Abstract:Although long-wavelength infrared imaging technology is crucial in applications such as terrestrial remote sensing and astronomy, it faces a fundamental challenge from the overwhelming thermal background radiation. This background photon flux often pushes conventional detectors to the limits of their background-limited performance (BLIP). The main limiting factor here is not the intrinsic noise of the detector, but the shot noise of the background itself. In this paper, a key classification is demonstrated to distinguish between two superficially similar but fundamentally different detection architectures (difference detector and differential detector). According to the application and implementation of the detector, the background photocurrent of the conventional difference detector sets a background-determined threshold for the detectable signal difference, while the differential detector is a device that directly measures the differences of the target physical quantities at the physical perception level. Only the weak difference signals are integrated, resulting in extensive cumulative sampling to improve the signal-to-noise ratio to an unprecedented level. In particular, the differential detection technology path based on the quantum well infrared photodetector (QWIP) is introduced. QWIP provides an ideal physical basis for realizing high-performance long-wavelength infrared differential detectors with its extremely low dark current, precise electrical controllability and intrinsic spectral selectivity, and has made significant progress in experiments. Finally, Fisher information theory and Cramer-Rao bound are used to provide rigorous theoretical support for differential detectors.

Abstract:Compared with the monochromatic detector, the two-color detector has higher detection accuracy and is the typical representative of third-generation infrared detectors. Type-II superlattice has outstanding advantages such as wide absorption spectrum and high uniformity, and can be used to prepare two-color detectors. Annealing technology can improve the performance of two-color type-II superlattice devices by improving the quality of sidewall passivation and the quality of contact between materials and electrodes. By conducting a series of annealing experiments at different temperatures on the device, the effect of annealing on the performance of mid-/long-wavelength two-color type-II superlattice infrared focal plane devices is analyzed and studied. By optimizing the annealing process, the long-wavelength corresponding impedance of the pnp structure device can be increased by 4.6 times, and the long-wavelength corresponding impedance of the npn structure device can be increased by 31%. Compared with improving device performance by optimizing material structure and device structure, annealing has outstanding advantages such as high efficiency and simplicity. This study has certain reference significance for the performance improvement of mid-/long-wavelength twocolor type-II superlattice infrared focal plane devices.

Abstract:In the research field of infrared transparent conductive films, alleviating the contradiction between high transmittance and low resistivity is a major scientific challenge. The molecular beam epitaxy (MBE) technique is used to study the effect of growth temperature on the electrical properties of indium-doped cadmium selenide (CdSe:In) films, and a transparent conductive film with a high mobility of 204 cm²·V^-1·s^-1 and a low resistivity of 6.95×10^-5 Ω·m is prepared. The film exhibits a high transmittance of more than 87% in the 1－4 μm waveband. The results of the temperature-dependent characteristics study show that there are three temperature ranges for the conductivity of the film, which are distinguished by the transition of the carrier transportation mechanism. Compared with other reported mid-infrared transparent conductive films, it can be seen that the CdSe:In film shows obvious advantages in carrier mobility and transmittance. This study lays an experimental and theoretical foundation for the application of CdSe:In films in mid-infrared detectors.

Abstract:In view of the importance of the concentration of engine tail flame components to the infrared spectrum radiation intensity, an efficient infrared spectrum concentration solution model is proposed, namely the CARS-CNN-GRU model which combines the competitive adaptive reweighted sampling (CARS) algorithm with the convolutional neural network (CNN)-gated recurrent unit (GRU) deep learning algorithm. This method uses the CARS algorithm to select the key wavelengths and obtain the tail flame component concentration information. Then the CNN-GRU model is used to perform long-range dependency analysis on the sequence data to achieve multi-scale feature extraction. Simulation results show that compared with the traditional models, the CARS-CNN-GRU model has higher accuracy in solving H₂O and CO₂ concentrations. Its root mean square error (RMSE) is reduced to 0.0014 and 0.0017, respectively. The R² value is 0.999 and 0.998, respectively; the mean absolute error (MAE) is 0.0011 and 0.0014, respectively. The CARS-CNN-GRU model proposed in this paper shows superior performance in solving infrared spectral concentration. Compared with traditional methods, it has higher accuracy, stability and reliability, and provides strong support for stealth technology, environmental monitoring and combustion efficiency evaluation in the military and civil aviation fields.

Abstract:Terahertz (THz) technology has great potential in the next generation of wireless communications due to its abundant spectrum resources. Electronic device-based systems have very limited device bandwidth when used to generate THz waves, which restricts the growth of system throughput, while photonics-aided THz systems are expensive and complex in structure. To solve this problem, a terahertz system using Delta-Sigma modulation (DSM) is proposed. In the study, a set of 0.15 THz 1024-QAM signals is generated and a 2-meter free-space wireless THz wave transmission system is successfully demonstrated. In addition, inspired by the rapid error propagation in DSM demodulation, a method combining digital signal processing (DSP) with complex-valued neural network (CVNN) is proposed to improve the bit error rate (BER) performance of 1024-QAM signals. When the BER soft-decision is 2×10^-2, the sensitivity of the receiver is improved by 0.5 dB. The method proposed in this paper can effectively solve the problems caused by noise in traditional quadrature amplitude modulation (QAM) to improve the spectrum efficiency of electronic devices with insufficient bandwidth.

Abstract:In order to understand the characteristics and dynamic changes of the eco-climate in the Yangtze River Delta (YRD) urban agglomeration, based on the daily observation data of air temperature, precipitation, relative humidity and wind speed from 111 meteorological stations in the region, as well as the MODIS normalized difference vegetation index (NDVI) and land surface temperature (LST) data, remote sensing, GIS and principal component analysis (PCA) methods were used, and the existing remote sensing ecological index (RSEI) was improved. A regional integrated eco-climatic index (IECI) model was constructed from the aspects of dryness/wetness, comfortableness, greenness, heat and air cleanliness, and the dynamic change characteristics of the eco-climate in YRD urban agglomeration were analyzed. The results showed that during the period from 2001 to 2018, the fractional vegetation cover (FVC) of the urban agglomeration increased significantly with a linear trend of 2.80% per decade, the mixed layer height (MLH) decreased significantly at a rate of 51.3 m per decade, and the regional IECI decreased significantly with a linear trend of 0.10 per decade, showing a regional overall decreasing trend. Human activities and urbanization have significant effects on eco-climate change in the YRD urban agglomeration. It is necessary to strengthen the protection and improvement of eco-climate while promoting economic and social development, so as to achieve harmonious coexistence between humans and nature.