Optics and Lasers in Engineering最新文献

This paper presents an innovative GPI-NCCSR subdivision approach for grating displacement sensor based on grating projection imaging (GPI) and normalized cross-correlation sub-pixel registration (NCCSR) algorithm, achieving high subdivision within the grating pitch and exhibiting robust immunity to fluctuations in light source intensity. The GPI method facilitates the creation of long-period longitudinal moiré fringes more readily, and capturing moiré fringe information with a line-scan CCD allows for an extremely high subdivision. The NCCSR approach to displacement detection is impervious to signal amplitude fluctuations, thus enhancing the stability of the subdivision. Moreover, the sub-pixel registration algorithm can improve resolution even further. The experiments demonstrate that the proposed subdivision method achieves a displacement resolution superior to 4nm_RMS, indicating a subdivision multiple within the 20µm pitch exceeding 5000 while remaining unaffected by variations in light intensity. Besides, the sensor exhibits repeatability accuracy better than 0.05% across various measurement points, with a linearity of 0.17% within a 3mm range.

With an increasing number of countries engaging in space activities worldwide, space non-cooperative target tracking and identification technology has become a prerequisite for safely conducting space operations. In order to the identify distant non-cooperative targets performing complex motions, this paper proposes a method to recognize difficult parameters by using easily available signal labels as privileged information, which is named Pi-FcResNet. The privileged information is connected to the output end of the network through a fully connected network and coupled with the linear layer of the main network. Through testing, our network achieved a recognition accuracy of 94.45 % for precession angles under high signal-to-noise ratio conditions. After incorporating the Convolutional Block Attention Module (CBAM), our method demonstrates fast fitting speed and robust performance. Testing on experimental data shows that, compared to traditional methods, our approach offers better stability and reproducibility in recognizing micro-motion parameters. This approach of using known information as additional information for deep learning networks holds great potential in the field of feature extraction for space non-cooperative targets undergoing complex motions.

Existing signal separation methods such as Fourier transform, wavelet transform, empirical mode decomposition, and variational mode decomposition are ineffective in separating mixed pulse sequences. This paper proposes an adaptive decomposition method for mixed pulse sequences by analyzing the generation mechanism and time-frequency characteristics of mixed laser pulse sequences in an accurate laser positioning system (ALPS). This method can adaptively decompose mixed pulse sequences into steady-state or non-steady-state pulse trains, with decomposed results having clear physical meanings. The effectiveness and robustness of the proposed adaptive decomposition method for mixed pulse sequences are validated using the ALPS platform. Experimental results demonstrate that this method can adaptively decompose ALPS mixed pulse measurement sequences and has strong interference resistance. This paper provides new insights into adaptive decomposition methods for signals with many discontinuous points, offering new tools for diagnosing faults in rotating machinery and monitoring sub-cycle speed fluctuations. Additionally, based on this method, a coordinate online calculation model for ALPS measurement nodes is designed, which increases the coordinate data refresh rate of ALPS by more than ten times, effectively improving the system's dynamic measurement performance.

This paper presents a laser screen imaging measurement system (LSIMS) based on arrayed fibers to measure the velocity and dimension of a flying object. A laser diode is connected to the emission module of the laser screen via a single-mode fiber, then the emitted light beam is collimated into a parallel beam with a lens, this structure is arrayed to form the laser screen. The receiving module of the laser screen employs a cylindrical lens array to converge the collimated beams into a focal line. The input ends of the plastic fibers are arrayed along this focal line, while the output ends are imaged on the sensor of a line scan camera (LSC) through a lens. The LSIMS effectively modulates the process of a flying object passing through the laser screen into the light intensity change in the plastic fibers. The velocity and dimension of the flying object are subsequently measured through the analysis of the image obtained by the LSC. The timing accuracy of the LSIMS is verified through experiments. The velocity and diameter of pellets launched by a slingshot are measured and analyzed for errors.

With the continuous advancement of optical imaging technology and the increasing requirement for remote sensing applications, high-resolution spatial imaging technology has been extensively researched. Subject to the diffraction limitation, the optical aperture is continuously increasing to obtain more target details, which leads to larger satellite platforms and higher manufacturing costs. In order to balance the cost of satellite platforms and the imaging quality of space cameras, this paper focuses on the optical aperture, which affects both of the above by conducting an end-to-end analysis of the space imaging process to examine its effects on overall imaging spatial quality. This paper formulates the optical aperture optimization problem by establishing the evaluation functions for deployment cost and imaging quality. Two types of optical systems commonly used in space imaging, the coaxial reflective optical system with annular aperture and the topologically compact optical system with square aperture are studied based on the proposed optimization model. Their imaging characteristics and design principles are summarized. The optimization model proposed can be applied to the optical aperture design of any manufacturable optical system to guide the design of the entire space camera and even the satellite platforms.

The computed tomography of chemiluminescence (CTC) can be used to reconstruct a three-dimensional (3D) flame chemiluminescence field to obtain information about the spatial characteristics of the flame. However, additional information is needed to solve the ill-posed inverse problem of the CTC due to the constraints such as economy of CTC system and the number of views. In this study, a PR-SART algorithm is proposed for 3D flame reconstruction by combining the flame outer contour pre-reconstruction model with the simultaneous algebraic reconstruction technique (SART). The influence of the number of pre-reconstruction iterations is analyzed in numerical studies. The reconstruction performance of the SART algorithm is compared with the PR-SART algorithm for two flame structures under various numbers of views and noise conditions. Finally, an OH* chemiluminescence imaging system consisting of 8 ultraviolet (UV) cameras is developed, and evaluated through use of reconstructing the 3D structure of low-swirl flames. Numerical and experimental studies indicate that the proposed algorithm and CTC system are effectively capable of removing the reconstruction error in the flame-free region, improving the reconstruction quality, and reducing the computational cost.

The purpose of the existing research is to analyze the luminescence behavior on a set of different co-formers involved Dy³⁺ ions activated Barium comprised zinc borate glasses fabricated through the utilization of usual melt quenching technique with a glass composition of 64B₂O₃+20ZnF₂+15BaO+1Dy₂O₃ & 44B₂O₃+20A+20ZnF₂+15BaO+1Dy₂O₃ (where A = 0, P₂O₅, TeO₂, Bi₂O₃). Their structural, optical, luminescence and decay behavior were scrutinized by several respective characterization techniques. Some of the physical properties were calculated by utilizing the corresponding formulae. Besides, the bonding parameter and oscillator strength estimation alongside Judd-Ofelt parameter are also computed to find out the radiative properties from luminescence spectra. From these analyses, ionic nature of the glass network was confirmed. The spectroscopic intensity parameter follows the tendency Ω₂>Ω₆>Ω₄. This higher value of Ω₂ is owing to the larger oscillator strength value and signalizing that Dy³⁺ ions are completely doped into the glass network. Among all the as- quenched samples, BZfBaT:Dy glass possesses high stimulated emission cross-section and holds high optical gain width value which implies that the glass is a perfect candidate intended for laser utilization. By utilizing its emission spectra, the colour chromaticity coordinates (x, y), colour purity, colour correlated temperature (CCT), and Y/B intensity ratio were investigated by means of CIE 1931 diagram and confirmed the light emitting capability. Decay curve displays well-fitting with the exponential fit and the efficiency (ɳ) for the BZfBaP:Dy glass is found to be 61 % and possesses high optical gain signalizing that the material is a perfect choice for optoelectronic applications.

In this comprehensive review, we delve into super-resolution optical imaging techniques and their diverse applications. Our primary focus is on linear optics super-resolution methods, encompassing a wide array of concepts ranging from time multiplexing, ptychography, and deep learning-based microscopy to compressive sensing and random phase encoding techniques. Additionally, we explore compressed sensing, non-spatial resolution improvement, and sparsity-based geometric super-resolution. Furthermore, we investigate various methods based on field of view, wavelength, coherence, polarization, gray level, and code division multiplexing, as well as localization microscopy. Our review extends to stimulated emission depletion microscopy via pump-probe super-resolution techniques, providing a detailed analysis of their working applications. We then shift our attention to near-field scanning optical microscopy, discussing its principles and applications in various fields. Recent techniques such as Microsphere-assisted microscopy, Airyscan, mean-shift super-resolution, photothermal relaxation localization microscopy, and a novel structured illumination-based super-resolution technique enables tomography of semi-transparent samples by investigating their refractive index thus providing a 3D map of the samples. Moreover, we examine the concept of super-resolution in a nonlinear medium, highlighting its unique characteristics and potential benefits. Finally, we discuss the future perspectives and trends of super-resolution optical imaging, offering insights into its potential evolution and impact on the field.

To improve the performance of 3D light field display(LFD) devices and optimize their display effects, a depth-of-field (DOF) enhancement in LFD based on fusion of voxel information on the depth plane is proposed. In previous research, a calculation method was developed to calculate the voxel size on the depth plane. According to this calculation method, a distribution model of voxel varying with display depth is established. A DOF determination criterion based on voxel distribution from visual perspective is proposed, and its accuracy is validated through subjective experiments involving multiple participants. By fusing the voxels on the depth plane, the phenomenon of voxel overlap is improved, resulting in enhanced definition of 3D images on the depth plane. Under the condition that the structure and parameters of the 3D LFD device are determined, the maximum achievable display depth will be increased significantly. Finally, experimental validation of the method's feasibility is conducted using multiple 3D light field devices for display.

Wavelength-coded spectral imaging represents a fusion of spectral imaging and compressed sensing, offering advantages such as reduced storage requirements and straightforward miniaturization. This approach employs optical filters for hyperspectral reconstruction. However, issues like insufficient energy and excessive noise arise in low-light detection, leading to a notable degradation of image reconstruction quality. This paper presents a robust segmented reconstruction algorithm named MCC-WSCI (Multi-Channel Clustering-based Wavelength-Coded Spectral Imaging), designed to enhance the method's tolerance to noise. This algorithm can accurately classify and process compressed images obtained by wavelength-coded spectral imaging systems, thus improving reconstruction quality significantly. Numerical simulations and experiments in low-light scenarios are carried out to verify the proposed method. Results show that the MCC-WSCI method is robust to different noise and sampling rates and outperforms other state-of-the-art compressed sensing reconstruction methods in terms of reconstructed spatial resolution and spectral resolution. The proposed method provides effective experimental robustness to wavelength-coded spectral imaging with a natural algorithmic extension, paving the way for its application in remote sensing.