Journal of Infrared and Millimeter Waves

ESIT 2024: Gathering of Global Minds to Hangzhou for Cutting-Edge Infrared and Terahertz Innovation
Welcome to our new Editorial Board Members Prof. Manijeh Razeghi
Welcome to our new Editorial Board Members Dr. He Zhiping
Welcome to our new Editorial Board Members Dr. Jun Ge
Welcome to our new Editorial Board Members Dr. Ye Zhenhua
Welcome to our new Editorial Board Members Dr. Chen Fansheng

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Infrared Physics, Materials and Devices

The Research on Polarization-tunable Terahertz GaAs Photoconductive Antenna array

Dong Chengang, Shi Wei, Han Xiaowei, Wang Zhiquan, Wang Xin, Zhang Xiuxing

DOI: 10.11972/j.issn.1001-9014.XXXX.XX.001

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As an important emitter of terahertz radiation, the traditional antenna has limited flexibility due to its fixed polarization state. In response to this issue, we have designed and studied a polarization-adjustable four-element terahertz gallium arsenide photoconductive antenna array, aiming to enhance its versatility and applicability in various applications. By precisely controlling the excitation of each element, the antenna array can achieve precise control of linearly and circularly polarized terahertz waves through in-phase unequal amplitude excitation and phase difference excitation. The results show that with in-phase unequal amplitude excitation, flexible control of linearly polarized terahertz waves within a 360-degree range can be achieved. With a 90-degree phase difference excitation, circularly polarized terahertz waves are generated, with a -10 dB impedance bandwidth range of 0.057 THz to 1.013 THz and a relative bandwidth of 178.69%. The axial ratio bandwidth range is 0.815 THz to 0.947 THz, with a relative bandwidth of 14.98%.
The study of hyperspectral remote sensing air traffic control monitoring based on contrails cloud proposal

Yang Lifeng, Feng Yanqing, WangJianyu

DOI: 10.11972/j.issn.1001-9014.XXXX.XX.001

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To address the issues of low detection rate and high false alarm rate caused by complex background during sub-pixel aerial aircraft detection in hyperspectral remote sensing image, an aerial aircraft detection method was proposed based on contrails cloud proposal. Firstly, a hyperspectral semantic segmentation model was used to search for the contrails cloud, and ROIs of aircraft were proposed to reduce invalid search ranges and suppress false alarms based on the contrails cloud; Secondly, an endmember extraction algorithm based on dictionary learning and semi-blind non-negative matrix factorization was proposed to improve the accuracy of aircraft endmember extraction for hyperspectral subpixels; Finally, verification experiments were carried out on the hyperspectral remote sensing image dataset of gaofen-5 satellite, and the results demonstrated that the algorithm proposed in this paper can effectively suppress false alarms in complex scenes, and significantly improve the detection rate and detection accuracy of sub-pixel aerial vehicles.
Infrared small target detection algorithm via Partial Sum of the Tensor Nuclear Norm and direction residual weighting

SUN Bin, XIA Xing-Ling, FU Rong-Guo, SHI Liang

DOI: 10.11972/j.issn.1001-9014.XXXX.XX.001

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Aiming at the problem that infrared small target detection faces low contrast between the background and the target and insufficient noise suppression ability under the complex cloud background, an infrared small target detection method based on the tensor nuclear norm and direction residual weighting is proposed. Based on converting the infrared image into an infrared patch tensor model, from the perspective of the low-rank nature of the background tensor, and taking advantage of the difference in contrast between the background and the target in different directions, we design a double-neighborhood local contrast based on direction residual weighting method (DNLCDRW) combined with the partial sum of tensor nuclear norm (PSTNN) to achieve effective background suppression and recovery of infrared small targets. Experiments show that the algorithm is effective in suppressing the background and improving the detection ability of the target.

Infrared Optoelectronic System and Application Technology

Research progress on infrared temperature measurement for low emissivity object

HUANG Shan-Jie, ZHAO Jin-Song, WANG Ling-Xue, SONG Teng-Fei, XU Fang-Yu, CAI Yi

DOI: 10.11972/j.issn.1001-9014.XXXX.XX.001

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Smooth objects such as metals， optical mirrors， and silicon wafers generally have extremely low emissivity and high reflectivity， and are called low emissivity objects.The extremely weak radiation from low emissivity objects will be submerged by the environmental radiation reflected from their surface. Infrared temperature measurement of low emissivity objects has always been a challenge in the field of infrared temperature measurement. Due to the continuously growing demand for non-contact temperature measurement of low emissivity objects in fields such as metal smelting， solar telescope thermal control， and semiconductor production， a large number of infrared temperature measurement methods for low emissivity objects have been proposed. First， this paper elaborates on the difficulties of the infrared temperature measurement of low emissivity objects and summarizes the temperature measurement methods currently used for low emissivity objects into five categories. Then， the basic principles and technical routes of each temperature measurement method were summarized， and the advantages and disadvantages of each temperature measurement method were analyzed in detail. Finally， the possible development directions of temperature measurement for low emissivity objects were discussed.

Infrared Physics, Materials and Devices

Study of time and frequency domain characteristics of a quasi-continuous 2 μm thulium-doped fiber laser

MEI Xue-Han, CHEN Xiang, XU Gang, YANG Yuan-Zhong, ZHANG Zhong, LEI Cheng, LI Sheng, WANG Xing-Huan, WANG Du

DOI: 10.11972/j.issn.1001-9014.XXXX.XX.001

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Lasers near the wavelength of 2 μm are located in the atmospheric transmission window and the strong absorption peak of water， and have important applications in medicine， LIDAR， material processing， and as pump sources for mid-infrared lasers. The thulium-doped fiber laser （TDFL） stands out as a critical light source capable of delivering high power outputs at this wavelength. In this paper， to address the problems of relaxation oscillation and inter-modal four-wave mixing in quasi-continuous wave （QCW） TDFL， the time and frequency-domain output characteristics of the laser are optimized by increasing the bias current， optimizing the length of the gain fiber， and changing the diameter of the fiber coiling， etc. The effects of different gain fiber structures on the fiber transmission modes are also investigated. The developed QCW-TDFL achieves a peak power of 894 W and an average power of 89.4 W at a central wavelength of 1939.2 nm with a pulse width of 100 μs， a repetition frequency of 1 kHz and a duty cycle of 10%， and obtains stable and controllable pulse output waveforms and spectral characteristics.

Interdisciplinary Research on Infrared Science

A lightweight dark object detection network on infrared images

Li Zhaoxu, Xu Qingyu, An Wei, He Xu, Guo Gaowei, Li Miao, Ling Qiang, Wang Longguang, Xiao Chao, Lin Zaiping

DOI: 10.11972/j.issn.1001-9014.XXXX.XX.001

Abstract: (195) HTML (0) PDF (1.24 MKB)(283)

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Small target detection has been a classic research topic in the field of infrared image processing, and the objects are usually brighter than the local background. However, in some scenarios, the target brightness may be lower than the background brightness. For example, the civil airplanes usually have low-temperature skin when cruising, appearing as dark points on medium spatial resolution thermal infrared satellite images. There are few features of these objects, so the current detection networks are redundant. Hence, authors proposed a lightweight dark object detection network, AirFormer. It only has 37.1K parameters and 46.2M floating-point operations on a 256×256 image. Considering the lack of infrared dark object detection dataset, authors analyzed the characteristics of airplanes on thermal infrared satellite images, and then developed a simulated flying aircraft detection dataset called IRAir. AirFormer achieves 71.0% at recall and 82.6% at detection precision on the IRAir dataset. In addition, after training on simulated data, AirFormer has achieved detection of real flying airplanes on the thermal infrared satellite images.

Infrared Physics, Materials and Devices

The Research on Aircraft Altitude Estimate Method Based on Multispectral Feature Matching in Thermal Infrared

Yang Lifeng, Chen Zhuo, Chen Fansheng, WangJianyu

DOI: 10.11972/j.issn.1001-9014.XXXX.XX.001

Abstract: (103) HTML (0) PDF (1.36 MKB)(149)

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The acquisition of aircraft altitude information is crucial for aviation safety and traffic control applications. Infrared remote sensing technology can accurately measure the thermal radiation information of targets, which means there is potential for quantitative observation of certain characteristics of aircraft target. A method for estimating the altitude of airborne targets based on infrared multi-channel feature matching is proposed in this paper. Firstly, a thermal infrared radiation characteristic observation model of aircraft is established, which based on the thermal infrared radiation characteristics of large aircraft and atmospheric radiative transfer models. Secondly, based on the observation model, a spectral database of aircraft方 at different altitudes and flight states under different atmospheric condition can be obtained by simulating. Thirdly, target spectral information can be extracted from remote sensing images and the altitude information can be estimated with using spectral angle matching (SAM). Finally, verification and analysis were completed using simulation data and SDGSAT-1 in-orbit data. The results indicate that the proposed method can achieve kilometer-level estimation accuracy for aircraft at cruising altitude. This method provides a new solution for estimating the altitude of aircraft and has important application potential.

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Research on low-power consumption, high heat dissipation efficiency terahertz quantum cascade laser

TAN Cheng, YAN Chuan-Feng, ZANG Shan-Zhi, WANG Kai, GAN Liang-Hua, CAO Chen-Tao, CHEN Bing-Qi, CHEN Hong-Tai, ZHANG Yue-Heng, FANG Yu-Long, XU Gang-Yi

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A single-mode terahertz quantum cascade laser (THz-QCL) with a two-dimensional patch antenna array as a resonant cavity is proposed and realized. The active region of each patch antenna is sandwiched between two metal layers, exhibiting full-scale subwavelength characteristics and exciting a vertical electric quadrupole mode with low radiation loss. The inter-antenna coupling within the array effectively suppresses electromagnetic leakage in the plane, allowing for a high-quality factor and low threshold current density even with only a few antennas in the array. As a result, the laser's power consumption is reduced to 950 mW. Moreover, the discrete antenna array design provides a larger heat dissipation area compared to the heat-generating area, and with the lateral heat dissipation channels offered by the unpumped regions, the thermal resistance per unit area is as low as 5.6 mK/W/cm2. By significantly reducing power consumption and enhancing heat dissipation efficiency, the laser achieves a lasing frequency of 3.18 THz, a side-mode suppression ratio (SMSR) of 19.5dB, and a beam divergence angle of 35°× 35°. It operates continuously at 3.14 mW at 20 K, with a maximum continuous operation temperature of 90 K, notably higher than that of Fabry-Pérot cavity lasers made from the same material. This work provides a novel approach to improving the continuous operating temperature of THz-QCLs.
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An Improved Template Matching Algorithm for Infrared Cross-Target Center Positioning Based on Self-Constructed Convolution Kernels

yuandijian, XU Xin-Ke, LIU Tong, WANG Jin-Wen, DU Yu

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Target center positioning is a critical technology in the calibration process of infrared thermal imagers. Given the relatively complex morphology of target images, we propose a center positioning algorithm based on improved template matching with self-constructed convolution kernels. The algorithm first constructs a normalized template with target image features and performs matching operations on downsampled and preprocessed target images to obtain coarse positioning results. Based on the coarse positioning center, the original image undergoes ROI fine matching, and further correction is achieved through a subpixel subdivision algorithm, ultimately determining the precise target center position. This algorithm effectively detects target images with blurring and indistinct edge features, avoiding interference from blurring, occlusion, complex backgrounds, or indistinct features. It demonstrates good robustness, accurately positions the target center, and operates at high speed. Compared to traditional template matching methods like CCORR, NCC, and Hough transform, it offers significant improvements and meets the positioning requirements in the automatic calibration process of infrared thermal imagers.
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Infrared remote sensing image super-resolution network by fusion of dense connection and multi-attention mechanism

XU Xinhao, WANG Jun, WANG Feng, Sun Shengli

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Space-borne infrared remote sensing images have crucial application value in the fields of environmental monitoring and military reconnaissance. Nonetheless, due to limitations in technologies, atmospheric disturbances, and sensor noise, these images suffer from insufficient resolution and blurred texture details, severely restricting the accuracy of subsequent analysis and processing. To address these issues, a new super-resolution generative adversarial network model is proposed. This model integrates dense connections with the Swin Transformer architecture to achieve effective cross-layer feature transmission and contextual information utilization while enhancing the model's global feature extraction capabilities. Furthermore, we improve the traditional residual connections with multi-scale channel attention-based feature fusion, allowing the network to more flexibly integrate multi-scale features, thereby enhancing the quality and efficiency of feature fusion. A combined loss function is constructed to comprehensively optimize the performance of the generator. Comparative tests on different datasets demonstrate significant improvements with the proposed algorithm. Additionally, the super-resolved images exhibit higher performance in downstream tasks such as object detection, confirming the effectiveness and application potential of the algorithm in space-borne infrared remote sensing image super-resolution.
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Infrared UAV Detection Based on Multi-Channel Interactive Attention Mechanism and Edge Contour Enhancement

Nie Su-Zhen, CAO Jie, HAO Qun, ZHUANG Xu-Ye

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UAVs have a wide range of applications in agriculture, logistics, rescue and disaster relief because of their compactness, lightness and flexibility. However, if they are used improperly or mismanaged, they may not only cause personal privacy leakage and property loss, but also pose a threat to public safety and even military security. Therefore, real-time and accurate detection and warning of UAVs in the airspace plays an important role. In this regard, a multi-channel interactive attention and edge contour enhancement (MCIAECE) method for infrared UAV detection is proposed. Firstly, the shallow and deep features of the infrared image are extracted by constructing a multi-channel consisting of a multi-channel interactive attention mechanism module and an edge contour enhancement module, after which the attention mechanism enhances the target features while the edge contour enhancement obtains more detailed information. Then the extracted features of each layer are fused and enhanced using the multilevel feature fusion module to obtain the detection results. The experimental results show that better results can be achieved with multi-channel interactive attention and edge contour enhancement on all three datasets. Among them, the best results are obtained on the NUDT-SIRST infrared dataset, with the detection probability and intersection and concurrency ratio of 98.83% and 85.11% respectively compared with the baseline network, and the effect is significant in the edge contour restoration of the target compared with other methods.
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Design and preparation of LWDM AWG for 1.6Tbps and above data center

HuangSong, CUI Peng-Wei, WANG Yue, WANG Liang-Liang, ZHANG Jia-Shun, MA Jun-Chi, ZHANG Chun-Xue, GUO Li-Yong, YANG Han-Ming, WU Yuan-Da, AN Jun-Ming

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A 16-channel arrayed waveguide grating (AWG) with an 800 GHz channel spacing in the O-band has been developed and fabricated based on silica planar lightwave circuit (PLC) technology. By extending the wavelength allocation from 8 channels to 16 channels as specified in IEEE 802.3bs, we increased the number of channels and boosted transmission capacity to meet the 1.6 Tbps and higher-speed signal transmission requirements for future data centers. Through optimizing the AWG structure, it has achieved insertion loss (IL) better than -1.61 dB, loss uniformity below 0.35 dB, polarization-dependent loss (PDL) below 0.35 dB, adjacent channel crosstalk under -20.05 dB, ripple less than 0.75 dB, center wavelength offset under 0.22 nm and 1 dB bandwidth exceeding 2.88 nm. The AWG has been successfully measured to transmit 53 Gbaud 4-level pulse amplitude modulation (PAM4) signal per channel and the total transmission speed can reach 1.6Tbps and above.
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Performance analysis of electro-optic sampling detection technique with thin GaSe crystal in mid-infrared band

DU Hai-Wei, WANG Jing-Yi, LI Qiang-Shuang, SUN Chang-Ming

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Electro-optic sampling (EOS) detection technique has been widely used in the terahertz science and technology, and it also can measure the field time waveform of the few-cycle laser pulse. Its frequency response and band limitation are determined directly by the electro-optic crystal and duration of the probe laser pulse. Here, we investigate the performance of the EOS with thin GaSe crystal in the measurement of the mid-infrared few-cycle laser pulse. The shift of the central frequency and the change of the bandwidth induced by the EOS detection are calculated, and then the pulse distortions induced in the detection process are discussed. It is found that this technique produces a red-shift of the central frequency and narrowing of the bandwidth. These changings decrease when the laser wavelength increase from 2 ?m to 10 ?m. This work can help to estimate the performance of the EOS detection technique in the mid-infrared band and offer a reference for the related experiment as well.
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Structural Design of a Wide-ridge Mid-wave Infrared Quantum Cascade Laser Based on a Supersymmetric Waveguide

DU Shu-Hao, ZHENG Xian-Tong, JIA Han, CUI Jin-Tao, ZHANG Shi-Ya, LIU Yuan, FENG Yu-Lin, LIU Ming, ZHANG Dong-Liang

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In the process of power scaling large-area quantum cascade lasers (QCLs), challenges such as degradation of beam quality and emission of multilobe far-field modes are frequently encountered. These issues become particularly pronounced with an increase in ridge width, resulting in multimode problems. To tackle this, an innovative multiridge waveguide structure based on the principle of supersymmetry (SUSY) was proposed. This structure comprises a wider main waveguide in the center and two narrower auxiliary waveguides on either side. The high-order modes of the main waveguide are coupled with the modes of the auxiliary waveguides through mode-matching design, and the optical loss of the auxiliary waveguides suppresses these modes, thereby achieving fundamental mode lasing of the wider main waveguide. This paper employs the finite difference eigenmode (FDE) method to perform detailed structural modelling and simulation optimization of the 4.6 μm wavelength quantum cascade laser, successfully achieving a single transverse mode QCL with a ridge width of 10 μm. In comparison to the traditional single-mode QCL(with a ridge width at about 5 μm), the MRW structure has the potential to increase the gain area of the laser by 100%. This offers a novel design concept and methodology for enhancing the single-mode luminous power of mid-infrared quantum cascade lasers, which is of considerable significance.
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Research on the Punch-through Phenomenon of Separate Absorption, Charge, and Multiplication Avalanche Photodetectors

LI Chong, MA Zi-Yi, YANG Shuai, LIU Yue-Wen, WANG Jia-Xuan, LIU Yun-Fei, DONG Yu-Sen, LI Zi-Qian, LIU Dian-Bo

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In this paper, the punch-through phenomenon was studied, based on a fabricated separate absorption, charge, and multiplication avalanche photodetector (SACM APD). The spectral response, capacitance characteristics, and I-V characteristics at different operating temperatures of the APD were measured and analyzed. Meanwhile, the device performance before and after the punch-through phenomenon were compared, and the model of the electric field region formed by external voltage was analyzed, based on the measurement results and the simulated the electric field and energy band distributions by the SILVACO. When the ion implantation energy of the charge layer was 580keV, the simulated device has a punch-through voltage of -30V and a capacitance reduction of one-third before punch-through. Then a Si SACM APD was prepared based on CMOS process. The punch-through voltage of the device was -30V and the capacitance was reduced to 1/3@1MHz before punch-through, which exactly match the simulation results. Moreover, the photocurrent after punch-through increases to 2.18 times of the before value at 808nm. The peak responsivity increases from 0.171A/W@590nm to 0.377A/W@820nm.
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Study on Correlation of Thermal Model to in-Orbit Data for Infrared Optical Payloads on FY-3E/HIRAS-II

LI Yu-Han, YANG Bao-Yu, ZHANG Qiang, GUO Zhi-Peng, WU Yi-Nong, TANG Xiao, LI Shang-Ju

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The Infrared Hyperspectral Atmospheric Sounder II (HIRAS-II) is the key equipment on Funyun-3E (FY-3E) satellite, which can realize vertical atmospheric detection, featuring hyper spectral, high sensitivity and high precision. To ensure its accuracy of detection, it is necessary to correlate their thermal models to in-orbit data. In this work, an investigation of intelligent correlation method named Intelligent Correlation Platform for Thermal Model (ICP-TM) was established, the advanced Kriging surrogate model and efficient adaptive region optimization algorithm were introduced. After correlation with this method for FY-3E/HIRAS-II, the results indicate that compared with the data in orbit, the error of the thermal model has decreased from 5 K to within ±1 K in cold case (10℃). Then the correlated model is validated in hot case (20℃), and the correlated model exhibits good universality. This correlation precision is also much superior to the general ones like 3 K in other similar literatures. Furthermore, the process is finished in 8 days using ICP-TM, the efficiency is much better than 3 months based on manual. The results show that the proposed approach significantly enhances the accuracy and efficiency of thermal model, this contributes to the precise thermal control of subsequent infrared optical payloads.
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Multi-physics coupling-based multi-parameter joint optimization technique for aerial target infrared detection

DING Xiang, QIAO Kai

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One of the key areas of advancement in space-based infrared sensing is the high-sensitivity detection of small and weak targets. A major innovation in this regard is the design of the infrared detection system indicator, which is influenced by the characteristics of the target background radiation. The effectiveness of space-based infrared detection is significantly challenged by airborne targets, especially civil aircraft. These targets are active in the upper troposphere and lower stratosphere. They exhibit weak and variable radiation characteristics due to complex background clutter and atmospheric attenuation. Aiming to address this issue, this paper proposes a multi-parameter joint optimization method for an airborne target infrared detection system based on the coupling of multiple physical effects. Firstly, the initial optimization of the target detection spectral band in the sky is completed based on the spectral radiation characteristics of the target, the background, and the spectral atmospheric transmittance change characteristics of the target-sky-based detection platform. Subsequently, the detection sensitivity requirements are proposed. Then, a system parameter optimization method is established with the target motion speed limit, earth background limit, and detection sensitivity as the three major boundaries. This method facilitates the creation of an infrared detection index system for air targets.
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Analysis of Infrared Polarization Characteristics and Modeling of Operating Distance on Aerostat Platform in Sea Fog

YE Min-Rui, CUI Wen-Nan, HUANG Xia-Yang, ZHANG Tao

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The study aims to reveal the detection advantages of infrared polarization imaging systems on aerostat platforms against the background of sea fog. Firstly, based on the polarization bidirectional reflection distribution function, the study analyzes the variation of polarization characteristics with observation angles, indicating the applicability of infrared polarization in oblique viewing from aerostats. Secondly, using Monte Carlo method and the MRTD model, the study constructs a model for the maximum operating distance of infrared polarization imaging systems, thereby verifying the advantages of infrared polarization imaging over infrared intensity imaging in maintaining features and detection distance under sea fog conditions. This provides theoretical analysis and simulation evidence for the deployment of infrared polarization detection technology on aerostat platforms.
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A near-infrared all-fiber mode monitor based on the mini-two-path Mach-Zehnder interferometer

ZHU Xiao-Jun, LIU Yu, WU Yue, ZHUANG Hao-Ran, SUN Dan, SHI Yue-Chun, CAO Juan, YANG Yong-Jie

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A novel near-infrared all-fiber mode monitor based on a mini-two-path Mach-Zehnder interferometer (MTP-MZI) is proposed. The MTP-MZI mode monitor is created by fusing a section of no-core fiber (NCF) and a single-mode fiber (SMF) together with an optical fiber fusion splicer, establishing two distinct centimeter-level optical transmission paths. Since the high-order modes in NCF transmit near-infrared light more sensitively to curvature-induced energy leakage than the fundamental mode in SMF, the near-infrared high-order mode light leaks out of NCF when the curvature changes, causing the MTP-MZI transmission spectrum to change. By analyzing the relationship between the curvature, transmission spectrum, and spatial frequency spectrum, the modes involved in the interference can be analyzed, thereby revealing the mode transmission characteristics of near-infrared light in optical fibers. In the verification experiments, higher-order modes were excited by inserting a novel hollow-core fiber (HCF) into the MTP-MZI. When the curvature of the MTP-MZI changes, the near-infrared light high-order mode introduced into the device leaks out, causing the transmission spectrum to return to its original state before bending and before the HCF was spliced. The experimental verification shows that the MTP-MZI can be used as an all-fiber mode monitoring device to monitor the modes introduced into the optical fiber from the outside, providing experimental and theoretical basis for near-infrared all-fiber mode monitoring in optical information systems.
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Sparsity and Self-Similarity Priors Guided Deep Learning for Blind Image Super-Resolution

GE Sun-Yi, LUO Xiao-Wei, FENG Shi-Yang, WANG Bin

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Blind image super-resolution (BISR) aims to restore corresponding high-resolution (HR) images from low-resolution (LR) images with unknown degradation, becoming a research hotspot in the field of computer vision. Due to the ill-posed nature of this problem, the rational selection and utilization of image priors have become key to solving it. However, existing deep learning-based BISR algorithms only employ neural networks to learn the mapping from LR to HR images in an end-to-end manner, only allowing the network to implicitly learn image priors, resulting in somewhat blurry super-resolution results. A deep learning-based BISR algorithm guided by sparsity and self-similarity priors is proposed to address the above issues. Initially, for various LR image inputs, a dynamic linear kernel estimation module is employed to effectively estimate the corresponding blur kernels; Subsequently, a deep unfolding deconvolution filtering module based on the Fast Iterative Shrinkage-Thresholding Algorithm (FISTA) is utilized to explicitly model the sparsity prior of signal, achieving deconvolution restoration of the degraded images; Finally, a dual-path multi-scale large receptive field restoration module leverages the self-similarity prior of images for super-resolution recovery. Experimental results on the public Gaussian8 and DIV2KRK datasets demonstrate that, compared to existing methods, the proposed algorithm not only achieves the highest restoration metrics but also delivers superior visual quality in the recovered images.
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Study on the preparation and spectroscopic ellipsometry of 2H-MoTe₂quantum dot films

LI Guo-Bin, HU Kun, ZHANG Tai-Wei, YANG Ao, XIA Yi-Ping, LI Xue-Ming, TANG Li-Bin, YANG Pei-Zhi, WANG Shan-Li, CHEN Sheng-Di, YANG Li, ZHANG Yan

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The preparation of quantum dot thin films and the accurate determination of optical constants are particularly important in the development and application of their optoelectronic fields. At present, the optical constants of MoTe2 single-crystal films prepared by mechanical exfoliation and chemical vapor deposition are relatively mature. However, the optical constants of 2H-MoTe2 quantum dot films are rarely reported. 2H-MoTe2 quantum dots were prepared by ultrasonic assisted liquid phase exfoliation, and two sizes of 2H-MoTe2 quantum dots were prepared by changing the type of solvent and ultrasonic order. The optical constants such as refractive index, extinction coefficient and dielectric constant of quantum dot films of two sizes were studied by B-spline model and Tauc-Lorentz model using ellipsometry. The results show that the two sizes of 2H-MoTe2 quantum dots have similar refractive index, extinction coefficient and a wider spectral absorption in the visible to near infrared band. And compared with MoTe2 bulk material, it has a lower dielectric constant.
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Waveform frequency domain matching-based positioning method for Gaofen-7 satellite lidar footprints

ZHOU Si-Han, ZHAO Pu-Fan, YANG Jian, HAN Qi-Jin, WANG Heng, MA Yue, ZHOU Hui, LI Song

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The laser altimeter aboard the Gaofen-7 satellite primarily provides elevation control points for imagery. During satellite operations, environmental variations can induce laser pointing offsets, which in turn increase the positioning errors of the footprints, thereby directly reducing the elevation accuracy of the control points. This issue is particularly pronounced in complex mountainous terrains. To enhance the reliability of laser altimeter observations from satellites in such regions, this paper proposed a new laser footprint positioning method based on waveform frequency domain matching. This method utilizes high-precision terrain data for waveform simulation and determines the position of the laser footprint by calculating the correlation between the simulated waveforms and the received waveforms of Gaofen-7 in the frequency domain. Additionally, systematic deviations in laser pointing are derived from the joint computational results of multi-footprint frequency domain matching. Experiments were conducted using in three regions: central Montana, western Wyoming, and eastern Utah in the United States. The results indicate that the standard deviations of footprint planar offset distances, planar true north pinch angles, and equivalent laser pointing deviation angles obtained with this method are all superior to those achieved with the time-domain waveform matching method. The findings underscore the advantages of frequency-domain waveform matching in achieving high-precision footprint localization, thereby providing a robust foundation for enhancing the utility of satellite laser altimeter observations in challenging environments and facilitating the correction of laser altimeter pointing errors.
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Simulation and Evaluation of Mid-Infrared Sea Surface Sun Glint Directional Radiation

zhangzhenwu, WANG Ning, MA Ling-Ling, ZHANG Bei-Bei, ZHAO Yong-Guang, LI Wan

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The energy received in the mid-infrared (MIR) band at the sensor's aperture includes both reflected solar energy and the emitted energy from the Earth's surface. Typically, the reflected solar energy in this band is weak; however, under certain conditions, such as in sun glint regions over the sea surface, the reflected solar energy detected by the MIR channel can be substantial. Currently, the application of sun glint physical models in the MIR band is not well understood. This study investigates the accuracy of applying different visible light and shortwave infrared sun glint models to the MIR band. The paper selects three models: Breon-Henriot, Ebuchi-Kizu, and Wu, and evaluates the sensitivity of each sun glint model. Subsequently, using four selected MODIS sun glint images as data sources, and combining them with ERA5 reanalysis data matched to satellite data for atmospheric parameter calculations, the solar radiation intensity reflected by the sea surface is computed using the three models. The accuracy of each model is then further validated with an MIR radiative transfer model. The results show that the Breon-Henriot model generally performs best in terms of correlation coefficient and root mean square error compared to MODIS measurements. These findings not only extend the application range of sun glint models in the MIR band but also enhance the MIR forward modeling system, providing new theoretical support for MIR radiative transfer and improving the effectiveness and accuracy of MIR remote sensing products in climate change monitoring and sea surface temperature dynamic analysis.
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A High Output Power 340GHz Balanced Frequency Doubler Design Based on Linear Optimization Method

Zhicheng Liu, Jingtao Zhou, Jin Meng, Haomiao Wei, Chengyue Yang, Yongbo Su, Zhi Jin, Rui Jia

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Abstract:

In this paper, a linear optimization method(LOM) for the design of terahertz circuits is presented, aimed at enhancing simulation efficacy and reducing the time of the circuit design workflow. This method enables the rapid determination of optimal embedding impedance for diodes across a specific bandwidth to achieve maximum efficiency through harmonic balance simulations. By optimizing the linear matching circuit with the optimal embedding impedance, the method effectively segregates the simulation of the linear segments from the nonlinear segments in the frequency multiplier circuit, substantially increasing the speed of simulations. The design of on-chip linear matching circuits adopts a modular circuit design strategy, incorporating fixed load resistors to simplify the matching challenge. Utilizing this approach, a 340GHz frequency doubler was developed and measured. The results demonstrate that, across a bandwidth of 330GHz to 342GHz, the efficiency of the doubler remains above 10%, with an input power ranging from 98mW to 141mW and an output power exceeding 13mW. Notably, at an input power of 141mW, a peak output power of 21.8mW was achieved at 334GHz, corresponding to an efficiency of 15.8%.
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BDMFuse: Multi-Scale Network Fusion for Infrared and Visible Images Based on base and Detail Features

Si Hai-ping, Zhao Wen-rui, Li Ting-ting, Li Fei-tao, Feiernanduo.Basang, Sun Chang-xia, Li Yan-ling

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Abstract:

The result of infrared and visible image fusion should highlight the significant targets of the infrared image while preserving the visible light texture details. In order to satisfy the above requirements, this paper proposes an automated encoder-based infrared and visible image fusion method. The encoder constructs both a base encoder and a detail encoder according to the optimization objective. The base encoder extracts low-frequency information from the image, while the detail encoder captures high-frequency information. Since this extraction method may miss some information, we introduce a compensation encoder to supplement the missing information. Additionally, we introduce multi-scale decomposition for the encoder to extract image features more comprehensively. The image features obtained by the encoders are then fed into the decoder. The decoder first adds the low-frequency, high-frequency and compensatory information to obtain multi-scale features. An attention map is derived from these multi-scale features and multiplied with the fused image at the corresponding scale. The Fusion module is introduced in the multi-scale fusion process to achieve image reconstruction. The network proposed in this paper demonstrates its effectiveness on the TNO, RoadScene, and LLVIP datasets. Experiments show that our network can better perceive changes in light, effectively extract image detail information, and produce fused images that are more aligned with human visual perception.
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Urban Tree Species Classification with Multispectral Airborne LiDAR

Peilun Hu, Yuwei Chen, Mohammad Imangholiloo, Markus Holopainen, Yicheng Wang, Juha Hyyppä

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Abstract:

Urban tree species provide various essential ecosystem services in cities, such as mediating urban temperature, isolating noise, fixing carbon, and alleviating the urban heat island effect. The quality of these services is influenced by species diversity, tree growth status, and the distribution and composition of trees. Traditionally, data about urban trees has been gathered through field data collection and manual interpretation of remote sensing images. In this study, we evaluate the capacity of using Multispectral Airborne Laser Scanning (ALS) data to classify 24 common urban roadside tree species in Espoo, Finland. We utilized tree crown structure information, intensity features, and spectral information for classification. The results demonstrated an overall accuracy of 71.5% using multispectral LiDAR data, highlighting that combining structural and spectral information in a single frame could enhance classification accuracy. In the future, we will focus on identifying the most important features in species classification and finding algorithms with higher efficiency and accuracy.
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Tidal flats extraction in the coastal zone based on time-series Sentinel-2 imagery and near-infrared tidal flats indices

zhourujia, XIA Qing, ZHENG Qiong, ZHU Li-Hong, LI Bin, Li Jianhua, SONG Jia

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Abstract:

When extracting coastal zone tidal flats using remote sensing transient images, the influence of tides greatly limits the accuracy of tidal flat spatial distribution extraction. In this paper, based on the Google Earth Engine (GEE) cloud platform, a coastal zone tidal flats extraction method by combining the time-series Sentinel-2 image and the tidal flats index is proposed. First, based on the Sentinel-2 time-series image data, we use the quantile synthesis method to generate high- and low-tide images, and then analyze the spectral reflectance characteristics of different land classes on the high- and low-tide images. A NIR-band tidal flat extraction index that excludes the interference of the tidal transient is constructed. Secondly, the image spectral information and the tidal flat extraction index are input into a machine learning algorithm to realize fast and efficient extraction of the tidal flat. Finally, the separability of the tidal flats index and the universality are investigated. The results show that the tidal flats extraction index constructed in this research had a good separability for tidal flats, the overall accuracy of tidal flats extraction was 93.02%, the Kappa coefficient was 0.86, and the proposed method has good applicability to remote sensing images containing near-infrared bands. This method can realize automatic and rapid tidal flat extraction, and provide data support for the sustainable management and protection of coastal zone resources.
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Detection and quantification of water / ice in typical lunar minerals using Raman spectroscopy

WEN Dao-Yuan-Tian, Zhao Hai-Ting, LIU Xiang-Feng, XU Wei-Ming, XU Xue-Sen, LEI Xin-Rui, SHU Rong

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Abstract:

The water in lunar materials can promote the evolution of lunar geology and environment and provide the necessary conditions for the utilization of lunar resource. Owing to the low resolution of lunar remote sensing methods, it is difficult to obtain direct evidence of water / ice or determine its form of occurrence. Laser Raman spectroscopy can obtain fingerprint information of minerals and water bodies without the need for illumination, sample pretreatment, and non-destructive, providing direct and favorable information regarding the type, distribution range, and content of lunar materials. In this study, Raman spectroscopy was used to detect the water-containing characteristics of typical lunar rocks/minerals and forms such as adsorbed water, ice, crystalline water, and hydroxyl-structured water, and quantitatively analyze the water content. First, a 532 nm laser micro-Raman spectroscopy was used to identify and analyze the water-containing signals of typical lunar minerals and various forms of water in lunar soil simulants. Second, the detection limits of adsorbed water, crystalline water, and hydroxyl-structured water in lunar soil simulants were examined and analyzed, along with the patterns between their content and signal intensity. Finaly, linear regression (LR), ridge regression (RR), and partial least squares regression (PLSR) were employed for quantitatively analyze of the contents of three forms of water in the lunar soil simulants. The results show that (1) the characteristic spectral peaks of the four forms of water in the lunar soil simulants can be clearly identified. The peak distribution regions of the lunar soil simulants components and water bodies are located at 100-1700 cm-1 and 2600-3900 cm-1, respectively. The characteristic spectral peaks of water are manifested as a combination of broad envelope peaks of hydrogen-bonded OH and sharp peaks of non-hydrogen-bonded OH stretching vibrations in varying proportions. (2) Detection limits of adsorbed water, crystalline water (MgSO4·7H2O), and hydroxyl water (Al2Si2O5(OH)4) in the lunar soil simulants are 1.3 wt%, 0.8 wt%, and 0.3 wt%, respectively. (3) A linear relationship exists between the intensity of water-containing peaks and the water content in the lunar soil simulants, with root mean square errors of 1.75 wt%, 1.16 wt%, and 1.19 wt% obtained through LR, RR, and PLSR.
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Simulation design of short-wave infrared heterogeneous phototransistor for weak light detection

LIAO Ke-Cai, HUANG Min, WANG Nan, LIANG Zhao-Ming, ZHOU Yi, CHEN Jian-Xin

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Abstract:

The sensitivity of the detector is the core technical indicator of the infrared detector. Short-wave infrared detector has low dark current and the sensitivity will be limited by the inherent read-out circuit noise of the detection system. Therefore, it is an effective way to further enhance the sensitivity by introducing internal gain into the detector. Heterogeneous phototransistor takes advantages of high gain, low operating bias, and low excess noise, which provides novel approach for high-sensitive detection. This paper mainly focuses on the simulation design of InGaAs/GaAsSb type-II superlattice short-wave infrared phototransistor, and studies the dependence of the device size on the optoelectronic characteristics. The results show that a higher gain, a lower dark current, and a faster response can be achieved by a smaller base size. Based on the optimization design of size structure, a sensitivity with a noise equivalent photon lower than 10 can be achieved, which provides a new technical approach to achieve high-sensitive heterogeneous phototransistor detector.
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Infrared small target detection method based on nonconvex tensor Tuck decomposition with factor prior

yangjungang, 刘婷, liuyongxian, liboyang, wangyingqian, shengweidong, anwei

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Abstract:

Low-rank and sparse decomposition method (LRSD) has been widely concerned in the field of infrared small target detection because of its good detection performance. However, existing LRSD-based methods still face the problems of low detection performance and slow detection speed in complex scenes. Although existing low-rank Tuck decomposition methods achieve satisfactory detection performance in complex scenes, they need to define ranks in advance according to experience, and too large or too small the estimated ranks will lead to missed detection or false alarms. Meanwhile, the size of rank is different in different scenes. This means that they are not suitable for real-world scenes. To solve this problem, this paper uses non-convex rank approach norm to constrain latent factors of low-rank Tucker decomposition, which avoids setting ranks in advance according to experience and improves the robustness of the algorithm in different scenes. Meanwhile, an symmetric GaussSeidel (sGS) based alternating direction method of multipliers algorithm (sGSADMM) is designed to solve the proposed method. Different from ADMM, the sGSADMM algorithm can use more structural information to obtain higher accuracy. Extensive experiment results show that the proposed method is superior to other advanced algorithms in detection performance and background suppression.
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中文版

Volume 43,2024 Issue 5

Infrared Physics, Materials and Devices

Millimeter Waves and Terahertz Technology

Infrared Spectroscopy and Remote Sensing Technology

Remote Sensing Technology and Application

Infrared Optoelectronic System and Application Technology

Interdisciplinary Research on Infrared Science

Infrared Physics, Materials and Devices

Infrared Optoelectronic System and Application Technology

Infrared Physics, Materials and Devices

Interdisciplinary Research on Infrared Science

Infrared Physics, Materials and Devices

Volume 43,2024 Issue 5

Infrared Spectroscopy and Remote Sensing Technology

Interdisciplinary Research on Infrared Science

Remote Sensing Technology and Application

Infrared Physics, Materials and Devices

Millimeter Waves and Terahertz Technology

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