This PDF file contains the front matter associated with SPIE Proceedings Volume 13255, including the Title Page, Copyright information, Table of Contents, and Conference Committee information.

To enhance the accuracy of surgical instrument pose estimation within the surgical navigation system, a near-infrared surgical instrument pose estimation system based on binocular stereoscopic vision was devised. Initially, near-infrared markers were affixed to the surgical instruments, and their positions were captured using binocular cameras. Leveraging the transformation between pixel and world coordinates, along with stereoscopic vision principles, the spatial positions of the markers were determined. Subsequently, these marker positions were utilized to establish the instrument coordinate system, aligned with the camera coordinate system. Finally, employing the motion model of the instrument in space and utilizing the least squares algorithm with the minimum mean square error criterion, the instrument calibration process was optimized. The Extended Kalman Filter (EKF) was then deployed to refine the dynamic pose estimation of the instrument. The experimental outcomes illustrated that the stability and precision of the instrument pose estimation met the demands of surgical navigation, with a root mean square error (RMSE) of 0.23 mm for dynamic tip position estimation and a maximum error of 2 degrees in the estimation of the instrument's orientation. This approach enables automatic, accurate, and stable estimation of surgical instrument poses.

The combustion of different substances has different spectral and smoke characteristics. Decalin in the international standard ISO7240-15 has low-temperature black smoke combustion characteristics, while wood open fire can simulate the combustion characteristic of a large number of wood stacking site. These two types of test fires are not covered in Chinese standards. This article establishes a flame infrared radiation measurement system, which tests decalin and wood open flames respectively, and qualitatively evaluates its performance evaluation effect on point-type flame detectors; Conduct smoke characteristic tests on decalin and wood open fire, testing point-type smoke detectors and point-type fire detectors using smoke and heat sensors based on these two test fires. The results indicate that the two standard test fires in ISO have good evaluation effects on detectors of different types and applications. The open wood fire can simulate the development process of wood combustion, while decalin simulates low-temperature and dense smoke combustion.

Photodetectors, widely employed in optical communication, automatic control, and consumer electronic devices, are a type of optical component. The performance requirements of photodetectors vary depending on their applications. To enhance these devices, certain parameters such as the thickness of different layers and doping levels in each layer are necessary. However, this information is often not provided by manufacturers' datasheets. In this project, a reverse engineering approach was utilized to investigate the relationship between device design and performance by analyzing three different commercial devices through measurement techniques including I/V characteristics, C/V measurements, and spectral response-wavelength analysis. These measurement results were used to extract structural information about the devices. Through this process, it was concluded that depletion region thickness plays a crucial role in dark currents; smaller depletion regions result in lower dark currents. Additionally, potential issues influencing measurement outcomes were also addressed.

UAV thermal infrared remote sensing imagery allows for higher resolution LST (land surface temperature) to be acquired, but temperature drift during thermal camera data acquisition reduces the reliability of the data. Data with temperature drift cannot be accurately removed by the camera’s own automatic calibration or by using a fixed calibration function. In addition, during the acquisition of data by a thermal imaging camera at low altitude, the transmission of thermal radiation is affected by the atmosphere at mid-flight altitude, and the data need to be atmospherically corrected to characterize the actual LST. In this paper, the errors caused by temperature drift are removed by feature matching and linear fitting in the data processing process, so as to obtain more accurate mosaics of brightness temperatures. In the retrieval process, the LST is obtained by synchronizing the atmospheric wet temperature contour lines, based on the principle of thermal radiation transmission, and combining with the specific emissivity of the ground to obtain the high accuracy of the LST. The feasibility of the algorithm is verified using continuous actual measured LST. The results show that based on the synchronized atmospheric temperature and humidity contours, the atmospheric influence can be effectively eliminated, and the LST obtained by the retrieval has a high accuracy. From the experimental results, it can be seen that the method proposed and analyzed in this paper is a feasible method to obtain high-precision LST using thermal infrared remote sensing images from UAVs.

Multi-camera is widely used in systems such as optoelectronic pods and security cameras; However, the optical axis deviation problem in multi-camera systems has a great impact on the measurement precision and accuracy of the system. When calibrating a multi-optical axis system, conventional methods usually take a long time and have limited accuracy. In order to solve the problem of accuracy and speed of multi-optical axis line-of-sight deviation measurement, this paper proposes a fast measurement method for multi-optical axis line-of-sight deviation. The gray matrix inter-correlation algorithm is utilized for rapid and precise calibration of the optical axes across multiple cameras. A reference point on the optical axis of one camera is selected as a benchmark, and a small template is extracted from its vicinity to be matched with images from other cameras. This process allows for the determination of differences between the reference point and the optical axes in other cameras, enabling measurement of their line-of-sight deviations. In this study, experiments were conducted using Electro-Optical Targeting System and inserted-axis detector to illustrate this process with two optical axes. At the same time, it solves the problem that the inserted-axis detector camera is not parallel to the axis, and ensures the consistency of the optical axis and the inserted axis. The experimental results show that this paper's method has a high accuracy.

This paper proposes a compact dual-band substrate integrated waveguide (SIW) bandpass filter based on a multi-mode SIW cavity, four modes TE₁₀₁, TE₁₀₂, TE₂₀₁ and TE₂₀₂ are excited in a single resonator to construct two passbands. The resonance frequencies of the four independent resonant modes can be controlled by loading metalized vias to enhance the electric field intensity of the proposed cavity, altering the direction of surface current by etching gaps. And the bandwidth allocation can be achieved by changing the spacing between two closely distributed modes. A fourth-order bandpass filter centered at 7.44 GHz and 9.64 GHz is realized, with two transmission zeros at 7.9 GHz and 10.54 GHz, respectively. The BPF have been designed, fabricated, and measured, with the good agreement between the simulations and the measured ones. This demonstrates the technique's flexibility in designing multi-bandpass filters with controllable transmission zeros.

Due to the influence of the applied magnetic field, the ionosphere is an anisotropic medium, which makes its reflection characteristics of the radio waves incident from the ground towards the ionosphere more complicated. The impedance matrix method is proposed to analyze the reflection characteristics of very low frequency radio waves in the anisotropic stratified ionosphere in this paper. Based on Maxwell equation, the reflection characteristics of VLF waves in anisotropic homogeneous media are analyzed, and compared with the results of traditional analytical methods, the correctness and simplicity of the application of impedance matrix method in VLF frequency band are clarified, which provides a certain reference for the study of the propagation characteristics of VLF waves.

SRAM based large capacity programmable FPGA is widely used in electronic systems, undertaking increasingly complex control and information processing tasks. The routine operation of updating FPGA software requires connecting through the JTAG interface, using matching download cables and software development tools to complete the program update. This method has significant limitations, as it cannot achieve multi FPGA multi version startup and online remote update functions, resulting in low software upgrade efficiency and high software upgrade costs. This article introduces a remote online update method for FPGA. The updated program is transmitted to the FPGA through the CAN bus, and the FPGA configures Flash through the SPI protocol to write the program into Flash. After power on again or through instructions, the FPGA loads the updated program, achieving online startup and remote online updates of multiple FPGA versions. After practical testing, this solution has overcome the difficulties of multi FPGA multi version startup and online remote updates. The design operation process is simple and practical, greatly improving the efficiency of multi FPGA multi version startup and online remote updates.

The use of Unmanned Aerial vehicles (UAVs) in both military and civilian contexts raises a series of safety issues. Traditional anti-UAV detection methods may cause false and missed detections when faced with complex backgrounds and large changes in target scale. To solve the above problems, a lightweight anti-UAV detection algorithm based on yolov7-tiny was proposed. Firstly, the YOLOv7-Tiny backbone network is substituted with an enhanced ShuffleNetV2 network, augmenting the network's feature extraction capacity to acquire richer semantic information while maintaining a lightweight model. Secondly, we propose a cross-scale fusion feature strategy inspired by the feature pyramid concept to enhance the model's detection capabilities across various target scales. Thirdly, the ELAN-DS module is introduced to reduce computations and parameters while maintaining detection effectiveness. Finally, the loss function is replaced with Focal-EIoU to improve detection accuracy for small targets. The improved algorithm is trained and evaluated on the UAV dataset. The mAP@0.5 increases by 1.1%, the Parameters is reduced by 21.67%, the Floating Point Operations (FLOPs) is reduced by 33.33%, the model size is 10.4MB, and the frame rate reaches 48 frames per second, all in comparison to the YOLOv7-Tiny algorithm. The improved algorithm possesses a smaller model size and enhanced detection capability. Methods are provided for deployment on anti-UAV mobile devices or embedded systems.

The single event effect of 650 V silicon carbide diode induced by Californium source was studied. The leakage current of silicon carbide diodes irradiated under 300 V and 350 V bias voltages increased continuously, and when the cumulative irradiation fluence reaching 3 × 10⁴ n·cm^-2, the reverse leakage current of silicon carbide diodes under the two bias voltages differed by two orders of magnitude. Under the bias voltages of 370 V and 400 V, silicon carbide diodes suffered single event burnout, and the cumulative irradiation fluence that occurred single event burnout was related to the bias voltage of silicon carbide diode. The electrical characteristics test results show that the breakdown voltage of silicon carbide diodes with continuous increase of leakage current is degraded to varying degrees, and it still retains part of the breakdown characteristics, while the device with single event burnout completely loses the breakdown characteristics. The micro damage analysis results show that the single event burnout leads to the destruction of the anode contact of silicon carbide diode, which affects the turn-on and breakdown characteristics.

In scattering imaging, a light beam carrying target information will form a speckle image after passing through a scattering medium. In order to recover the original target image from the speckle image, this paper designs an optical imaging scheme of a light beam passing through a random scattering medium, based on the optical memory effect and speckle autocorrelation technology. This paper proposes a novel reconstruction algorithm based on multi-range coherent diffraction imaging, named parallel Amplitude-Phase Retrieval (APR) algorithm. The simulation is carried out under the condition of static scattering medium. The performance of the reconstructed images of different restoration algorithms is compared by the Peak Signal to Noise Rate (PSNR). Through the analysis of the simulation results, for the reconstruction of simple images, the PSNR of APR algorithm is 35.9 dB, which is 6.6 dB, 7 dB and 6.5 dB higher than that of ER algorithm, HIO algorithm and ER-HIO algorithm respectively. For complex image reconstruction, the PSNR of APR algorithm is 26.3 dB, which is 8 dB, 7.2 dB and 6.5 dB higher than that of ER algorithm, HIO algorithm and ERHIO algorithm respectively. The results show that APR algorithm is better than other algorithms for image reconstruction.

Based on the experience of practical ultraviolet spectrum measurement in outfield, this paper analyzes the main factors that make ultraviolet spectroscopy data invalid or worse data quality, such as great continuous impact, uncontrollable environment, shaking ground. The main principles to deal with these factors are proposed, such as human protection and power supply in outfield measurement.

Optogenetics technology has greatly promoted the development of neuroscience. Flexible gene manipulation tools and sensitive light activation methods have provided convenience for neural function research. However, the thermal effect generated in the process of light stimulation affects the activation of neurons by optogenetic technology, which makes the results of light-activated light-sensitive proteins to generate neural currents inaccurate. Here, we established an in vivo activation model of LED-based optogenetic technology through simulation and analyzed the thermal effect produced by it. We propose to use microchannels to dissipate heat from implanted devices, reducing the thermal effect of light stimulation for neural activation. Through simulation, we propose the use of the vortex-like and cobweb-like microchannels for heat dissipation, which can control the temperature rise within 0.28K and 0.31K, respectively.

In response to the urgent need for high-precision long baseline measurement in tasks such as precision assembly measurement of large space institutions and precise formation flight, a dual-comb femtosecond laser ranging engineering prototype was built to verify the engineering environmental adaptability of this technology. The absolute distance measurement technology based on nonlinear optical down-sampling principle is adopted, which widens the echo signal width from femtosecond level to nanosecond level, effectively avoided the problem of insufficient response rate of photo-detectors, overcomes the disadvantage of low precision of traditional pulse ranging, and achieves high-precision absolute distance measurement of long baseline targets. The optical and mechanical structure of femtosecond laser ranging prototype is designed for environmental adaptability. We conducted distance measurement experiments on the relative positions of multiple positioning points on a clean interval vibration platform and a 52m long baseline target distance measurement experiment on a conventional laboratory testing platform for the product. The results show that under both operating conditions, the product's ranging accuracy reaches the level of 10um, the system operates stably and can quickly and continuously measure dynamic micro displacement. At this precision level, the impact of laboratory air disturbance and environmental vibration on this product can be ignored, which provides important reference value for the subsequent engineering application of the product.

The electric power fusion network represents a wireless core backbone specialized network that utilizes 5th generation (5G) short slicing and 4th generation (4G) short multiplexing technologies. It aims to meet the high bandwidth, low latency, and broad connection requirements of smart grids while simultaneously leveraging the extensive coverage of existing 4G networks to ensure the secure, controllable, and economical carriage of electricity services. However, due to the heterogeneous nature of the 4G/5G integrated electric power network, current methods face challenges in the user access short slicing process, characterized by low resource utilization rates and high user resource leasing costs. This issue complicates efficient end-to-end resource allocation within the electric power fusion network. To address this problem, this paper introduces an end-to-end slicing wireless resource allocation strategy based on the Sine Cosine Algorithm (SCA). This strategy comprehensively considers communication delay and resource leasing costs, establishing a cost function model to conduct a holistic assessment of resource allocation. By employing the SCA algorithm for optimization, the proposed strategy leverages its advantages such as fewer parameters, simple structure, easy implementation, and fast convergence speed to identify the optimal resource allocation scheme when the cost function is minimized. Simulation results demonstrate that, compared to methods with fixed costs, the proposed strategy exhibits lower access latency and rental costs.

Aiming at the problem of edge extraction for reconstruction results of high energy flash X-ray images, an edge detection algorithm for each density layer of layer based on adaptive anisotropy factor and multi-scale fusion is proposed. The anisotropy factor, which is associated with numbers of anisotropic filters, is derived based on the ratio of signal-to-noise ratio of the edge strength to the resolution constant. The adaptive anisotropy factor can reduce anisotropic stretch phenomenon and spurious edge response. Edge intensity maps between adjacent scales are fused by scale multiplication to reduce the conflict between high edge resolution and robust to noise so as to enhance edge structure. The edge strength maps obtained under the first-order derivative of anisotropic and isotropic Gaussian kernels are further fused by geometric averaging mechanism. Finally, the false edge suppression of non-maximum and double threshold is carried out to obtain the edge with single-pixel of the target. Experimental results show that the algorithm can effectively suppress the influence of noise and reduce the fuzzy effect on edge, and can obtain more accurate edge detection results.

The motivation for this research stems from the critical need within the tobacco industry to enhance the quality control and efficiency of flue-cured tobacco production. The inadvertent inclusion of non-tobacco related materials (NTRM) during the production process has been a persistent challenge, significantly affecting the final product's quality. Existing detection methods have proven insufficient in addressing this issue comprehensively. To address this gap, we embarked on the development of a dedicated NTRM detection method tailored to the specific requirements of the tobacco industry. We first established an extensive NTRM spectral database through the utilization of multispectral and visible light imaging techniques. Subsequently, we propose an enhanced YOLO model, called YoRMD-Net, which enables swift and precise NTRM segmentation. Our method achieves a 97.5% mAP in identifying NTRM and offers real-time tracking at 16.5 ms per frame, significantly outperforming traditional manual detection in actual production. By doing so, we aim to provide an effective solution that not only improves product quality but also streamlines production processes, ultimately benefiting the entire tobacco industry by ensuring the production of premium-grade flue-cured tobacco products.

Addressing signal attenuation and multipath interference challenges in underground mine communications, an innovative Impulse Radio Ultra-Wideband (IR-UWB) communication system is introduced in this paper. Four narrow pulse signals with distinct pulse positions are employed by this system to facilitate multiple access and secure transmission. Furthermore, a sampling integration circuit based on equivalent time sampling is utilized for parallel reception, to enhance signal reception performance and communication rate in low signal-to-noise ratio (SNR) environments. The simulation results show that the system maintains a bit error rate of no more than 10^-1 under SNR conditions ranging from -20dB to 5 dB. Furthermore, its transmission rate is improved by several times compared to traditional single-channel transceiver systems. This provides a low complexity and effective solution for underground mine communications.

The omnidirectional receiving system is suitable for underwater wireless optical communications (UWOCs), and it has less dependence on the structure of the underwater platform as it is connected by only one cable. The optical receiving module is a spherical structure, small size, and generates less heat. There is a square structure in the center of the spherical structure, and the spherical structure consists of six converging lenses in close contact with each other. And there is a photo-detector (PD, APD or PMT etc.) at the focus of each converging lens. Thus, with this structure, the underwater platform can realize the demand of omnidirectional reception without aligning at the sending end. By using high-sensitivity detectors in the receiving system, longer distance underwater communication and cross-media data transmission can be achieved.

Guided wave radar level gauges are known for their high measurement accuracy, low maintenance costs, and high reliability, making them suitable for challenging conditions such as high temperature and pressure. In order to use guided wave radar for measuring oil, water, and gas interfaces, the transmitted signal employs high-frequency pulse signals with extremely narrow pulse width. By combining the similar equivalent sampling method and using a pair of positive and negative symmetric sampling pulses to control the sampling gate switch, the high-frequency radar signal is extended into a low-frequency signal that can be collected by a microcontroller. The four-diode bridge sampling circuit utilizes HSMS- 285P, resulting in a significant reduction in the output signal noise of the circuit. Simulation results indicate that this circuit is applicable for a double-interface measurement system.

This paper presented three types of 3dB directional couplers designed for millimeter wave radar with a center frequency of 79GHz and operating frequency range of 77 GHz⁓81 GHz. The characteristic impedance of microstrip line for these three directional couplers was obtained using the odd-even mode analysis method, and their design parameters were calculated accordingly. Models of the directional couplers were established and simulated using HFSS simulation software for analysis. The simulation model diagrams were optimized, and the final simulation results were obtained. The final results showed that all three types of 3dB directional couplers had good isolation performance. A comparison of the coupling effects of the three directional coupler was provided, showing that the microstrip hybrid ring directional coupler offered better coupling effects and was more conducive to fabrication.

LiDAR is a radar system that detects the position, speed and other characteristic quantities of a target by emitting a laser beam, which is mainly used in the field of unmanned driving. The realization of laser navigation technology in AGV (Automated Guided Vehicle) is mainly to locate and navigate by LiDAR, obtain the three-dimensional information of the surrounding environment in real time, and provide reliable navigation and obstacle avoidance function for AGV. In this paper, on the basis of analyzing the principle of laser navigation AGV, we propose a simultaneous localization and mapping method (Simultaneous Localization and Mapping, SLAM) based on LiDAR to obtain the motion information in the robot's surroundings through LiDAR, and then construct the map through Fast-SLAM algorithm. An improved Artificial Potential Field (APF) method is designed to quantify the convergence of the motion planning path, and based on the convergence, the adjustment factors of artificial gravitational field and artificial repulsive field are constructed, and the artificial gravitational field and artificial repulsive field are combined to obtain the artificial joint force field of the robot, so as to solve the problems of localization and unreachable target endpoints in the existing technology. In order to solve the problems of local optimization and unreachable target endpoint in the existing technology. The experimental results show that the optimal trajectory path is established by the artificial force field, and the trajectory navigation from the starting point to the target point is completed, the adaptability of AGV robot localization and the accuracy of map construction are improved.

A millimeter-wave 24-way waveguide dividing and combining integrative network is designed in this paper. The dividing network part is the 24-way divider, and the combining network part is the 24-way combiner. The insertion loss of the back to back of the 24-way waveguide dividing and combining integrative network is about 2dB in the whole band, which implies that the average insertion loss of the combiner in the network is about1dB, and can allow for the overall power-combining efficiency to remain high, 80% over X.5-Y.5GHz.