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Chen X.,China Jiliang University | Wang D.,China Jiliang University | Xu Y.,China Jiliang University | Kong M.,China Jiliang University | And 4 more authors.
Guangxue Xuebao/Acta Optica Sinica | Year: 2015

Based on the fiber with sub-wavelength aperture, the point-diffraction wavefront with both high numerical aperture (NA) and high power is obtained, by which the poor light power of pinhole point diffraction wavefront and the small aperture angle of single-mode fiber point diffraction wavefront can be solved. We analyze the point-diffraction wavefront based on the finite difference time domain (FDTD) method, and the effects of various factors such as aperture, cone angle, film thickness of sub-wavelength-aperture fiber and NA on pointdiffraction wavefront error, aperture angle, light transmittance and intensity uniformity are discussed in detail. The simulation results show that an aperture angle about 90° and light transmittance about 29% can be obtained with 0.5 mm sub-wavelength fiber aperture, and the corresponding testing precision is better than root mean square value 0.0011λ within 0.60 NA. The simulation demonstrates the feasibility of high NA and high power of point-diffraction wavefront, and provides theoretical basis for choosing the dimension of sub-wavelength-aperture fiber in practical system design. ©, 2015, Chinese Optical Society. All right reserved. Source


Wang D.,China Jiliang University | Wang D.,China University of Technology | Chen X.,China Jiliang University | Xu Y.,China Jiliang University | And 6 more authors.
Precision Engineering | Year: 2015

Abstract The stage error of coordinate measuring machines (CMM) can significantly influence the measurement results, and it places ultra-high requirement on the measurement and calibration tools. A calibration technique based on self-calibration algorithm is presented to calibrate the two-dimensional stage error of CMM, and it can be carried out with a grid plate of the accuracy no higher than test stage. With the proposed self-calibration algorithm based on least squares method, the measurements at various position combinations of rotation and translation are carried out to separate the stage error from measurement results. Both the accuracy and feasibility of the proposed calibration method have been demonstrated by computer simulation and experiments, and the measurement accuracy RMS better than 1 μm is achieved. The proposed calibration method has a good anti-noise ability and provides a feasible way to lower the accuracy requirement on standard parts. It is of great practicality for high-accuracy calibration of the stage error of CMM and manufacturing machines in the order of submicron. © 2015 Elsevier Inc. All rights reserved. Source


Wu J.,Guilin University of Electronic Technology | Wu J.,Guangxi Colleges and Universities Key Laboratory of Optoelectronic Information Processing | Rao Y.,Guilin University of Electronic Technology | Hu Y.,Guilin University of Electronic Technology | And 3 more authors.
Yaogan Xuebao/Journal of Remote Sensing | Year: 2016

This paper presents our research on registering single aerial image to a LiDAR point cloud. Given its high spatial resolution, spatial positioning accuracy, and efficiency in capturing data of physical surfaces, LiDAR has been influenced by and has significantly changed photogrammetry. The fusion of LiDAR data with aerial images offers various applications, such as DOM generation, virtual reality, city modeling, and military training, because of the complementary nature of the information provided by the two systems. However, the two datasets should be geo-registered into a common coordinate frame prior to such integration, which proves to be quite challenging in terms of either automation or accuracy. Such a challenge may be partly caused by inefficiency in the feature measurement or detection stage. For example, the identification of point of interest or straight line feature is viable and reliable in optical images but is difficult to achieve in LiDAR point clouds because of its poor discontinuity measurements. To this end, an automatic geo-registration approach based on “pin-hole” imaging simulation and iterative gradient mutual information computation is proposed to align single aerial image to discrete LiDAR point clouds. The proposed approach takes photogrammetry collinear equation as strict mathematic mode and involves three stages. First, a virtual “pin-hole” imaging process restored from aerial image orientation parameters is established on urban LiDAR point clouds to generate simulated, gray, LiDAR-depth images. The generated LiDAR-depth images are geometrically similar to aerial images. Hence, difficulties in registration caused by distinct differences in spatial resolution, perspective distortion, and size between the two types of data sources can be greatly alleviated. Second, the geometric transform parameters between LiDAR depth images and aerial images are successfully estimated with the gradient mutual information as the similarity measurement. Moreover, the image pyramid partitioning strategy is implemented to accelerate the search for parameter space. In this stage, LiDAR laser feet points can be roughly mapped on aerial image pixels on the basis of the estimated geometric transform parameters and the known projection relations between LiDAR point clouds and their depth images. Third, the photogrammetry space resection algorithm is implemented using all the mapped aerial image pixels as observed values and their gradient mutual information as weight to improve image orientation parameters. The three stages are repeated until the given iterative calculation condition is met and the LiDAR point clouds are registered with single aerial image. Selected airborne LiDAR data and an aerial image with different initial parameter values are tested with the proposed approach. Approximately 0.5 pixel is obtained, indicating a higher registration precision compared with the ICP algorithm. (1) The “pin-hole” simulation imaging and iterative gradient mutual information calculation successfully resolve the difficult heterologous correspondence problem between LiDAR point clouds and optical aerial images; (2) The photogrammetry space resection algorithm can obtain registration parameters with minimum projection errors and reliable precision evaluation by maximizing the use of intensive space information from LiDAR data and recovering optical bundles of laser beams directly. © 2016, Science Press. All right reserved. Source


Du L.,Guilin University of Electronic Technology | Du L.,Tianjin University | Li Q.,Tianjin University | Li S.,Tianjin University | And 8 more authors.
He Jishu/Nuclear Techniques | Year: 2015

Graphene, a two-dimensional layer of carbon atoms forming a honeycomb crystal lattice, has attracted much attention for its extraordinary carrier transport properties. The unique electronic structure of graphene gives rise to massless charge carriers and ballistic transport on a submicron scale at room temperature. The tunable electrical properties realized by raising or lowering the Fermi level, allow excellent tunability of electromagnetic structures made of this material. We used terahertz time-domain analysis of the composite structure. Here we demonstrate a significant amplitude modulation of THz waves with gated graphene by using extraordinary transmission through the graphene layer placed right above N-silicon substrate in the blue-violet laser of continuous irradiation. However, the reflection modulation of THz waves is weak monotonic. We employ the carrier transport properties of the graphene and the transport properties of the Schottky junction to analyze a graphene-silicon hybrid structure's strange transmission reasonably. © 2015, Science Press. All right reserved. Source


Nie J.-Y.,Guilin University of Electronic Technology | Nie J.-Y.,Guangxi Colleges and Universities Key Laboratory of Optoelectronic Information Processing | Zhang W.-T.,Guilin University of Electronic Technology | Zhang W.-T.,Guangxi Colleges and Universities Key Laboratory of Optoelectronic Information Processing | And 7 more authors.
Guangzi Xuebao/Acta Photonica Sinica | Year: 2016

An approach for recognition of transgenic soybeans was proposed based on spectral analysis in the terahertz (THz) range combing with Principle Component Analysis (PCA) and Back Propagation Neural (BPN) network. Eight principal component factors, whose accumulated variance reached 97.582%, were extracted from the original spectra data and then fed as inputs into the BPN network model. The utilization of the dimension-reduced data in training the network model can recognize the validation set accurately. The nondestructive testing of transgenic soybeans could be achieved by using THz spectroscopy, which could be widely applied in agricultural security areas. © 2016, Science Press. All right reserved. Source

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