming at the problem that the received signal quality drops sharply when transmit and receive beams have angular deviations in a mobile millimeter wave communication scenario， this paper proposes a beam tracking algorithm based on Adaptive Unscented Kalman Filter （AUKF）. Considering the applicability of low complexity for mobile scenarios， this algorithm designs an effective beam tracking scheme. In the analog beam forming architecture， a beam pair is trained to track an electromagnetic wave path to maintain an effective millimeter wave communication. By introducing an adaptive adjustment factor， the prediction and observation covariance matrices can be adjusted adaptive when there is an abnormal disturbance in the system， improving the estimation accuracy and the convergence speed. Simulation results show that the adaptive Unscented Kalman Filter algorithm in this paper significantly reduces beam tracking errors in mobile environments and has robust beam tracking capabilities.

Abstract:A method to overcome the problem of limited dynamic range in current radar-cross-section （RCS） measuring systems in the terahertz band was proposed， by adopting structural subsection calibration and data subsection processing. The limitation of onefold calibration on the RCS measurement range and accuracy was analyzed based on the relative calibration theory， and verified by experimental measurement of a smooth metal sphere and a smooth metal cylinder. A smooth metal plate was also used to discuss the effect of using signal attenuators on the system measuring range and accuracy. Finally， the measurement of the RCS of a warhead model was realized by structural subsection calibration combined with data subsection processing， and the main scattering characteristics were successfully recognized. The measuring dynamic range reached 63 dB， which should be the highest as far as we know. The measured results accorded well with the simulation results.

Abstract:An integrated multi-beam traveling wave tube based on Multi-Corrugated Waveguide SWS （MCW） is investigated by simulation and cold test in this paper. The MCW SWS is adopted here for its high coupling impedance and its natural multi-beam tunnels， then a Ka-band integrated three-beam traveling wave tube amplifier with MCW is designed. The interaction circuit is fabricated by CNC milling with oxygen-free high conductance copper. The cold test is found to be in great consistency with simulation and the S₁₁ is lower than -15 dB from 32~39 GHz. Using CST PIC Studio， the PIC simulation is performed for the interaction circuit with 50-periods SWSs and three beams with 12.9 kV voltage and 67 mA current. The simulation shows significantly better output power， gain， and electronic efficiency than DCW. The maximum output power is about 132.8 W with corresponding electronic efficiency of 5.12% and gain of 41.2 dB. The high power and high efficiency performance of the proposed MCW TWT provides potential application for point-to-multipoint transmission based millimeter-wave wireless system.

Abstract:Sensitivity is an important radiation performance index of remote sensor. In this paper， the sensitivity concept of infrared hyper-spectral sounding is extended from the sounder noise sensitivity to the atmospheric parameter sensitivity and the surface temperature error sensitivity for the on-orbit application of sounder. The corresponding sensitivity calculation models and their relations are introduced. These models are applied to the sensitivity evaluation of the first infrared hyper-spectral atmospheric sounder on geostationary meteorological satellite FY-4A GIIRS. With the sounder test data and the atmospheric historical statistical data， we obtained the quantitative variation characteristics of the atmospheric parameter sensitivities （atmospheric temperature， water vapor， ozone， CO₂， CH₄ and N₂O）， the surface temperature error sensitivity and the sounder noise sensitivity with the channel. The physical mechanisms of these characteristics are analyzed. The results show that， as a whole， the sensitivities of atmospheric temperature， water vapor and ozone are much higher than that of the sounder noise and surface temperature error， while the sensitivities of CO₂， CH₄ and N₂O are submerged by the sounder noise sensitivity and the surface temperature error sensitivity. The study lays a foundation for the signal-to-noise ratio evaluation of infrared hyper-spectral atmospheric parameters detection， and is helpful for the optimization of infrared hyper-spectral atmospheric sounding channels.

Abstract:In the measurement of source emissions， it is inevitably interfered by the gas emissions from the adjacent fields and turbulence， which affects the accuracy of gas detection. In order to improve the measurement accuracy， the measurement method of composite non-point sources non-uniformity methane emissions based on laser spectrum detection has been studied. Moreover， the interference in external environment is reduced with multiple self-calibration measurements. A detection system for composite non-point source emissions has been established， and the detection method of eliminating gas fluctuation has been proposed. First， the accuracy verification test has been carried out. The standard deviation of source a is 0.17， and that of source b is 0.18. Subsequently， a comparative test has been carried out with the extraction method of the photo acoustic spectrum， and the correlation coefficient reached 0.91. Finally， the actual field measurement has been carried out to monitor the two non-uniform emission sources caused by different fertilization methods to achieve accurate measurement. It has practical engineering value such as agricultural gas emission and environmental gas detection.

Abstract:A new single-stage deep convolution detection network is proposed to solve the complex background problem of night light remote sensing. Firstly， a classification network is designed by extracting high-dimensional features and then selecting features， and the influence of different channel number networks of noise reduction is studied. A prior box matching of gray-scale energy is proposed， inputting a low-noise and high-quality matching box into SSD detection network， and the idea of integral diagram is used to simplify the calculation. By adding sequential connection and dense connection to improve the global semantic module， the cross layered information interaction of the network is introduced， and its attention map comprehensively considers the high and low receptive fields to effectively distinguish small targets and background noise. Experimental results of the night light remote sensing data set show that the designed network has advantages over the rest single-stage network， which has a better detection effect of the building area under the complex background.

Abstract:Full-waveform airborne LiDAR （FWL） is able to record complete echo signals as waveforms， including useful information such as elevation details and backscatter coefficients of the target， but the waveform information data cannot be obtained directly. Waveform decomposition is an important method to process waveform data to extract effective information. In view of the shortcoming of common used parameter optimization algorithm in waveform decomposition which is sensitive to initial value and prone to local optimization， a waveform decomposition method based on Modified Differential Evolution （MDE） algorithm is proposed： the generalized Gaussian function is taken as the model， after the initial estimation， a global MDE optimization algorithm is used for the parameter optimization， and the point cloud is finally generated. Experimental results show that， compared with the waveform decomposition method based on other optimization algorithms， this method has been obviously improved in terms of the decomposition and point position accuracy.

Abstract:As the weak absorption intensity and high interference signals in the thermal infrared band of carbon monoxide （CO）， it is difficult to retrieve CO profiles with promising accuracy from thermal infrared data. The development and application of ultra-spectral infrared detector make it possible to improve the retrieval accuracy of CO profile. However， the ultra-spectral resolution and the huge channel numbers of the data not only enhance the abundant atmospheric retrieval information， but also induce lots of redundant information. As such， it is necessary to do the channel selection to ensure the accuracy and efficiency of retrieval. In this paper， a channel selection method considering both channel sensitivity and weighting function characteristics is proposed to CO profile retrieval of ultra-spectral infrared data. First， by analyzing the gas sensitivity of the channels in CO absorption band， the channels severely affected by other gases are excluded and initial channel group is obtained. Then， the weighting function characteristics of the initial channel group are studied. The channels located at the bottom and top of the peaks at the CO absorption spectrum， suggesting abundant gas retrieval information about different atmospheric layer， are selected as the final channel selection results. The channel selection method is applied for the winter and summer air masses in Alxa desert area， Beijing-Tianjin area， Yangtze River Delta， and Pearl River Delta. By comparing with the Optimal Sensitivity Profile method （OSP）， the channels selected by the proposed method can cover a wider spectral range and have more CO absorption characteristics. Additionally， the application of the proposed method can improve the retrieval accuracy of CO profiles in all the regions and seasons studied in this paper. The best improvement effect was observed in the Alxa desert area in the winter， whose root mean square error （RMSE） was reduced from 3.23×10^-8 g/g to 3.07×10^-8 g/g， with an average increase in accuracy of 10.56%.

Abstract:It is a highly important and challenging task to finish the high-accuracy hyperspectral image classification using fewer training samples. A novel hyperspectral image-based classification method （hereafter referred to as the LBP-SSKNN） was proposed by combing Local Binary Patterns （LBP） and K-Nearest Neighbors （KNN）. First， the Principal Component Analysis （PCA） was used to reduce the dimension of hyperspectral image. Subsequently， the LBP was used to extract the spatial texture information and the spatial and spectral features were uniformly scaled to form the spatial-spectral vectors. Finally， the vectors were input into the KNN classifier to obtain the classification result. The training and test datasets of three popular open hyperspectral datasets were used to validate the proposed method， including Pavia University， Indian Pines and Salinas. the classification method was verified on three groups of hyperspectral remote sensing image datasets. In addition， three classic classifiers were also selected to compare the LBP-SSKNN， including Radial Basis Function Support Vector Machine （RBF-SVM） and Kernel Simultaneous Orthogonal Matching Pursuit （KSOMP）. In the Pavia University dataset and Indian Pines dataset， the 10% of training dataset were randomly selected as the training samples. The overall accuracy （OA） and Kappa coefficient reach 99.15%， 98.87% and 97.88%， 97.58%， respectively. In the Salinas dataset， only the 2% of training dataset were randomly selected as the training samples， and the OA and Kappa coefficient reach 98.46% and 98.29%. The experimental results show that the OA of LBP-SSKNN method can still reach more than 98% under the 10% and even 2% of the training dataset. Our proposed method can satisfy the high-accuracy requirement due to limited training samples in practical application scenes.

Abstract:Three-dimensional reconstruction technology has been widely used in the field of industrial automation. However， traditional 3D reconstruction methods are difficult to obtain accurate results from high-temperature products of industrial production lines such as glass and forgings that are characterized by a single surface structure， high reflectivity and no texture， because these high temperature products generate infrared polarized radiation. We propose a three-dimensional reconstruction method of the target based on infrared radiation polarization imaging. First， we establish an infrared polarization radiation model， and analyze the relationship between the infrared radiation polarization state and the normal vector of the target surface. Finally， we obtain the three-dimensional morphology of the target surface by integrating the normal vectors. The method does not rely on the structure and texture information about the target surface， has low lighting requirements， and can reconstruct the 3D morphology of the target surface with only one data acquisition. Therefore， it is easy to implement and has a wide range of applications.

Abstract:Satellite-to-ground quantum key distribution（QKD） has verified the feasibility of wide-area quantum communication networks. Towards to the future multi-users of quantum communication networks， being able to accurately and quickly predict the key rate is the core issue for quantum network. This paper proposes a new channel prediction method based on machine learning and stellar image recognition， and applies this method to the observation of the Beijing ground station. The experimental results show that the stellar image recognition accuracy rate can reach 88%， and provide the suggestion on whether to carry out a QKD experiment. In the case of the recommended channel for satellite-to-ground QKD， it is estimated that the average rate of sifted key at elevation angle of 39.5°is about 8~9 kbit/s， and the measured sifted key rate is 8.8 kbit/s. The experimental results can be used to reasonably arrange satellite-to-ground QKD tasks of multiple satellites and multiple ground stations. Moreover， this work can improve the success rate of satellite-to-ground quantum communication， avoid wasting satellite and ground station resources， and promote the practical research of satellite-based quantum communication networking.