This PDF file contains the front matter associated with SPIE Proceedings Volume 13493, including the Title Page, Copyright information, Table of Contents, and Conference Committee information.

The spectral resolution of The Temporally and Spatially Modulated Fourier Transform Imaging Spectrometer (TSMFTIS) is mainly determined by the optical focal length, lateral shear, and the performance of the infrared focal plane array (FPA) in combination. However, due to the limited number and density of pixels in the FPA, the lateral shear of the optical system is constrained, resulting in the overall spectral resolution of the instrument unable to be higher. Therefore, this paper proposes achieving super-sampling of the detector for interference images by performing multiple subpixel shifts on the FPA detector. This method supports the continuous increase of lateral shear amount, ultimately improving the overall spectral resolution of the instrument. Experimental results show that using a 384x288 uncooled infrared FPA and under conditions of eightfold super-sampling and 8000μm lateral shear, the instrument's spectral resolution increased from 15.75 cm-1 to 2.31 cm-1.

The Internet of Things technology has improved the accessibility and efficiency of educational resources while promoting innovation and the development of educational models. The Internet of Things technology has been widely applied in the operation and maintenance of smart classrooms in universities. However, the existing operation and maintenance mechanism of smart classrooms based on the Internet of Things technology have some problems such as insufficient system planning, stacking of intelligent devices, poor adaptability to technological iteration and updates, low efficiency in fault handling, and high complexity in operation and maintenance. Therefore, we proposed a cloud-edge-end architecture based on the Internet of Things and developed a digital twin visualization platform for the operation and maintenance of smart classrooms in universities. We offered integrated solutions for the supervision, testing, use, and service of intelligent devices and information systems, and provided a new approach for the operation and maintenance of smart classrooms in universities.

Near-infrared spectroscopy (NIRS) technology has a wide range of potential applications in hemoglobin detection, but its accuracy is susceptible to noise and background interference. In order to improve the accuracy of quantitative analysis of hemoglobin in blood NIRS spectra, this study introduces a hybrid method (WPT-FS-WOA), which integrates wavelet packet transform (WPT), fuzzy shrinkage (FS), and Whale Optimization Algorithm (WOA) for hemoglobin feature band extraction. The method uses WPT to decompose the blood near-infrared spectrum at multiple scales, applies FS to denoise the wavelet packet node coefficients for data affiliation assessment, and combines WOA to optimize the wavelet packet nodes at different frequencies, and finally reconstructs the hemoglobin feature spectrum. The analysis of real blood data shows that this method can effectively capture the hemoglobin spectral features compared with the traditional preprocessing techniques.

Infrared (IR) small target detection problem has attracted increasing attention. Tensor theory-based detection techniques have been widely utilized, while facing challenges such as tensor structures, background and target estimation. This paper proposes an IR dim and small target detection method based on 5-D spatial-temporal knowledge (5D-STD). Specifically, a 5-D whitened spatial-temporal patch-tensor is constructed. Then, we design a 5-D tensor nuclear norm for background estimation and a Moreau envelope-derived sparsity estimation norm. Furthermore, we establish a low-rank and sparse decomposition model with an alternating direction method of multipliers (ADMM)-based optimization scheme for IR target detection. Extensive experiments conducted on three real IR sequences prove the superiority of 5D-STD in terms of target detectability, background suppressibility and overall performance.

A directional coupled emission external ring cavity (ERC) based on an interband cascaded laser (ICL) was designed and manufactured. The laser emitted from the front cavity facet of the Fabry-Perot ICL is vertically incident on the rear cavity facet through the blazed grating and three gold-plated reflection mirrors, thereby forming a closed-loop system. The laser emitted from the front and rear cavity facets form clockwise and counterclockwise traveling waves in ERC, respectively. Since the anti-reflection film coating only on the front cavity facet introduces different losses in two directions, resulting in directional coupling in the clockwise direction. And the 0th-order reflected light generated by the directional coupling light passing through the blazed grating is used as the output light. The emitted laser from the two cavity facets enter the ICL again through ERC, enhancing the gain of the ICL. Therefore, a higher output power and wider tuning range are achieved compared to the traditional external cavity with 0th-order diffracted light as output light. The output power of ERC-ICL is 75% of the output power of the corresponding Fabry-Perot ICL, which is much higher than the output power of Littrow external cavity ICL. And single-mode operation is observed within the tuning range of 163 cm-1 (220nm), which is twice the tuning range of Littrow external cavity.

In response to the deployment requirements of target recognition algorithms based on convolutional neural networks (CNN) on embedded platforms, this paper proposes a hardware accelerator based on the Digital Signal Processor (DSP) + Field Programmable Gate Array (FPGA) architecture, aiming to overcome the current issues of low recognition speed and low hardware resource utilization. The system is designed based on the 6678 series DSP and the V7 series FPGA. The DSP is used as the host computer, and the design of various operators required in the CNN are completed in the FPGA as the core computing module of the accelerator. This architecture enables flexibility in implementing different neural networks by configuring different instruction sets. Within the core computing module of the FPGA, this design completes the implementation of operators such as Convolution, MaxPool, Upsample, Concat, and Split, and further focuses on optimizing the Convolution operator. For the Convolution operator, a parallel acceleration method is adopted, which improves computational speed. Moreover, a method of input reuse is adopted to minimize the number of memory accesses. Additionally, a new feature map data input cache module is designed, which reduces the occupancy of on-chip hardware resources while minimizing the time from inputting image to the start of convolution calculation, enhancing the system's real-time performance. Finally, the system is used to accelerate the You Only Look Once (YOLO) neural network. It achieves a single-frame recognition time of 135.63ms for a 640×640-sized image at 200MHZ, with a throughput of up to 100.132GOPS.

The infrared radiation characteristics of ballistic missile were of great significance to the penetration capability an d detection technology. Based on the Trident II ICBM, the infrared radiation characteristics of the ballistic missile in the medium-wave infrared radiation of the boost, middle and re-entry range. The results show that the total radiation intensity of medium wave in the boost section was 3.23×10⁵W/sr, the particle radiation contribution was 77.84%, and the contribution of gas was 21.22%. Attention must be paid to the influence of solid particle and gas radiation; the total radiation intensity of long wave was weaker than the medium wave, 1.44×10⁵W/sr. The particle radiation contribution was higher than the middle wave at 91.38%. The transmittance of long wave radiation in the atmosphere was significantly higher than that of medium wave; the long wave radiation was lower than the middle wave in the order of 1~10²; the highest temperature of the head was about 2333K, the total radiation intensity of medium wave was equal to 10³, with high military application value for the improvement of ballistic missile infrared stealth performance and optimization of infrared detection technology.

The infrared radiation characteristics of space targets have been applied in the fields of target detection, classification, and identification. This paper simulates the infrared radiation characteristics and dynamic imaging of space targets using spaceborne detection systems. The study investigates the infrared radiation characteristics of space targets in the 4.2~6μm, 5.5~7μm, and 8~12μm bands. Additionally, a spaceborne network detection scenario was established to update the relative positions of detection satellites and targets in real-time. By modeling and simulating the infrared radiation characteristics of mid-course warheads and decoys, a sequence of satellite-detected infrared images under various detection conditions was generated. This research provides a reference for infrared imaging methods for the detection, classification, and identification of space targets.

In recent years, hypersonic aircraft have played an increasingly important role in modern battlefields, and detecting and warning hypersonic aircraft has become a research hotspot. In order to study and verify the effective detection range of space-based infrared satellite warning systems for hypersonic aircraft, we established an approximate equivalent model of the X-51A tail flame, calculated the infrared radiation characteristics in two atmospheric infrared window bands, and drew radiation intensity distribution maps of the tail flame in different directions in three-dimensional space. The parameters of GEO-1, the first geostationary orbit satellite of the SBIRS, were obtained through research. The detection distance of this system was calculated, and its detection and early warning capabilities for hypersonic aircraft were analyzed. The simulation results show that the radiation level of the X-51A tail flame calculated based on the model in this article is basically consistent with the literature, and the tail flame radiation reaches its maximum at an angle of 55° to the axial direction. The maximum detection range of the space-based infrared warning satellite was calculated to be around 10⁷ - 10⁸m, which is consistent with the actual situation and verifies its ability to effectively detect targets in theory.

The study of infrared radiation characteristics of buildings is of great significance in target identification, infrared precision guidance, remote sensing detection, urban planning and non-destructive testing protection of buildings under modern war. This paper takes a buildings as the research object, analyzes the infrared radiation characteristics of the buildings, and establishes the theoretical calculation model of its temperature field. Firstly, starting from various parameters of the buildings, this paper determines the geometric parameters, physical parameters, geographical parameters and meteorological parameters of the buildings through literature and field measurement. Then, the buildings is divided into two-dimensional meshes to determine the spatial position of each mesh and the geometric relationship with adjacent meshes. Each grid is regarded as a node by the control volume method, and the heat balance equation of each grid is established by using heat transfer and infrared radiation theory. The external surface of the buildings considers the environmental radiation, including solar radiation, atmospheric radiation, earth radiation, etc., plus the thermal radiation of the target itself. Constant temperature and no internal heat source environment shall be considered for the inner surface. The heat conduction between each grid is considered. Finally, the temperature distribution of the buildings surface at each time is obtained by measuring the initial temperature of the buildings. Finally, its infrared radiation characteristics are further studied.

Aiming at the urgent need of infrared radiation characteristics of different types of targets of interest under typical sea conditions in the development of high-precision missile infrared imaging guidance weapons, a model data-driven infrared radiation modeling method was developed. Firstly, by studying the influence factors of the system's full link in the Marine environment, the atmospheric radiative transfer model is constructed, and the theoretical values of the target and background parameters are calculated. Secondly, through the consistency comparison between the measured results and the theoretical model, the simulation target model is iterated to improve the system accuracy. Finally, the measured radiation luminance data of different bands and the theoretical modeling data of the same ship target in head-on and side-head-on attitude are compared and analyzed. The results show that the model prediction is in good agreement with the measured results, and the error is less than 15%. The proposed model is reliable and feasible, which can lay a model foundation for the follow-up development of infrared imaging guidelines, and provide technical support for the detection and recognition of sea surface targets.

By adopting the vacuum sealed-ampoule technique, P-type doping of Zn elements in the lattice-mismatched NInAs_0.6P_0.4/i-In_0.8Ga_0.2As/N-InP heterostructure material was achieved to form PN junction. The diffusion mechanism of Zn in the material was studied using secondary ion mass spectrometry (SIMS) and scanning capacitance microscopy (SCM). Furthermore, the temperature-dependent photoelectric properties were investigated after the short-wave infrared (SWIR) detector was fabricated and packaged in a vacuum Dewar. The results indicate that the doped Zn elements in the material are not fully activated, leading to a PN junction depth smaller than the diffusion depth, and rapid thermal processing (RTP) does not affect the PN junction depth. The cutoff long-wavelength of the detector at 273K is 2.53 μm, and the peak detectivity reaches a peak value of 2.42×10¹¹ cm•Hz^1/2/W at 133K.

The analog counter counts the input pulses by increasing the analog voltage. The input pulse controls the charging and discharging process of the counting capacitor to increase the voltage on the capacitor, and the voltage value is proportional to the number of pulses. There are two main design methods for analog counter: one is to charge the capacitor through a current source within a certain period of time, and the voltage on the capacitor increases during each high-level pulse; The second is the redistribution of charge between two capacitors, transferring the charge on the small capacitor to the large capacitor, achieving a voltage increase on the large capacitor. This paper simulates and analyzes three analog counter Structures implemented by the above two methods, comparing their performance in terms of counting step consistency, area, swing, DNL (Differential Non-linearity), and INL (Integral Non-linearity). Based on the above analysis, an analog counter with high linearity and high swing is designed in 180nm standard CMOS process, with a resolution of 7 bits and a swing of 0.4V~3.3V. In the worst case, the DNL is 0.039LSB and the INL is 0.206LSB. Compared with a digital counter of the same resolution, the proposed analog counter significantly reduces the layout area occupied. Compared with previous designs, the proposed analog counter circuit with its advantages of small area and low power consumption, can be applied to infrared focal plane digital pixel circuit.

The mapping relationship between visible images and infrared images of different targets varies due to differences in their physical properties, such as surface emissivity, reflectivity, temperature, ambient radiation intensity, and heat dissipation effects. When using Generative Adversarial Networks for visible-to-infrared image translation, we focus not only on the overall quality of the image but also on the accuracy of target feature translation. In previous research, the authors used the AVIID-3 dataset to classify cars targets into four categories: light-colored moving cars A, dark-colored moving cars B, light-colored parked cars C, and dark-colored parked cars D. The scenes are divided into two categories: moving scenes with only moving car targets and parking lot scenes with only parked car targets. An optimal generation strategy for the AVIID-3 dataset based on Pix2pix and CycleGAN has been proposed. Although this research has made significant progress, some limitations still exist. In the AVIID-3 dataset, moving and parked car targets do not appear simultaneously in the same scene, making it impossible to evaluate different generation strategies in complex scenes. To address this issue, this study proposes a general visible-to-infrared image generation strategy for car targets. Additionally, data from complex scenes captured by drones were used to reconstruct the dataset. This approach validates that the proposed strategy is effective not only for simple scenes containing only one type of target but also for mixed scenes with random combinations of multiple targets, demonstrating its practical applicability in real engineering scenarios.

Currently, the digital infrared focal plane array (DIRFPA) detector is developing towards a large format and high frame rate, which puts high demands on the performance of the digital readout circuit (DROIC). In response to the high-speed data transmission and high conversion rate analog-to-digital converter (ADC) requirements in the digital readout circuit, this paper adopts the 180nm CMOS process to design an on-chip integrated high-speed clock generation circuit based on a charge pump phase-locked loop, providing a high-speed and low-jitter clock signal for the digital readout circuit to meet its data transmission and ADC conversion needs. The designed clock generation circuit mainly consists of a phase frequency detector (PFD), a charge pump (CP), a loop filter (LPF), a voltage-controlled oscillator (VCO), and a multimode divider (MDIV). The VCO includes three sets of differential ring oscillators in different frequency ranges, achieving a wide frequency tuning range with output frequencies ranging from 200MHz to 1.5GHz. Using a combination of multiple VCOs reduces the sensitivity of each VCO, which is beneficial for decreasing the jitter of the output signal. The area of the charge pump phase-locked loop clock generation circuit designed in this study is 0.13784mm². In simulation, when the output frequency is 1GHz, the lock time is 4μs, the phase noise is -95 dBc/Hz at a 1MHz offset, the RMS jitter is approximately 5.4ps within a frequency offset range of 1kHz to 100MHz, and the power consumption is 16.1mW.

Column-level ADC DROIC (Digital Readout Integrated Circuit) is widely used in large arrays, small pixels, high frame rates, and low-power digital IRFPA (Infrared Focal Plane Array). In this paper, a high-precision, low-power, highspeed single-slope ADC that can be used for column-level ADC DROIC is proposed. The ADC uses a 13-bit hybrid counter with a 5-bit shared Gray code counter and an 8-bit binary counter, powered by three voltage domains. This design maintains low power consumption while balancing precision and speed. The ADC is designed in a 180nm CMOS process. The layout of the proposed ADC can be implemented in a pixel pitch less than 10μm. The simulation results show that the Differential Nonlinearity (DNL) of the ADC proposed in this paper is -0.7/0.71 LSB, the Integral Nonlinearity (INL) is -0.36/5.7LSB, the Signal to Noise and Distortion Ratio (SNDR) is 75.09 dB, the ENOB is 12.18 bits, and the power consumption at a sampling rate of 100K/s is approximately 36 µW. These results indicate the ADC is suitable for large arrays, small pixels, and low-power IRFPA DROICs.

Infrared imaging technology has garnered widespread attention due to its advantages in long-distance detection, multispectral imaging, stealth capability, and imaging in low-light environments. In this study, real-world images captured by two thermal imagers operating in the infrared bands of 3-5μm and 8-14μm were investigated to explore the infrared radiation transmission characteristics of target backgrounds and calculate their radiation contrast. The characteristics of radiation contrast between target and background in different wavelength bands were analyzed, along with the resulting image features. Specific details of the images in different wavelength bands were elucidated using histogram analysis, mean, standard deviation, and information entropy. Ultimately, a dual-band infrared image fusion algorithm was proposed based on Planck's law. Experimental results confirm that this algorithm significantly enhances image details, improves target clarity and recognizability, comprehensively presents target features, enhances target detection efficiency, and exhibits clear targeting in the fusion process.