Guest editors Paul McManamon, Umar Piracha, Steve Jameson, Jeremy Bos, and Robert Stead introduce the Special Section on Autonomous Vehicles.

Autonomous vehicles rely on perceiving the road environment through a perception pipeline fed by a variety of sensor modalities, including camera, lidar, radar, infrared, gated camera, and ultrasonic. The vehicle computer must perform sensor fusion reliably in various sensor signals degrading environments, which can be performed parametrically or using machine learning. We study sensor fusion of a forward-facing camera and a lidar sensor using convolutional neural networks (CNNs), for drivable area detection in winter driving, where the roads are partially covered with snow, tire tracks obscuring lane markers. Seven fusion models are developed and evaluated for their ability to classify pixels into two classes: drivable and nondrivable. A total of seven models are designed and tested, including camera only, lidar only, early fusion, (three types of) intermediate fusion, and late fusion. The models have accuracies between 84% and 89%, with runtimes between 23 and 61 ms. To select the best model from this group, we introduce a unique metric, named normalized accuracy runtime (NAR) score. A network in a group has a higher NAR score, the more accurate it is, and the shorter its runtime is. The models are evaluated on a winter driving DENSE dataset. Camera and lidar fog noise are synthesized to examine model robustness.

Obstacle detection (OD) for autonomous ground vehicles on highways and in dynamic environments is exceptionally difficult due to the short response time requirements. Many OD systems handle this problem by using sensors with less data or by using powerful processors. However, this problem can be solved using biology-inspired processing without replacing hardware. LiDAR is one of the most common sensor options for OD in autonomous ground vehicles. The importance map, a recently developed biology-inspired processing technique using events, has been able to efficiently highlight LiDAR returns in a scene that correspond to obstacles. Even though the importance map has shown potential, there are three significant flaws: no object movement distinction, high levels of noise, and poor static object tracking. Solutions for these flaws are presented in this research. The constant-angle principle identifies motion toward the ego vehicle, temporal filtering removes noise, and an updated static object-tracking algorithm performs well at various speeds. OD capabilities of the importance map and the previous importance map are compared using LiDAR data from the KITTI data set. Using comparisons between true-positive and false-positive rates, the importance map performs much better than the previous importance map. Furthermore, events are shown to be a highly discriminative feature for finding obstacles in a scene.

Advanced light detecting and ranging (LIDAR) sensors are the primary sensing modality for autonomous vehicles and are seeing increasing adoption in consumer and commercial vehicles for robust advanced driver assist systems. LIDAR returns from the environment are typically predicted using elastic LIDAR models, which can help emulate the performance of LIDAR sensors in environments with multiple returns or heavy obscurants. We derive the first elastic LIDAR model for a random modulated continuous wave LIDAR system using a homodyne receiver and show good agreement with experimental measurements.

The promise of fully autonomous vehicles to replace the judgment of human drivers with real-time algorithmic decision-making based on optoelectronic systems relies fundamentally on the quality of the available data. Limitations imposed by sensor-resolution, available optical power, and achievable signal-to-noise ratios have been well studied in the light detection and ranging (LIDAR) application space. Additionally, the problem of integrating multiple sources of image data as well as the need to establish and maintain the system calibration over life are critically important to system reliability and safety. These latter concerns will receive even greater attention as self-driving vehicles begin to transition toward fully autonomous operation. Because of the importance of calibration to system performance and safety, the process of validating and recalibrating the system will ideally be integrated into the LIDAR system itself with calibration occurring automatically “anywhere and at any time,” without dedicated external infrastructure. Mass-market adoption is also being driven by the systems’ size and weight, as well as reliable manufacturability and resilience to environmental stresses. Due to their extreme stability, manufacturability, and small size, diffractive optical elements (DOEs) are well suited for use as optical calibration references. Current three-dimensional (3D) mapping systems based on structured light illumination already rely on DOEs as precision pattern generators to provide 3D depth sensing in a wide array mobile devices. We examine the potential use of DOEs as calibration elements in multicamera or LIDAR systems, including appropriate choices of materials, designs, and fabrication methods to ensure reliable long-term performance under automotive use conditions. We present simulations of the impact of DOE material properties on the accuracy of the generated dot patterns and consequently on the depth accuracy and lateral distortion of the 3D image. Additionally, we present requirements for DOE manufacture using conventional semiconductor fabrication technologies optimized for creating engineered surface nanostructures capable of transforming the output of a laser or other narrow-band source into a precise reference pattern.

The availability of public datasets with annotated light detection and ranging (LiDAR) point clouds has advanced autonomous driving tasks, such as semantic and panoptic segmentation. However, there is a lack of datasets focused on inclement weather. Snow and rain degrade visibility and introduce noise in LiDAR point clouds. In this article, summarize a 3-year winter weather data collection effort and introduce the winter adverse driving dataset. It is the first multimodal dataset featuring moderate to severe winter weather—weather that would cause an experienced driver to alter their driving behavior. Our dataset features exclusively events with heavy snowfall and occasional white-out conditions. Data are collected using high-resolution LiDAR, visible as well as near infrared (IR) cameras, a long wave IR camera, forward-facing radio detection and ranging, and Global Navigation Satellite Systems/Inertial Measurement Unit units. Our dataset is unique in the range of sensors and the severity of the conditions observed. It is also one of the only data sets to focus on rural and semi-rural environments. Over 36 TB of adverse winter data have been collected over 3 years. We also provide dense point-wise labels to sequential LiDAR scans collected in severe winter weather. We have labeled and will make available around 1000 sequential LiDAR scenes, amounting to over 7 GB or 3.6 billion labeled points. This is the first point-wise semantically labeled dataset to include falling snow.

Self-supervised depth estimation has achieved remarkable results in sunny weather. However, in the foggy scenes, their performance is limited because of the low contrast and limited visibility caused by the fog. To address this problem, an end-to-end feature separation network for self-supervised depth estimation of fog images is proposed. We take paired clear and synthetic foggy images as input, separate the image information into interference information (illumination, fog, etc.) and invariant information (structure, texture, etc.) by a feature extractor with orthogonality loss. The invariant information is used to estimate depth. Meanwhile, similarity loss is introduced to constrain the fog image depth using the depth of the clear image as a pseudo-label, and an attention module and reconstruction loss are added to refine the output depth, so that better depth maps can be obtained. Then, real-world fog images are used for fine-tuning, which effectively reduces the domain gap between synthetic data and real data. Experiments show that our approach produces advanced results on both synthetic datasets and Cityscape datasets, demonstrating the superiority of our approach.

Event-based vision has been rapidly growing in recent years justified by the unique characteristics, such as its high temporal resolutions (∼1 μs), high dynamic range (>120 dB), and output latency of only a few microseconds. Our work further explores a hybrid, multimodal approach for object detection and tracking that leverages state-of-the-art frame-based detectors complemented by hand-crafted event-based methods to improve the overall tracking performance with minimal computational overhead. The methods presented include event-based bounding box (BB) refinement that improves the precision of the resulting BBs, as well as a continuous event-based object detection method, to recover missed detections and generate interframe detections that enable a high-temporal-resolution tracking output. The advantages of these methods are quantitatively verified by an ablation study using the higher order tracking accuracy (HOTA) metric. Results show significant performance gains resembled by an improvement in the HOTA from 56.6%, using only frames, to 64.1% and 64.9%, for the event and edge-based mask configurations combined with the two methods proposed, at the baseline frame rate of 24 Hz. Likewise, incorporating these methods with the same configurations has improved HOTA from 52.5% to 63.1% and from 51.3% to 60.2% at the high-temporal-resolution tracking rate of 384 Hz. Finally, a validation experiment is conducted to analyze the real-world single-object tracking performance using high-speed LiDAR. Empirical evidence shows that our approaches provide significant advantages compared to using frame-based object detectors at the baseline frame rate of 24 Hz and higher tracking rates of up to 500 Hz.

We describe a method for detecting crossing pedestrians and, in general, any object that is moving perpendicular to the driving direction of the vehicle. This is achieved by combining video snapshots from multiple cameras that are placed in a linear configuration and from multiple time instances. We demonstrate that the proposed array configuration imposes tight constraints on the expected disparity of static objects in a certain image region for a given camera pair. These regions are distinct for different camera pairs. In that manner, static regions can generally be distinguished from moving targets throughout the entire field of view when analyzing enough pairs, requiring only straightforward image processing techniques. On a self-captured dataset with crossing pedestrians, our proposed method reaches an F₁ detection score of 83.66% and a mean average precision (MAP) of 84.79% on an overlap test when used stand-alone, being processed at 59 frames per second without GPU acceleration. When combining it with the Yolo V4 object detector in cooperative fusion, the proposed method boosts the maximal F₁ scores of this detector on this same dataset from 87.86% to 92.68% and the MAP from 90.85% to 94.30%. Furthermore, combining it with the lower power Yolo-Tiny V4 detector in the same way yields F₁ and MAP increases from 68.57% to 81.16% and 72.32% to 85.25%, respectively.

This paper describes the initial results from the first of 3 years of planned testing aimed at developing methods, metrics, and targets necessary to develop standardized tests for these instruments. Here, we evaluate range error accuracy and precision for eight automotive grade lidars; a survey grade lidar is used as a reference. These lidars are tasked with detecting a static, child-sized, target at ranges between 5 and 200 m. Our target, calibrated to 10% reflectivity and Lambertian, is a unique feature of this test. We find that lidar range precision is in line with the values reported by each manufacturer. However, we find that maximum range and target detection can be negatively affected by presence of an adjacent strong reflector. Finally, we observe that design trade-offs made by each manufacturer lead to important performance differences that can be quantified by tests such as the ones proposed here. This paper also includes some lessons learned, planned improvements, and discussion of future iterations of this activity.

To react to the presence of pedestrians, an automated braking system must first find the pedestrian(s) including locations relative to the automobile both in angular position and in distance. In the daytime, cameras and radar can provide the necessary information, but this combination, which requires ambient or active illumination, fails at night. Passive thermal sensors are now being enlisted to dramatically improve imaging at night, whereas substantial effort is underway to assure proper fusing of object information from the thermal sensor with other sensors on the automobile. To simplify the acquisition of information needed to make valid automated braking decisions at night, a camera system with a thermal image sensor was developed that identifies pedestrians and labels each identified pedestrian with location and distance data. The camera utilizes a single uncooled custom microbolometer sensor and a software suite implementing artificial intelligence and machine learning capabilities, running on a combination of convolutional neural networks and fusion processing to provide the data that an automobile host computer needs to implement fast, safe, and accurate automatic braking. We present details of the system construction and operation as well as initial test results showing the potential this technology has to dramatically reduce pedestrian fatalities at night as well as augment safety across all conditions, whether day, night, fog, rain, snow, dust, sun glare, or headlight glare.

Automotive LiDAR sensors are seen by many as the enabling technology for higher-level autonomous driving functionalities. Different concepts to design such a sensor can be found in the industry. Some have already been integrated into consumer cars while many others promise to be in mass production soon to become cost-effective enough for broad deployment. However, automotive LiDAR sensors are still evolving and a variety of sensor designs are pursued by different companies. Here, we construct the automotive LiDAR design space to visually depict system design options for these sensors. Subsequently, we exemplify the concepts with drawings that can be found in published patent applications (focusing on scanning mechanisms and scan patterns) before discussing their advantages and challenges.

Modeling and simulation (M&S) tools are used extensively throughout the Ground Vehicle Systems Center and the U.S. Army to perform an analysis of ground vehicles more quickly and less expensively than through physical testing. The Computational Research and Engineering Acquisition Tools and Environments-Ground Vehicles (CREATE-GV) project is an M&S software effort that focuses on mobility and autonomous vehicle simulation and analysis, using physics-based three-dimensional modeling to accurately calculate a variety of ground vehicle metrics and parameters of interest. However, because these simulations are high fidelity, they often require a great deal of computational power and time. One approach to reducing simulation time that has proved effective in certain contexts is the creation of “surrogate models” through machine learning (ML) algorithms. However, it is often very challenging to accurately predict the mobility of a ground vehicle system in general, and there is no existing model that can predict the mobility of autonomous systems. A great deal of uncertainty exists in the mobility and autonomy area of physics-based simulation models related to modeling assumptions, terrain conditions, and insufficient knowledge of interactions between the vehicle and terrain. Understanding how the uncertainties inherent in autonomous mobility prediction affect model accuracy is still an open fundamental research question. We present a surrogate modeling approach leveraging ML algorithms to work with CREATE-GV to increase the computation speed of mobility assessments while still considering the reliability of the mobility predictions under uncertainty.

Drawing from techniques used to dehaze visible, three-channel RGB images, we propose an approach to separate emissive and reflected radiance in images at short distances with a microbolometer-based longwave infrared (LWIR) camera system. The best case for optimal contrast and with the most descriptive information about the scene in an LWIR image would be where no external sources are radiating toward the scene. We introduce the concept of a blackbody channel prior (BCP) to multiband LWIR imaging to describe pixels that represent objects that behave most similarly to perfect blackbodies with an emissivity near unity. Most LWIR images of outdoor scenes are degraded largely in part by reflected sky path radiance. We can estimate scene radiance with a minimized reflective component producing images with enhanced contrast. Experiments on a number of multiband images are present to demonstrate this spectral-based BCP technique and show its potential for preserving scene information while achieving contrast enhancement.

The defect of silicon photovoltaic (PV) modules excited by photoluminescence (PL) technology at high light level (HLL) will be easily drowned in the ambient light; therefore, the detection equipment cannot sense the defect information directly. To solve this problem, a defect detection method that effectively resists the interference of ambient light in daytime is proposed in this paper. This method uses modulated light as the excitation for PV modules, and employs the near-infrared (NIR) camera to capture a group of image sequences satisfying the modulation characteristics. To restore the defect information of PV modules from image sequences, an algorithm based on time domain error is proposed. Finally, hardware acceleration of algorithm by field programmable gate array is implemented to solve the problem of time-consuming tasks for the personal computer. The experimental results show that this method can effectively restore the defect pattern with HLL extending from 0.1 lx to 11,170 ± 5 lx. Therefore, this work can provide an effective detection strategy for PL detection of PV modules at HLL.

Inkjet-print additive manufactured freeform gradient refractive index representations of an Alvarez-Lohmann lens were developed and optimized for use in vision-correction inserts for respiratory masks. A series of planar 30-mm by 20-mm Alvarez-Lohmann lens pair were printed and characterized. Select lens pairs were mounted with printed mechanical lens mounts and translation guides optimized for vision correction. Metrology showed accurate reproduction of the cubic refractive phase functions. Tests matching simulated performance showed a large diopter adjustment over a large eyebox and a wide gaze angle. The printed optics were environmentally tested and then mounted in a respiratory mask and demonstrated with glove-accessible control electronics. The performance demonstrates the benefits of using printed three-dimensional freeform gradient index optics for implementing complex refractive optical functions for challenging applications including artificial and virtual reality systems.

Deblurring turbulent images is an active topic in image processing and low-level vision research. Existing methods usually use the parametric physical model for nonblind image restoration, which lacks adaptability to different turbulent scenes. To overcome this challenge, a dual patch-wise pixels (DPP) prior is proposed for effective blind deblurring of turbulent images. A DPP-based turbulent image deblurring model was established based on the fact that the value of the DPP decreases through the turbulent blurring process, which has been proven both mathematically and experimentally. To solve the nonlinear DPP in the model, a linear mapping operator was constructed. Additionally, half-quadratic splitting and threshold methods were used to solve the L0 regularization term. Experimental results showed that the proposed algorithm performs well on various types of turbulent scenes as well as real images and outperforms state-of-the-art algorithms in terms of computational efficiency and effectiveness.

The traditional fractional order total variational model has better results in denoising and maintaining texture details in infrared images. However, it is difficult to determine the order of fractional order differentiation in image processing so that the model has the best denoising effect. To solve this problem, a fractional order total variational infrared image denoising model incorporating a flower pollination particle swarm optimization (PSO) algorithm is proposed in this paper. The model combines the search advantages of the flower pollination optimization algorithm and the PSO algorithm. The maximization multiobjective equation is designed as the fitness function of the optimization algorithm. The optimal order of the fractional order total variational model is found adaptively according to different features in different regions of the infrared image. The experimental results show that the improved model not only achieves the adaptivity of the adaption of the fractional order of total variational model order but also effectively removes the noise and retains the texture structure of infrared images to the maximum extent.

A pulse array image sensor (PAIS) is a bionic image sensor that converts light intensity into a pulse sequence to reduce the data volume. The traditional tracking method is not suitable for the sparse data form because of the absence of grayscale information. A trajectory tracking method based on a Bayesian classifier is proposed to maximize the property of the pulse data. First, candidate points with the smallest interval distances are selected in the area of interest. Then the total pulse numbers in a specified period at different positions are gathered to compose the positive and negative feature vectors, which are used to train a naive Bayesian classifier. The classifier can exactly obtain positions from the candidate points, and features in the new tracking positions train and update the classifier. The two-step filtering target point tracking algorithm using the interval distance and Bayesian classifier requires only the raw pulse data without processing, which can maximize the advantages of the special data format and improve computing efficiency. In this way, the position information can be directly obtained from pulse data, and the problem of wasting computing resources on reconstructing grayscale images and treating them in the traditional way is avoided. Experiments were performed on both real filmed data and the public event camera datasets. Our method can obtain trajectories with a high accuracy and long tracking time. The tracking errors are in single digits. In the comparison experiments, although our method has a smaller data volume than other models that obtain both frame and event data, the results still show that it has a comparable performance to the state-of-the-art methods.

By fusing a low spatial resolution hyperspectral image (LR-HSI) and a high spatial resolution RGB image (HR-RGB), hybrid-resolution hyperspectral imaging has been a popular framework for acquiring high spatial resolution hyperspectral images (HR-HSIs). Existing fusion methods always employ a known spectral response function (SRF) of the RGB camera to reconstruct the HR-HSI. The SRF is often limited or unavailable in practice, restricting the performance of existing methods. To address this problem, we propose a color space transfer-based fusion strategy that obtains HR-HSIs based on a hybrid resolution hyperspectral imaging system without measuring the SRF. Specifically, using a clustered-based backpropagation neural network, the HR-RGB is mapped into the CIE XYZ color space, and the HR-XYZ is obtained. In the CIE XYZ color space, its SRF is known; thus, the the SRF measurement is successfully skipped. To efficiently fuse the HR-XYZ and the LR-HSI, we propose a polynomial fusion model that estimates the ratio matrix between the target HR-HSI and the upsampled LR-HSI. Finally, the target HR-HSI is reconstructed by combining the ratio matrix and the unsampled LR-HSI. Experimental results on two public data sets and our real-world data sets show that the proposed method outperforms five state-of-the-art fusion methods.

The difference-map (DM) algorithm is an iterative method to retrieve the image of an object from its diffraction pattern. Our study proposes the use of nonnegative constraints, reducing the number of unknown variables by half, on both the real and imaginary parts of the object space to reconstruct the image of a complex-valued object in the iterative process of the DM algorithm. The feasibility of the algorithm in biological cell applications was demonstrated using both simulations and optical laser coherent diffraction experiments. The results show that a more accurate image of the object can be retrieved using a loose support by nonnegative constraints than by the same support alone. The comparison indicates that the DM algorithm is superior to the hybrid input–output algorithm in the presence of nonnegative constraints. Therefore, during the execution of a DM algorithm, a loose support allows for more accurate reconstruction than a tight support, which can hardly be found in most cases because of the noise blurring of the retrieved image, and considerable reduction in the reconstruction errors.

Chromatic confocal metrology suffers from a limitation in the number of measurement points that can be measured simultaneously in a single frame acquisition. We propose chromatic confocal areal metrology (ChromaCAM), in which the surface height for each point in a 2D grid of measurement spots, generated by a rectangular micro-lens array, is parallely analyzed through the utilization of a pinhole multiplexer unit, an analog optical analysis unit, and postprocessing algorithms. An experiment shows the viability of the simultaneous acquisition of multiple measurement points and the advantages over exisiting areal chromatic confocal approaches. Compared with conventional chromatic confocal metrology, the increase in the acquisition rate is significant and enables one-shot measurements.

Microplastics are an emerging marine pollutant, and their negative impacts on the photosynthetic efficiency of marine photoautotrophs are gradually endangering marine ecosystems and biota. To analyze and solve the impact of microplastic particles on light propagation in the ocean, the investigation of radiative properties of microplastic particles is essential. The extinction and absorption coefficients of polyamide-12 (PA12) with different particle concentrations are experimentally measured using transmission and integration methods in the spectral range of 200 to 1100 nm. The extinction and absorption cross sections are obtained from the measured extinction and absorption coefficients. The measured PA12 absorption peaks, located at 692, 728, 764, 835, and 940 nm, correspond to the vibrational absorption of methylene groups (-CH₂) and amide groups (CO-NH). The scattering albedo of PA12 is mostly above 0.7 in the visible spectral, indicating that PA12 is a scattering dominated medium. The measured radiative properties of PA12 provide optical parameters for determining the radiative transfer containing microplastics.

Laser interferometers and grating interferometers based on optical interferometry are widely used in displacement measurement of precision machining and testing equipment, such as the measurement system of integrated circuit equipment, due to their high precision, noncontact, and large dynamic measurement range. The ghost reflection in optical elements may lead to the periodic nonlinear error of the interferometer and also reduce alternating current/direct current. We propose a general method for automatic ghost reflection interface identification. It can analyze the influence weight of ghost reflection for each interface of any interferometer. In addition, the manufacturing cost of the interferometer is effectively reduced by optimization algorithms that enable ghost reflection avoidance in the interferometer design. Experimental results prove the influence weight of ghost reflection at different positions in the interferometer and provide the parameter selection of the most suitable interface reflection of the interferometer.

We investigate the key techniques in ammonia (NH₃) measurement based on midinfrared quantum cascade laser absorption spectroscopy technology. As the detection object, the system chose two absorption peaks splitting near 1122.16 cm ^{− 1} at 0.3 atm. It was also combined with wavelength modulation spectroscopy technology and a high-temperature environment to reduce NH₃ absorption in dynamic measurement. Allan variance was used to analyze the stability of the system. The optimal time to measure the average was 195 s, and the minimum detection limit was 121.58 ppb.

The accuracy of the shear-phase retrieval method is critical for accurate wavefront aberration measurements in double-grating Ronchi lateral shearing interferometry. Currently, the suppression of the interferences of unwanted diffractions generated by the Ronchi grating at the image plane is eliminated by adding more phase shifts, which increases the measurement time. Here, a stepped phase-shifting algorithm is proposed to suppress the unwanted diffractions and retrieve the shear phase between ±1st orders accurately with fewer phase shifts, and the measurement efficiency can be increased by 25% at least. The minimum number of phase shifts, which depends on the high diffraction orders existing in the interferograms, is analyzed. The proposed method was verified via numerical simulations and experiments. The wavefront measurement was validated via a comparison with the results of point-diffracted interferometry, and the root-mean-square difference was within 2.0 nm.

Optical measurement and perception technology is widely used in the field of smart energy. The accurate calibration of the internal and external parameters of the camera in the optical system is very important for the application of the system in three-dimensional (3D) reconstruction and geometric measurement. At present, the mainstream camera calibration methods include Zhang’s calibration method and Tsai’s calibration method. These methods all choose to calculate the distortion parameters together with the camera’s internal parameters. For long focal length and narrow-field-of-view cameras with smaller perspective distortion, the coupling calculation of parameters may cause inaccurate calibration parameters and more time-consuming problems. To improve the calibration accuracy of the long focal length camera, we propose an efficient noniterative camera calibration method, based on the equation relationship between the vanishing point coordinates and the first-order single-parameter division lens distortion coefficient, and based on the radial distortion separation model as well as the corner subpixel coordinates and checkerboard 3D space points. The spatial point correspondence is solved to obtain the homography matrix to complete the calculation of the internal parameters of the camera. Our work has potential applications in photovoltaic troubleshooting and intelligent inspection. It may also contribute to the practical application of the sensor in intelligent energy.

Radio frequency (RF) technology covers all fields of life, but with the increase in the size and complexity for circuit devices, traditional contact detection methods have difficulty solving the fault diagnosis problem of electronic circuits. The infrared thermal image fault diagnosis technology can realize perfectly real-time monitoring of the circuit due to it being non-contact and non-destructive and having fast recognition. At present, infrared thermal diagnosis technology can locate the fault but not know what causes the fault. Therefore, we propose a heterogeneous fusion image fault diagnosis method for RF circuits based on image perspective transformation and convolutional neural network (CNN). First, a variety of faults are set on the circuit board, and the faults are numbered; then the optical image, infrared thermal image, and oscilloscope image of circuit board under each fault are obtained by the corresponding instrument and fused heterogeneously. The fused image set is divided into the training set and validation set after enhancement and finally is fed into the CNN for training and classification. The accuracy of the final validation set reached 97.3%, which was 3.4% higher than that of only using infrared thermal image and optical image fusion, 2.7% higher than that of the LeNet5 model, and 1.5% higher than that of Vgg16 model, and the time was shortened by 15 min.

A simple and accurate method for determining the focal length of a lens is presented. There is no need to know the distance between lens principal planes and can be performed with easily available and inexpensive hardware. Depending on the test lens (TL) f-number, the error on determining focal length can be in the order of 0.1% of the focal length. We discuss determining focal length with the Newton equation f² = zz ^′ , with the Bessel equation f = ( (L − PP)² − D² ) / 4 ( L − PP ) , with equation f² = y ^′ ( y + y ^′ ) , or with equation f = ( y² − PP² ) / 4PP.

The THz reflection spectra of optically thin hexogen (RDX) samples were studied by terahertz imaging with spectral resolution. A photoconductive antenna excited by femtosecond laser radiation was used as a source of broadband THz radiation. The presence of a Fourier spectrometer (as well as band-pass THz filters) and a microbolometric THz video camera in the experimental setup made it possible to use the terahertz imaging method to study reflection spectra taking into account scattering in the range of 0.6 to 1 THz. The influence of the optical characteristics of the substrate on the THz reflection spectra was studied. In particular, the conditions for observing the effect of anomalous dispersion for RDX samples with different dispersion in the frequency region of the RDX absorption band 0.8 THz were studied. The obtained results demonstrate the application of the method of terahertz imaging with spectral resolution based on THz video camera for the identification of explosives with concentrations 0.75 to 50 mg / cm² on various surfaces.

At present, in the shear speckle interference technique for vehicle tire defect detection, the key is to accurately reflect the real phase of object motion when there are interference factors. Thus, this study proposes a discrete cosine transformation (DCT) unwrapping algorithm based on phase gradient smoothing correction, and analyzes the feasibility of the proposed method through several experiments and numerical simulation calculations. The proposed method replaces abnormal phase gradients caused by noise with calculated weighted moving average phase gradients, bringing phases closer to real values. Finally, the DCT unwrapping method is used to obtain the final solution of phase. A phase recovered using the proposed method is closer to the real value than that recovered using the traditional DCT unwrapping algorithm. Compared to the traditional DCT unwrapping algorithm, the root mean square error accuracy of the proposed method is improved by 10 to 100 times. And after many experiments to record the average running speed, it can be obtained that the time-consumption of the two algorithms only differs by ∼0.1 to 0.3 s.

Based on photonic integrated circuit (PIC) technology and synthetic aperture technology, the advanced technology of segmented planar imaging, which can be used to realize ultrathin and high-resolution imaging, is proposed. We develop a sampling lens array structure that combines coherent detection and traditional imaging; it can improve the sampling of low- and medium-frequency information. Based on the proposed lens array structure, a full-chain simulation model of the segmented planar imaging system is established. Under the premise of similar imaging quality, compared with the existing sampling lens structures, the proposed lens array has a simpler structure, lower processing difficulty, and lower cost. The simulation analyses of the duty ratio of the lens array, the light splitting number of PIC arrayed waveguide gratings, and the radius of the single lens are carried out. The simulation results provide a certain reference value for the optimal design of the segmented planar optical imaging system and further prove the advantages of the proposed structure.

The need for imaging and detecting in various instrument areas has brought light detection and ranging (LiDAR) to the forefront of consumer technology. Among different LiDAR, microelectromechanical system (MEMS) LiDAR has more appeal due to its small size and high integration. However, due to its low resolution and slight scanning angle, MEMS LiDAR does not apply to all scenes. Thus we presented a 360-deg scanning LiDAR emission optical system. Design formulas were deduced from theoretical formulas. In this system, the aspheric lens collimated the beam, MEMS micromirrors tracked the concentric circular beams, and the converging lens compensated for the divergence of the outgoing beam. By doing so, the target was scanned 360 deg at high resolution. With Zemax, the fast-axis divergence angle was 0.2484 mrad, the slow-axis divergence angle was 0.1546 mrad, and the system energy utilization rate was 84.16% with an angular resolution of 0.0142 deg at a distance of 10,000 mm. We have provided a potential solution for improving the scanning angle and resolution of MEMS LiDAR.

The long-wave infrared (LWIR) spectral region spanning from 8 to 12 μm is useful for many scientific and industrial applications. Many of these applications require use of either a bandpass or a bandstop filter that can be realized by the guided-mode resonance (GMR) effect with subwavelength periodic features in layered dielectric materials transparent in the LWIR. The GMR filters operating in the LWIR region are fabricated by depositing an amorphous germanium (Ge) film to form a zero-contrast (ZC) waveguide-grating (WGG) on a polished zinc selenide (ZnSe) substrate. In general, the backside of a ZnSe substrate with refractive index 2.41 is uncoated causing a 17% Fresnel-reflection loss in the light transmitted through the filter due to a large impedance mismatch at the ZnSe/air interface. Because we use such filters in the LWIR laser experiments for notch filtering, to improve the filter transmittance we used ZnSe substrates coated on one-side with broadband antireflection coating (ARC) covering the 7 to 12 μm spectral range to fabricate GMRFs with one-dimensional (1D) Ge ZC WGG. We employed high-spatial resolution e-beam lithography and reactive-ion etching nanofabrication techniques to achieve high-performance large-area (12 × 12 mm²) 1D notch filters with subwavelength periods. We characterized polarization dependent spectral performance of the prototype filters with both coherent and incoherent incident light using a tunable quantum cascade laser system that spans the 7 to 12 μm region, and a Fourier transform infrared spectrometer with collimated incident beam to achieve close to 15% improvement in the peak transmittance as well as significant reduction in coherent noise compared to our earlier results with GMRFs without ARC. Here, we present the filter design simulation and measurement results.

Focus-tunable lenses, e.g., liquid filled membrane lenses (MLs), have found increasingly widespread application in optical systems. If a large refractive power range is to be used, the correction of chromatic aberrations is particularly challenging: a group containing a single ML cannot be corrected over the whole refractive power range. In analogy to hybrid achromats for lenses with constant focal lengths, we present the combination of an ML and a diffractive Alvarez-Lohmann-lens (ALL) for the compensation of axial color over a large refractive power range. In contrast to the combination of multiple MLs, this does not increase the axial length of the system significantly. At the same time, the flexible adaption of the phase function of the diffractive ALL can reduce spherical aberration over the whole focal range. Design examples with ray-tracing and wave-optical simulations demonstrate the performance of the resulting hybrid tunable element. Experimental data from fabricated sample lenses provide a proof of principle.

Freeform imaging systems are a subject of current interest. To aid in the design of such systems, we introduce structural aberration coefficients for plane symmetric imaging with XY-polynomial freeform surfaces that may also be tilted. Further, we extend the coefficients to systems with an arbitrary number of components and specifically provide analytical equations for two-mirror systems. Distinguishing between system configuration and structural parameters enhances clarity, which we highlight by deriving new conditions for minimum root-mean-square (RMS) spot size and minimum RMS wavefront error in aplanatic two-mirror telescopes.

The presence of clouds affects the detection of small airborne targets for infrared imaging. Clouds increase the signal of the background and create nonuniformity behind a desired target. This results in low and varying contrast. Clear sky conditions provide a low noise, uniform background that gives a better chance of detection. Understanding key variables of the clouds nonuniform structure allows for better detection and for accurate infrared search and track (IRST) models. Atmospheric modeling software, such as moderate resolution atmospheric transmission (MODTRAN), provides background path radiance in the emissive midwave infrared and longwave infrared bands. These modeled skies have been matched with measured skies in various conditions with low error. MODTRAN clouds, however, assume total cloud cover of uniform thickness and no varying transmission. MODTRAN clouds do not consider the spatially and radiometrically varying structures that make clouds unique. Studied spatial and radiometric characteristics of clouds are used in an empirical approach to predict cloud radiometric temperatures and structures with four simple equations. These cloud properties are measured at night to avoid solar contributions and focus on their emissive characteristics. The empirically modeled clouds are projections from measured or MODTRAN modeled clear skies. This method of modeling clouds allows for easy implementation of a nonclear sky background into IRST models. The range in which a target is first detected from its background can now be compared between clear and cloudy skies.

With the average power of commercial ultrafast lasers reaching the kW-level, process parallelization is required to avoid detrimental quality issues, such as caused by heat accumulation. This is especially relevant in the case of helical drilling, as the processing strategy is only employed when precise geometry, high-quality surface finish, tight tolerances, and high reproducibility are a priority. We illustrate that parallelization by means of a multipass process is conceptually attractive for pulsed drilling processes, but also challenging due to limitations imposed by the properties of appropriate beam-steering devices. While paraxial beam propagation methods applied to the suggested setup predict no aberrations, deviations from the idealized solution are a concern. Our experimental proof-of-principle investigations show that parallelization by means of a deflector preceding the helical drilling optics is possible while ensuring nearly identical processing parameters for all parallelly processed boreholes.

To realize the quasi-quantitative Schlieren measurement of the shock train structure across the cylindrical isolator in the supersonic flow field, based on the theory of Schlieren measurement and light transmission, we propose the design scheme of conformal windows and discuss the machining feasibility with the window’s parameters. The relationship between the Schlieren imaging effect, the deflection of parallel light in the Schlieren apparatus, and the conformal optical window aberrations was researched, putting forward the optical simulation model of the conformal optical windows and the quasi-quantitative Schlieren measurement. Moreover, considering the actual wind tunnel test conditions, under the speed of Mach 2 at the isolator’s inlet, the distortion brought by conformal optical windows in the Schlieren observation region was simulated by the computational fluid dynamics method. Finally, the image correction algorithm for the distorted picture caused by the conformal windows was presented, and the quasi-quantitative Schlieren measurement through the conformal optical window pair was conducted for the experimental verification. The results reveal the quasi-quantitative Schlieren measurement effect across the high-precision conformal optical window pair of the cylindrical isolator, providing guidance on maintaining the balance between the manufacturing feasibility and the observation performance of conformal windows.

We propose the use of slope orthogonal polynomials as a tool to manage distortion. The object-to-image mapping of the whole optical system is reduced to a single refracting surface, which reproduces the same lens mapping function (LMF) as the original optical system. Using slope orthogonal polynomials to describe this LMF equivalent surface, the orthogonal properties of the polynomial can be leveraged for efficient use of ray tracing by relating coordinates mapping to a surface gradient. We demonstrate that this distortion measurement can be linked to a physical surface aspherical departure in the case of a double Gauss objective. This relationship can be established for any surfaces, after a calibration step. We also show that this same relationship can be used to obtain a target LMF by setting a precomputed aspherical surface departure on a given surface.

The effects of geometry and horizontal positioning of ultrathin triangular silicon nanowires (SiNWs) on the function of solar cells (SCs) have been investigated. Two differentiated methods have been presented to improve the current density of SiNW-SCs. First, a semiperiodic array is used for better utilization of the optical antenna effect. In the second method, several NWs with different geometries are used to achieve broadband absorption. The key to increase absorption is irregularity. Therefore, maximum light absorption is achieved by introducing irregular NWs. A set of optimized irregular NWs have better properties compared to other broadband structures. Using irregular NW arrays, the increase in the absorption of SCs can be improved without applying more absorbent materials. Optimization processes are used to obtain the maximum current density of SCs.

In this study, an experimental system was developed using a broadband wavelength-swept laser for fast and broadband spectroscopic measurements at ∼1550 nm. The broadband wavelength-swept laser employed Fourier domain mode-locking (FDML) to realize a high-speed sweep rate of 50.7 kHz. FDML lasers at ∼1550 nm experience a problem of the sweep bandwidth being limited by the amplification wavelength range of the semiconductor optical amplifier (SOA). To realize a sweep bandwidth >100 nm, the proposed broadband FDML laser incorporated SOAs with different amplification wavelength ranges in parallel. Consequently, it expanded the sweep bandwidth to 120 nm at a center wavelength of 1544 nm. The experimental system employed the broadband FDML laser and introduced reference and compensation optics. These optics can compensate for the effects of fluctuations in optical output intensity and wavelength shift in the laser to improve measurement stability. Moreover, the experimental system demonstrated fast transmission spectrum measurements with a wavelength range of 1500 to 1580 nm.

The portable laser is indispensable for handheld laser-induced breakdown spectroscopy (LIBS) instruments. We developed a passive, Q-switched pulsed, Nd:YAG laser system with small size and low cost. The maximum pulse energy of the laser was 10 mJ and the pulse duration was <2 ns. The peak power was >5 MW. The laser exhibited very high stability without any cooling system and its relative standard deviation of the pulse energy was <0.2 % . The laser was also used as a light source of LIBS to measure the concentrations of Cr, Cu, Mn, and Ni in alloys. The experimental results show that the determination coefficient of the calibration curves for these four elements is all better than 0.99. For its shorter pulse duration, the laser can decrease the plasma shield effect to improve the coupling of laser pulse and the target and stability of spectra intensity. The portable laser developed is a good laser source for handheld LIBS instruments.

Solar-pumped lasers have promising potential in space technology. The first solar-pumped 1061-/1064-nm dual-wavelength Nd:YAG monolithic laser is proposed. The resonant cavity of the laser is formed by coating the dielectric film directly on both ends of the laser medium, and the thin film coated on the output end is specially designed to adjust the transmittance at 1061 and 1064 nm, thus balancing the threshold pump power and realizing a dual-wavelength output. Through theoretical analyses and simulations, a solar-pumped 1061-/1064-nm dual-wavelength laser with improved output power of 81.3 mW was achieved, corresponding to the slope efficiency of 0.13% and the optical-to-optical efficiency of 0.085%, which provides a possible solution for dual-channel space laser communication.

Intensity degenerate orbital angular momentum (OAM) modes are impossible to recognize by direct visual inspection even using available machine learning techniques. We are reporting speckle-learned convolutional neural network (CNN) for the recognition of intensity degenerate Laguerre–Gaussian (LG_{p , l}) modes, intensity degenerate LG superposition modes, and intensity degenerate perfect optical vortices. The CNN is trained on the simulated one-dimensional far-field intensity speckle patterns of the corresponding intensity degenerate OAM modes. The trained CNN recognizes intensity degenerate OAM modes with an accuracy >99 % . Speckle-learned CNNs are also capable of recognizing intensity degenerate OAM modes even under the presence of high Gaussian white noise and atmospheric turbulence with an accuracy >97 % .

A highly sensitive self-referenced surface plasmon resonance (SPR) fiber optic sensor with an indium tin oxide (ITO)/metal/dielectric structure is proposed and theoretically analyzed using the transfer matrix method-based numerical simulations. First, the thicknesses of the metal and ITO films are optimized to realize self-referenced sensing with low normalized transmission power at the resonance peak. Then, a thickness-optimized dielectric (TiO₂) film is employed on top of the metal film to improve the sensitivity of the proposed self-referenced sensor. In addition, a comparison between the traditional self-referenced sensor and the proposed self-referenced sensor with the dielectric film are carried out. The self-referenced sensor with a 36 nm ITO/37 nm Ag/70 nm TiO₂ structure obtains up to 14510 nm/RIU in sensing sensitivity when the refractive index of the analyte varies from 1.33 to 1.37, which is improved by 421% compared with the traditional one without the dielectric. At the same time, the shift of the self-referenced resonance wavelength changes little for the proposed structure. The proposed ITO/metal/dielectric structure-based fiber optic sensor exhibits highly sensitively self-referenced sensing performance in the near infrared band, which can promote its application in the field of biosensors.

We designed an all-normal flat near-zero dispersion As₂S₃ photonic crystal fiber (PCF) with orderly arranged air hole rings for generating an orbital angular momentum (OAM) supercontinuum (SC). We optimized the characters of chromatic dispersion and confinement loss compared with previous studies by carefully engineering the PCF. Simulation results show that, by launching a 100 fs 250 kW chirp-free hyperbolic secant pulse at 7 μm into a 5-mm designed PCF, a 9471-nm SC of OAM_1,1 forms from 757 to 10228 nm at a −40 dB level, which covers a 3.7-octave bandwidth. As the peak power increases, the higher-order OAM with a flatter chromatic dispersion profile in the normal dispersion region has a wider bandwidth. They are all highly coherent in the whole spectral range.

A v-shaped microstructured optical fiber (MOF)-based surface plasmon resonance (SPR) sensor is proposed for simultaneous measurement of temperature and refractive index (RI). Such a v-shaped structure could be coated with the gold layer conveniently, simplifying the sensor fabrication. We theoretically investigate the coupling property between the core mode and the plasmon mode, the polarized characteristics of the core modes, the behavior features of the resonance peaks and the sensing performance of the sensor at different temperatures and RIs. The simulation results demonstrate that the v-shaped structure can support two polarized resonance peaks (x- and y-polarized peaks) that have different response characteristics for the changes of temperature and RI, the temperature coefficients of x- and y-polarized peaks are 11.8 and 6.2 pm / ° C, the RI coefficients of x- and y-polarized peaks are 1408 and 1505 nm / RIU, respectively.

A single sideband (SSB) phase-modulated link with an improved spurious-free dynamic range (SFDR) is proposed and experimentally demonstrated. By generating a single-sideband phase-modulated signal containing a specific spectrum for demodulation, the third-order intermodulation distortion (IMD3) is effectively suppressed. The theoretical analysis is presented, and the experimental results show that a carrier-to-interference ratio of 62.45 dB is achieved. The improved SFDR is 120.25 dB · Hz^4/5, which is 14.47 dB higher than that of a conventional SSB phase-modulated link.

To compare the processing efficiency and quality of 20- to 1000-Hz pulsed laser and continuous laser ablating single-crystal germanium wafers, experiments and numerical simulations were performed. The experiments were conducted by varying the duty cycle and repetition frequency of a pulsed laser to ablate single-crystal germanium with the same total laser energy and irradiation time of 100 ms, and comparing the temperature-rise profile during ablation and the damage morphology after ablation. The temperature-rise curves during the ablation and the damage morphologies after the ablation were compared. Numerical simulations were performed to compute the dislocation field of single-crystal germanium ablated by laser with different parameters to compare the size of the heat-affected zone (HAZ) formed on the sample surface after the laser ablation with different parameters. The results show that the sample surface has the largest ablated pore size and the smallest HAZ after ablation at a laser repetition frequency of 20 Hz and a duty cycle of 5%; the smallest pore size and the largest HAZ after ablation at a laser repetition frequency of 1000 Hz and a duty cycle of 50%, and the continuous laser results are in the middle.

The power scaling of an all-solid-state visible laser is limited by the mode-to-pump ratio related to the thermal effect based on the spatial rate equation. The mode-to-pump ratio is also known as the overlap efficiency factor (OEF). We investigated the thermal effect as a function of pump power, the waist radius of pump beams, and the waist position of pump beams and have simulated the three-dimensional distribution of the OEF as a variable of the waist position and size of pump beams. Also, it is seen that the calculated optimal OEF under a plane–concave cavity is a decreasing function of input pump power, and it is less than unity in the case of high pump power. The practical example of a Pr:YLF laser pumped by 9-W fiber-coupled laser diodes confirms our theoretical analysis. The output power instability was < ± 1 . 625 % (RMS) within 1 h. In addition, by changing the cavity length to 38 mm, the output power of 607 nm is up to 103 mW with an OEF of 0.741.

We report a compact and highly stable 1064-nm electro-optic Q-switched laser operating at the repetition rate of 1 kHz. A composite Nd:YAG crystal was used as the gain media and the cavity length was 105 mm. Under the average pump power of 11 W, the output power achieved 2.404 W with the pulse width of 4.558 ns, corresponding to the maximum peak power of 0.527 MW and the optical-to-optical conversion efficiency of 21.85%. The slope efficiency reached 42.69%. The beam quality in the horizontal (Mx2) and vertical (My2) directions were 1.81 and 1.58, respectively. The pulse timing jitter was less than 1 ns, and the average power fluctuation measured within 30 min was 0.83% (RMS). It is believed that such a compact and highly stable pulsed laser with high repetition rate, high peak power, and good beam quality has great potential in the fields of lidar, etc.

The thermal-optical property of an ultralow expansion (ULE^®) 7973 glass wafer was assessed using spectrophotometers and variable angle spectroscopic ellipsometers. By modeling both the spectral transmission and the ellipsometric data, we derived optical dispersion of the glass over a broad spectral region from 180 nm up to 12 μm. Our results indicate that the transparency region of the glass is terminated by two fundamental absorption edges in the ultraviolet (UV) and the infrared (IR). The UV and IR absorption edges are dominated by the titania and silica constituents, respectively. The exponential absorption tail, the Urbach energy, in the UV increases linearly with the temperature ranging from room temperature to 650°C, whereas the optical bandgap decreases linearly over the same temperature range. The temperature-dependent coefficient is 18 μeV / ° C for the Urbach energy and −0.7 meV / ° C for the optical bandgap.

We present an Nb₂O₅-based grating coupler that employs multiple Nb₂O₅ / SiO₂ layers to improve the optical input/output power efficiency of a scanning differential laser-Doppler integrated probe for two-dimensional cross-sectional velocity distribution measurements. The multiple Nb₂O₅ / SiO₂ layers are designed for both the transmitting grating coupler and the receiving grating coupler. To demonstrate the effect of the designed multiple layers, the field distribution around the grating coupler is simulated as a feasibility study of the concept. The results indicated that the input/output power at the grating coupler can be improved using multiple Nb₂O₅ / SiO₂ layers over the input/output angle of 0 to 20 deg and the wavelength of 1530 to 1570 nm. The increase of the input/output power and the focusing from the transmitting grating coupler were confirmed by the simulation using the finite-difference time-domain method and beam propagation method.

In recent years, lead-free metal halide luminescent materials have attracted extensive attention because of their excellent properties including but not limited to good environmental compatibility, ultrawide emission band, and high photoluminescence quantum yield. They are considered to have great application potential in the photoelectric field. We modified the previously reported synthesis and prepared pure phase Cs₂SnCl₆ : Bi^{3 +} , Te^{4 +} using simple solution method. Then the emitter was further coated with polysiloxane to form polysiloxane luminescent ceramic (PSOLC). The prepared PSOLCs have almost the same luminescence as the powders, and their color coordinates and color temperature can be tuned freely by adjusting the ratio of blue and yellow emission, which both encourage outdoor-lighting application. Additionally, they are demonstrated to support flexible luminescence and show highly improved machinability. To test their performance in practical application, we apply the PSOLCs to safety identification board and finally get a satisfactory result, directly indicating that the PSOLCs prepared from lead-free perovskite are quite suitable for flexible-lighting-related display applications.

Polarization information is widely used in complex applications such as industrial detection, biomedicine, earth remote sensing, modern military, and aerospace. However, traditional polarization devices cannot adequately satisfy the requirements of increasingly complex environments. A subwavelength grating consisting of three types of materials, namely, aurum, platinum, and titanium, was designed to improve the performance of the polarimetric components of a midwavelength infrared polarization imaging system. The morphological structure parameters of the designed grating were optimized by analyzing the effects on the polarization performance through the rigorous coupled wave theory. The proposed Au–Pt–Ti composite grating could address the problem of grating peeling off from the substrate because of high temperature during preparation. The composite grating has some advantages such as high mechanical stability, lower oxidation, and great polarization properties. The diffraction can be reduced and the extinction ratio (ER) can be effectively enhanced in a midwave infrared (MWIR) focal plane array through appropriate reduction in the termination edge spacing and the addition of a gold frame between polarizer pixels. The grating with a period of 0.8 μm was designed for application in the MWIR band. The fill factor was 0.5 and the depths of Au–Pt–Ti in the grating region were 0.44 μm. Each pixel was separated by a 3.2-μm wide gold frame. Modeling results revealed that the ER of grating was higher than 28.68 and 32.77 above the incident wavelengths of 3.89 and 4.57 μm, respectively. Additionally, excellent polarization capability was observed over a wide MWIR spectrum. Furthermore, the current manufacturing process level may generate polarizers with the aforementioned structural specifications.

We developed and characterized luminescent temperature sensors with a simple construction based on YAG : Ln^{3 +} (Ln = Nd, Yb, Ce) nanocrystals and silica multimode optical fibers. Lanthanide-doped nanocrystals 40 to 60 nm in size were synthesized in the form of powders using the modified Pechini method. The obtained materials exhibited high sensitivity of luminescence intensity to temperature variations at wavelengths of 550 nm (YAG : Ce^{3 +} ), 1030 nm (YAG : Yb^{3 +} ), and 1064 nm (YAG : Nd^{3 +} ) in the temperature range 50°C to 600°C. Additionally, we offered a method to eliminate influence of vibration on accuracy of temperature measurements by adding SiO₂ sol to powders after their synthesis in sensitive elements.

A simply designed broadband meta-absorber (MA) that works in terahertz (THz) band is proposed and investigated. The reflector substrate of the MA is composed of nickel. The middle layer of this structure is made of dielectric Al₂O₃, which serves as a dielectric layer between the nickel and the metasurface layer. The metasurface layer comprises a graphene ring with a disk-like Au in the center. The wideband absorption mechanism benefits from the hybridized surface plasmonic modes caused by the coupling between the Au disk and the graphene ring. Besides, with the adhesion of the top Au metal disk, Fabry-Perot cavities formed by the top Au and the bottom metal produce the continuous cavity resonant modes also to enhance surface hybridization plasmons. Because the proposed broadband MA is symmetrical, it is insensitive to polarization and has a good bearing angle of 0 deg to 70 deg. The results of our study may inspire specific applications of wave modulation, including THz imaging, detecting, modulation, and sensing.

We propose a monolithic integrated cavity optomechanical accelerometer based on push-pull photonic crystal zipper cavity. The accelerometer integrates grating couplers, phase modulators, acceleration sensing unit, and electrostatic force feedback module on a chip. We use push-pull structure to eliminate the coupling crosstalk caused by paraxial acceleration and extend its range using electrostatic force feedback module. The transmissive photonic crystal zipper cavity structure is adopted to improve the integration and stability of the system. Accurate results are demonstrated as follows: the bandwidth is larger than 20 kHz, the mechanical sensitivity is 369 pm/g, the measuring range is ±100 g, and the noise equivalent acceleration is 5.06 μg / Hz. With its advantages, the accelerometer can be used in consumer electronics, aerospace, resource exploration, and other fields.

In view of recent developments in the utilization of terahertz (THz) communications technology for the increasing demands of high speed and data rates for various wireless applications, this research work targets the design and analysis of distributed Bragg reflector (DBR)-based hybrid plasmonic THz waveguide. This THz waveguide operates at a frequency range from 2.5 to 3.5 THz. The proposed DBR-based hybrid plasmonic THz waveguide consists of DBR layers of gallium arsenide (GaAs) and aluminum arsenide, high-density polyethylene (HDPE) as substrate, a GaAs stripe for wave-guidance, and few layers of graphene layers in HDPE for better confinement. To increase the light confinement between DBR and graphene, a GaAs strip is placed into HDPE. By altering the width and height of the GaAs strip, the parameters birefringence, mode field diameter (MFD), confinement loss, effective mode area, beat length, and dispersion have been fully examined. The obtained simulation results shows high birefringence of 0.6276, maximum MFD of 45 mm, low confinement loss of 7.5 × 10 ^{− 9} mm ^{− 1}, high effective mode area of 16.5 mm², and low anomalous dispersion of 0.0023 (ps/THz/cm) in the range of 2.5 to 3.5 THz. This optimized THz waveguide may helps to enable in guided THz applications for photonic integrated circuits.

We present the low-density parity-check-coded nonrecursive Gaussian minimum shift keying-based hybrid modulation scheme for free-space optical (FSO) communications under optimal signal-to-noise ratio, limited power, and spectrum resources to support 5G and beyond applications with high-throughput efficiency. Our work investigates and approximates the error rate of the proposed scheme across a negative exponential stochastic FSO channel model with misalignment-induced fading. Using the Meijer-G function over the combined channel probability density function, we develop a unique closed-form formulation of outage probability. The potential benefits of utilizing the normalized beamwidth to achieve the desired error rate ( ≈ 10 ^{− 12} ) is discussed. An improvement of 88.64% in the case of narrow beamwidth is perceived which collaborates with the proposed analytical expressions. The precision of our study is supported by numerical data from Monte Carlo simulation.

In free space optical (FSO) communications systems, the signal fading caused by atmospheric turbulence is a slow fading, so adaptive transmission technology can effectively mitigate the problem of channel fading. Considering the combined effects of turbulence, attenuation, and pointing errors on the atmospheric transmission of laser signals, we proposed an adaptive M-ary phase shift keying subcarrier modulation algorithm based on power control and studied the combined adaptation of modulation size and average transmit power. Karush-Kuhn-Tucker conditions are used to solve the optimization problem of maximizing the throughput under the constraint of average transmit power, the expressions of throughput and outage probability are derived based on Meijer G-function. We finally evaluated the effects of turbulence intensity, beam waist radius, jitter standard deviation, weather conditions, and maximum modulation order on the throughput and outage probability of adaptive system.

Based on periodically poled lithium niobate, a scheme for optical signal temporal cloak and encryption in the optical physical layer is proposed and numerically studied, in which the amplitude and phase information of the symbols to be sent are detected and transmitted while that of all other symbols will be hidden from the receiver. Meanwhile, the phase and amplitude of the symbols that are not hidden can be encrypted according to arbitrary encryption rules in the optical physical layer. The simulation results show that there is almost no ripple in the cloak time window, which makes the performance of temporal cloak quite well. The output signals with high Q factor can be obtained when the linewidths of the tunable lasers are <300 kHz. Two simple encryption rules are designed, 43.75% of binary codes will be misinterpreted by eavesdropper if the signal is encrypted with such two rules in the demonstration.

Here, an optical pulse controlled 2 × 2 surface–plasmon–polariton (SPP) mode interference coupler based on graphene clad is designed for the operation of optical fundamental gates. Exploiting the light–matter interactions on graphene–silicon interface and nonlinear optical property of graphene, coupling characteristics are obtained as a function of extra phase change between the excited SPP modes (fundamental and first order) modes with incidence of optical pulse. The device with a very small coupling length of ∼4.3 μm shows optical NOT, AND, and OR gate operation. Our compact design with high fabrication tolerance opens an avenue for the development of a complex optical processor.

The nonlinearity and memory effects induced by light-emitting diode distort the transmitted signal, which significantly limits the performance of visible light communication (VLC) system. With the characteristics of low computational complexity, fast convergence speed, and strong generalization ability, least squares support vector machine (LSSVM) is investigated in this paper and employed to alleviate the nonlinear effect. Since the performance of LSSVM is largely determined by the type of the adopted kernel functions, we utilize Gaussian and Laplace functions and propose a new combined kernel, which can increase the reproducing kernel Hilbert space and thus enhance the global expressive power compared with conventionally used Gaussian kernel. To further improve the performance, a hybrid parameter optimization algorithm is exploited to optimize the proposed kernel, based on genetic algorithm and particle swarm optimization. The property of the proposed postdistortion method is verified by numerical simulations, and better performance is obtained in VLC systems compared with the Gaussian-kernel LSSVM and conventional memory polynomial method.

Conventional visible light positioning (VLP) schemes usually require at least three light sources, making positioning accuracy sensitive to shadowing, a limited number of light sources, or sparse light-emitting diode (LED) layout. We proposed a mirror-assisted VLP system, where two-LED positioning can be realized by adopting specular reflection and time–frequency combination method. The scheme is based on the concept of virtual lamps and the received signal strength algorithm. Specular reflection power from one of the virtual lamps is integrated into the effective positioning power of its corresponding real lamp to obtain increased received power and mitigate the impact of diffuse reflection. Meanwhile, the other virtual lamp is independently used as the third light source for positioning, which means that the system becomes a “pseudo” three-LED positioning system, so that positioning can be realized with only two real lamps available. The corresponding positioning accuracy evaluated numerically shows an upward trend as the distance between the receiver and mirror decreases. By reducing the distance between the transmitters and the mirror, the positioning error can be limited to ∼12.4 cm.

We provide an experimental study of the channel characteristics in an underwater wireless optical communication (UWOC) system given by a 35-m transmission distance in various water types. A UWOC system using a low-power 488-nm laser diode is established to comprehensively evaluate the influence of the link distance, water turbidity, receiver parameters, and link misalignment on the communication link power. The results show that the link misalignment-induced power loss is significant and the effect of receiver parameters on power is limited. However, a higher turbidity or longer signal transmission distance can help to reduce the link misalignment effect and manifest the receiver parameters effect on the received power. In particular, in turbid waters with an attenuation coefficient of 0.471 m ^{− 1}, the change of the signal reception power curve is small over a certain degree of the link misalignment in the 35-m physical distance, and the reasonable configuration of receiver parameters effectively improves the signal reception quality in the UWOC system. These results can provide theoretical guidance for optimizing the UWOC system.