For decades, optical fiber interferometers have been extensively studied and applied for their inherent advantages. With the rapid development of science and technology, fiber sensors with higher detection sensitivity are needed on many occasions. As an effective way to improve measurement sensitivity, Vernier effect fiber sensors have drawn great attention during the last decade. Similar to the Vernier caliper, the optical Vernier effect uses one interferometer as a fixed part of the Vernier scale and the other as a sliding part of the Vernier scale. This paper first illustrates the principle of the optical Vernier effect, then different configurations used to produce the Vernier effect are classified and discussed. Finally, the outlook for Vernier effect fiber sensors is presented.

A temperature and refractive index simultaneous measurement sensor based on an optical microfiber coupler (OMC) combined with a polarization maintaining fiber (PMF) is proposed and experimentally demonstrated. The OMC-PMF sensor is fabricated by inserting a section of PMF between two output ports of the OMC. The interference spectrum of the OMC-PMF sensor has different responses to temperature and refractive index variations. Temperature and the refractive index can be measured by monitoring the dip intensity variation and the dip wavelength shift of the interference spectrum, respectively. The experimental results show that the refractive index sensitivity is 12 020 nm/RIU, and the temperature sensitivity is 0.88 dB/°C upon increasing temperature from 35 °C to 41 °C.

In this study, an Infrared Small-Target Detection Transformer (IST-DETR) is introduced, a novel model specifically designed to tackle the challenges of low-resolution infrared images and small target scales. IST-DETR integrates a backbone network, a hybrid encoder featuring, a Mutual Feature Screening (MFS) module, and a decoder with auxiliary prediction heads. The hybrid encoder employs Learning Position Encoding to reduce information redundancy and employs a mutual feature screening mechanism to enhance the interaction between high-level semantic features and low-level positional features, facilitating more accurate detection of small infrared targets. What’s more, a customized IoU metric and a novel sample weighting function are employed to effectively address dataset imbalance, significantly improving detection performance. Experiments conducted on the FLIR Dataset, HIT-UAV Dataset, and IVFlying Dataset yielded an average precision (AP) of 44.1%, 34.0%, and 58.5%, respectively, with a processing speed of 74 frames per second. IST-DETR outperforms contemporary algorithms such as Yolov8, CO-DETR, and DINO, demonstrating a superior balance of speed and accuracy, particularly in recognizing small infrared targets across diverse and complex scenarios.

Ultrawideband (UWB) technology has garnered significant attention due to its extensive applications in indoor positioning. However, its performance is susceptible to interference from environmental factors. In response to the positioning accuracy issues in time difference of arrival (TDOA) scenarios, this article proposes an integrated TDOA-UKF-FNN-Chan-RIC algorithm that incorporates the unscented Kalman filter (UKF), feedforward neural networks (FNNs), Chan’s algorithm, and redundant information correction (RIC) to effectively enhance the positioning accuracy and robustness of UWB systems. Initially, by investigating the redundant information within the UWB solution model in TDOA scenarios, the inter-relationship between redundant information and measurement vectors is revealed. Subsequently, a gradient descent error correction algorithm for redundant information suitable for TDOA scenarios is proposed, and UKF and FNN transformations are combined to ensure that the data meet the preconditions for algorithmic application. To address the stability issues of positioning algorithms based on implicit function solutions in TDOA scenarios, Chan’s algorithm is employed to convert range difference measurements into range measurements, thereby enhancing computational robustness. Ultimately, the TDOA-UKF-FNN-Chan-RIC algorithm is proposed, and its effectiveness is validated through simulation and practical experiments. The experimental results demonstrate that this algorithm significantly improves positioning accuracy and robustness, achieving millimeter-level fixed-point accuracy and centimeter-level track accuracy in practical experiments.

Using optical fiber devices at the terminal is an important means to improve the performance of free space optical communication systems. We proposed a Fraunhofer diffraction integral based method to calculate the coupling efficiency between spatial light and few-mode fiber, and studied the influences of alignment tolerance on coupling efficiency. Numerical simulations confirm that the results obtained by this new method are consistent with the traditional calculation method. What is more, a few-mode fiber has flatter response characteristics to F-number mismatch, fiber lateral offset and defocus. Compared with single mode fiber, few-mode fibers can not only improve the maximum coupling efficiency, but also their coupling efficiency is much less sensitive to deviations from ideal conditions, thereby making them a more practical option for real world applications.