A photoacoustic spectroscopy (PAS) based carbon dioxide (CO₂) sensor with a fixed wavelength quantum cascade laser (FW-QCL) was demonstrated. The emission wavelength of the FW-QCL at 4.42 μm in the mid-infrared spectral region matched a fundamental CO₂ absorption line. Amplitude modulation of the laser intensity was used to match the resonant photoacoustic (PA) cell. The noise from the background was reduced with the correlation demodulation technique. The experimental results showed that the sensor had excellent signal stability and a concentration linear response. When the integration time was 1 s, a 1σ minimum detection limit (MDL) of 2.84 parts per million (ppm) for CO₂ detection was achieved. The long-term stability of the sensor was evaluated by means of an Allan deviation analysis. With an integration time of ~100 s, the MDL was improved to 1 ppm. This sensor was also used to measure the CO₂ concentration from some common emission sources, such as cigarette smoking, automobile exhaust, and the combustion of some carbon-containing materials, which confirmed the stability and robustness of the reported FW-QCL based CO₂-PAS sensor system.

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.

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.

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.

A Si-prism-array coupled terahertz (THz)-wave parametric oscillator with the pump totally reflected at the THz-wave exit surface (PR-Si-TPO) is demonstrated by manufacturing an 800 nm air gap between the crystal and the Si-prism array. Influence on the total reflection of the pump from the Si prisms is eliminated and efficient coupling of the THz wave is ensured by using this air gap. When the THz-wave frequency varies from 1.8 to 2.3 THz, compared with a Si-prism-array coupled TPO (Si-TPO) with the pump transmitting through the crystal directly, the THz-wave output energy is enhanced by 20–50 times, and the oscillating threshold is reduced by 10%–35%. Furthermore, the high end of the THz-wave frequency tuning range of the PR-Si-TPO is expanded to 3.66 THz compared with 2.5 THz for the Si-TPO.