Yanchen Qu

Optically pumped gas terahertz (THz) lasers (OPGTLs) as reliable sources of THz radiation have been extensively utilized within THz application areas. In this paper, a substrate-free metal mesh coupler based on the metasurfaces principle was designed for continuous wave OPGTL, which is suitable for the Fabry–Perot (FP) THz resonator. The parameters of substrate-free metal mesh are calculated by the Ulrich equivalent circuit model, and the influence of metal mesh period and linewidth on its transmittance is analyzed quantitatively. Taking the THz laser with the 118.8 µm of CH₃OH optically pumped by the 9.6 µm CO₂ laser line for instance, two kinds of metal mesh were devised as input and output couplers of the resonator, and the transmittance and reflectance of the metal meshes are verified by the finite-difference time-domain (FDTD) method. Furthermore, the transmitted and reflected light fields of the FP resonant cavity metal mesh mirrors were simulated by using the FDTD method under the vertical incidence of both pump light and THz waves. Validation of the optical field characteristics of the substrate-free metal meshes confirmed their suitability as ideal input and output coupling cavity mirrors for FP resonant cavities in optically pumped gas THz lasers.

The tunable CO₂ laser is a common pump source for optically pumped terahertz lasers. In this paper, based on a sealed-off CO₂ laser tube and a grating-tuned cavity, we reported an efficient, high-power, low-cost, simple structure and tunable continuous-wave CO₂ laser. A sealed-off CO₂ laser tube was designed and customized, and its plasma discharge characteristics were experimentally analyzed. The influence of output coupler transmittance and discharge current on the laser’s tunability and output power was systematically studied using grating tuning. A total of 78 spectral lines were achieved within the wavelength range of 9.17–10.86 μm. The maximum output power of 55.5 W was recorded on the 10P20 line when the output coupler transmittance was approximately 22%. The laser exhibited a beam spot radius of about 3.8 mm and a beam quality factor (M²) of 1.74.

The Geiger-Mode Avalanche Photodiode (Gm-APD) LiDAR system demonstrates high-precision detection capabilities over long distances. However, the detection of occluded small objects at long distances poses significant challenges, limiting its practical application. To address this issue, we propose a multi-scale spatio-temporal object detection network (MSTOD-Net), designed to associate object information across different spatio-temporal scales for the effective detection of occluded small objects. Specifically, in the encoding stage, a dual-channel feature fusion framework is employed to process range and intensity images from consecutive time frames, facilitating the detection of occluded objects. Considering the significant differences between range and intensity images, a multi-scale context-aware (MSCA) module and a feature fusion (FF) module are incorporated to enable efficient cross-scale feature interaction and enhance small object detection. Additionally, an edge perception (EDGP) module is integrated into the network’s shallow layers to refine the edge details and enhance the information in unoccluded regions. In the decoding stage, feature maps from the encoder are upsampled and combined with multi-level fused features, and four prediction heads are employed to decode the object categories, confidence, widths and heights, and displacement offsets. The experimental results demonstrate that the MSTOD-Net achieves mAP₅₀ and mAR₅₀ scores of 96.4% and 96.9%, respectively, outperforming the state-of-the-art methods.

In order to solve the problem of detecting, tracking and estimating the size of “low, slow and small” targets (such as UAVs) in the air, this paper designs a single-photon LiDAR imaging system based on Geiger-mode Avalanche Photodiode (Gm-APD). It improves the Mean-Shift algorithm and proposes an automatic tracking method that combines the weighted centroid method to realize target extraction, and the principal component analysis (PCA) method of the adaptive rotating rectangle is realized to fit the flight attitude of the target. This method uses the target intensity and distance information provided by Gm-APD LiDAR. It addresses the problem of automatic calibration and size estimation under multiple flight attitudes. The experimental results show that the improved algorithm can automatically track the targets in different flight attitudes in real time and accurately calculate their sizes. The improved algorithm is stable in the 1250-frame tracking experiment of DJI Elf 4 UAV with a flying speed of 5 m/s and a flying distance of 100 m. Among them, the fitting error of the target is always less than 2 pixels, while the size calculation error of the target is less than 2.5 cm. This shows the remarkable advantages of Gm-APD LiDAR in detecting “low, slow and small” targets. It is of practical significance to comprehensively improve the ability of UAV detection and C-UAS systems. However, the application of this technology in complex backgrounds, especially in occlusion or multi-target tracking, still faces certain challenges. In order to realize long-distance detection, further optimizing the field of view of the Gm-APD single-photon LiDAR is still a future research direction.

With the wide application of UAVs in modern intelligent warfare as well as in civil fields, the demand for C-UAS technology is increasingly urgent. Traditional detection methods have many limitations in dealing with “low, slow, and small” targets. This paper presents a pure laser automatic tracking system based on Geiger-mode avalanche photodiode (Gm-APD). Combining the target motion state prediction of the Kalman filter and the adaptive target tracking of Camshift, a Cam–Kalm algorithm is proposed to achieve high-precision and stable tracking of moving targets. The proposed system also introduces two-dimensional Gaussian fitting and edge detection algorithms to automatically determine the target’s center position and the tracking rectangular box, thereby improving the automation of target tracking. Experimental results show that the system designed in this paper can effectively track UAVs in a 70 m laboratory environment and a 3.07 km to 3.32 km long-distance scene while achieving low center positioning error and MSE. This technology provides a new solution for real-time tracking and ranging of long-distance UAVs, shows the potential of pure laser approaches in long-distancelow, slow, and small target tracking, and provides essential technical support for C-UAS technology.

With the wide application of UAVs in modern intelligent warfare and civil fields, the demand for C-UAS technology is increasingly urgent. Traditional detection methods have many limitations in dealing with "low, slow, and small" targets. This paper presents a pure laser automatic tracking system based on Geiger mode avalanche photodiode (Gm-APD). Combining the target motion state prediction of the Kalman filter and the adaptive target tracking of Camshift, a Cam-Kalm algorithm is proposed to achieve high-precision and stable tracking of moving targets. The system also introduces two-dimensional Gaussian fitting and edge detection algorithms to automatically determine the target's center position and the tracking rectangular box, improving the automation of target tracking. The experimental results show that the system designed in this paper can effectively track UAVs in a 70 m laboratory environment and 3.07 km to 3.32 km long-distance scene and has low center positioning error and MSE. This technology provides a new solution for real-time tracking and ranging of long-distance UAVs, shows the potential of pure laser in long-distance "low-slow-small" target tracking, and provides essential technical support for C-UAS technology.

A novel scheme for improving the resolution of temperature sensor using fast and slow light in a fiber resonator is proposed and demonstrated experimentally. In the measurement system, the shift of resonance wavelength produced by the temperature change can be converted into strong variations of delay time. By measuring the delay time, this sensor we proposed has high temperature sensitivity. Different from the traditional method of tracing spectrum, the temperature detection is carried out using an oscilloscope, which results in the sensor with fast response and high resolution. Moreover, the sensitivity, resolution and measurement range of the sensor can be easily tuned by changing the Q-factor of the resonator. Using this approach we demonstrate temperature measurements at fiber resonators with low-Q and high-Q, respectively, as well as a 3.76×10 ^-4 °C resolution and a 2706 ns/°C sensitivity of temperature sensing are obtained. The scheme is simple in structure and easy to implement, which is particularly suitable for detecting very small temperature changes.

Long-distance multi-vehicle detection at night is critical in military operations. Due to insufficient light at night, the visual features of vehicles are difficult to distinguish, and many missed detections occur. This paper proposes a two-level detection method for long-distance nighttime multi-vehicles based on Gm-APD lidar intensity images and point cloud data. The method is divided into two levels. The first level is 2D detection, which enhances the local contrast of the intensity image and improves the brightness of weak and small objects. With the confidence threshold set, the detection result greater than the threshold is reserved as a reliable object, and the detection result less than the threshold is a suspicious object. In the second level of 3D recognition, the suspicious object area from the first level is converted into the corresponding point cloud classification judgment, and the object detection score is obtained through comprehensive judgment. Finally, the object results of the two-level recognition are merged into the final detection result. Experimental results show that the method achieves a detection accuracy of 96.38% and can effectively improve the detection accuracy of multiple vehicles at night, which is better than the current state-of-the-art detection methods.

A highly sensitive hybrid structure sensor based on suspended-core fiber (SCF) is proposed for vector curvature and temperature measurement. The sensor is prepared by self-assembly of SCF-based cascaded Fabry-Perot interferometer (cFPI), single-mode fiber (SMF), and fiber Bragg grating (FBG). In view of the asymmetry of the cFPI, theoretical analysis of the beam transmission and spectral characteristics is implemented when the beam is incident from different directions. The two sensing fibers in the triangular distribution sensor will not be located on the neutral plane at the same time, which makes it possible to measure bending in any orientation. The Vernier effect formed by the cFPI enlarges the curvature and temperature sensitivity to −1064.5 pm/m ⁻¹ and 50.7 pm/°C, respectively, without affecting the measurement range. The spectrum shows the opposite spectral response when the sensor bending direction difference is 180°. The sensor overcomes the bottleneck of bending sensitive blind spots in dual-fiber sensing. In addition, the sensor maintains a smaller size and more flexible preparation, which is conducive to its application in artificial intelligence, medical detection.