Herein, global sensitivity analysis is performed to analyze the numerical model of the thermal blooming distortion parameter (ND) with 113 uncertain input factors in typical transmission scenarios. First, the elementary effect test ranks factors in order of their importance and screens insensitive factors. Next, variance-based sensitivity analysis quantifies the sensitivity of the important factors and investigates the interactions between factors. Our results reveal that the atmospheric characteristics in the propagation path’s first few kilometers affect ND the most. These characteristics can either affect ND alone as well as with other factors. The most important parameters are atmospheric absorption coefficients at low attitude. These findings can guide the measurement and model construction of atmospheric parameters.

This study simulated the aero-optical effect of beams with different projection directions around turrets with different radii (400 mm and 2000 mm). The Mach number was fixed, and the Reynolds number remained similar in all cases. The space-time characteristic of the beam quality factor and beam tilt angle caused by the aero-optical effect was comprehensively studied. The aero-optical effect was mainly determined based on the mean flow effect, and the characteristic frequency of the mean flow effect was determined based on that of the flow around the turret. The spatial characteristic of the aero-optical effect was accurately reproduced in the reduced-scale experiments; however, the temporal characteristic was poorly simulated. The aero-optical effect appeared to be minimized at a projection direction of 40° zenith in the forward direction. An increase in the projection radius resulted in an increase in the mean flow effect while maintaining the turbulent effect almost constant.

The initial model of optical concealed depth (OCD) was established under the assumption of uniform optical properties of seawater, which had limited applications. Nonetheless, we developed a new model that views seawater as a non-uniform layered entity. Based on the contrast transfer equation, seawater was divided vertically into different areas, and each vertical division had multiple properties similar to the properties of homogeneous water. Subsequently, the new model of optical concealment depth for layered water(OCD_LAYER)was established. The observation zenith angle, attenuation coefficient of seawater, and surface reflectance of submarines were calculated and analyzed accordingly. The verification test and the effect analysis of the model were performed based on the latent model and measurement systems. As a result, the mean value of the diffusion attenuation coefficient is found to be 3 m. In the OCD model, the average root mean square error is 1.19 m, the average absolute error is 1.19 m, and the average relative error is 48.77%. Meanwhile, the OCD_LAYER model displays a better estimation system, as indicates by lower errors; the average root mean square error is 1.05 m, the average absolute error is 0.89 m, and the average relative error is 36.18%. The experimental results show that the proposed model demonstrates higher accuracy and provides more reliable results than the initial model.

The distribution of forward small-angle scattering radiation is related to the particle size and optical thickness of the scattering medium. The forward small-angle scattering ratio, atmospheric optical thickness τ and the Angstrom index α of aerosol particles are measured based on a new type of variable field photometer under different weather conditions. The results are compared with the results of DISORT simulation. It is shown that the scattering ratio increases with increasing of optical thickness. However, when the optical thickness is less than 1, the scattering ratio would depend on the effective scale of the particle. The larger the particle, the smaller the scattering ratio. When the size of cirrus ice crystal is larger (De>10 μm ), the scattering ratio is smaller than that of aerosol particles and water clouds. This provides a new method to distinguish thin cirrus clouds with aerosols. A simple method for extracting optical thickness of cirrus clouds is presented. It is proved that the extinction coefficient of cirrus clouds is independent of wavelength in short wavelength band. The research provides a certain reference for ground based detection on atmospheric properties.

On the basis of the quenching effect of oxygen on the material fluorescence, we developed an analytical method based on time-domain fluorescence lifetime to detect the concentration of dissolved oxygen in water. The fluorescence lifetime is calculated according to two points on the fluorescence quenching curve, and the dissolved oxygen concentration in water is then obtained by the inversion of Stern-Volmer equation. The results showed that under the same dissolved oxygen concentration, the normalized fluorescence quenching curve is not affected by the excitation conditions, such as the intensity of the excitation light and the duration of excitation. The measured fluorescence lifetime of different dissolved oxygen concentrations is affected by the system delay. The theoretical curve of the fluorescence lifetime after compensation is in good agreement with the modified curve with the fitting correlation coefficient of 0.9985. Compared with the HQ30d dissolved oxygen analyzer, the measurement error of the dissolved oxygen in the mass concentration range of 0-20 mg·L-1 is less than 0.5 mg·L-1 while the fitting correlation coefficient reach to 0.9992. These results showed that it could be an effective method for the measurement of dissolved oxygen concentration in water.

Coherent manipulation of a two-level quantum system is of great significance for the precision measurement and quantum information processing, such as atomic clock, atomic interferometer and quantum computing. Two-photon Rabi oscillations between hyperfine ground states of rubidium atoms simultaneously driven by microwave and radio frequency (MW-RF) fields are experimentally demonstrated. Based on the calibration of the thermal relaxation process and the measurement of the microwave transition between Zeeman sublevels, the coherent oscillations of the atomic population are distinctly distinguished in the thermal relaxation process. Moreover, the dependence of the generalized Rabi frequency on the intermediate state detuning and the power of the MW/RF fields is measured and analyzed in detail. When the intermediate state detuning is large enough, the experimental results are consistent with the equivalent two-level model. Otherwise, the measured Rabi frequency deviates from the theoretical value due to the population of the intermediate state by few atoms. These achievements provide us powerful theoretical support for the coherent manipulation of two-state quantum systems.

Based on the basic principle of Fourier optics and the pupil configuration of sparse aperture system, the relationship model of the thickness error between the sub-aperture and the diffractive segmented lens is established. The general expression of the phase difference induced by an arbitrary low-order surface shape error is presented under the condition of micro-deformation on one side of the sub-aperture which is without diffraction structure. Taking the spherical deformation as an example, the tolerance range of the surface shape error is discussed and calculated, and the results are verified by the ZEMAX ray tracing method. As for the special case that there is no deformation on both sides of the sub-aperture, the Monte Carlo method is used to investigate the effect of the thickness uniformity among these sub-apertures on the imaging quality of the segmented primary lens and the variance and extreme range of the sub-aperture thickness error are obtained when the coherent imaging is made by the diffractive segmented lens under a normal distribution. According to the theoretical design results, two off-axis diffractive sub-apertures are fabricated and the experiment on the segmented imaging performance of dual sub-apertures is conducted. The experimental results show that the diffractive segmented primary lens can improve the equivalent resolution.

Based on the Fresnel diffraction theory, the intensity distribution of a vortex beam diffracted by a regular hexagonal multi-hole array is investigated and the effects of the structural parameters of this regular hexagonal multi-hole array on the cellular optical field are also analyzed. The research results show that the diffracted field periodically changes with the phase structure and thus a cellular or petal shaped intensity distribution can be obtained. The radius of the circular hole has an effect on the diffracted field range and the side length of the regular hexagon has influences on the width and the separation distance of the diffraction fringes.

Two narrow-linewidth filters, consisting of an ultra-low-reflectivity fiber Bragg grating (LRFBG) and one (or two) 2×2 fiber couplers, are designed for single-longitudinal-mode fiber lasers. The reflectivity expressions of the two filters are deduced theoretically. The characteristics of the two filters, such as reflectivity, narrow linewidth and group delay, are numerically analyzed and experimentally verified. The two fiber filters have the characteristics of high reflectivity, ultra-narrow linewidth, large group delay and good slow-light effect. What’s more, in the case of the double-ring filter, the amplitudes of resonant peaks are modulated because of the Vernier effect. Therefore, the effective free spectral range (FSR) and side mode suppression ratio (SMSR) of the double-ring filter are larger than those of the single-ring filter, which means the double-ring filter is hardly mode hopping. Because of the advantages of narrow linewidth, compact structure and low cost, both of the designed filters can be used for fiber laser as the cavity mirror to narrow the linewidth of laser further. And the results show the linewidth of the laser with double-ring filter is narrower than that of the laser with single-ring filter.

Photonic crystal fibers have attracted intensive attention because of its advantages of a freedom design and a novel light guiding mechanism. Compared with photonic bandgap fibers and Kagome fibers, the hollow-core anti-resonant fibers (HC-ARF) exhibit excellent optical properties in terms of simple structure, single mode transmission, broad transmission bandwidth and low optical attenuation. HC-ARF is suitable for UV/mid-IR light transmission, high power laser generation, nonlinear optics, sensing and so on. However, in order for HC-ARF to be widely used, the fusion of HC-ARF and a conventional single-mode fiber must be simple and low-loss. While, because the special cladding capillaries of HC-ARF are easily destroyed during splicing, and the mode field of HC-ARF is different with single mode fiber, the direct splicing technique easily leads to a large loss. So we use a solid-core large mode area fiber with a core diameter of 20 μm as an intermediate, to obtain a low-loss fusion splice between a HC-ARF and a conventional single mode fiber. Compared to the direct splicing technique, which yields a splice loss of 3 dB, the intermediate fiber technique makes the overall insertion loss decrease to 0.844 dB.

We propose a new type Fabry-Perot cavity based on dynamic grating in Er-doped fiber and fiber Bragg grating. The dynamic grating model is established through two-level system of Er-doped fiber. We calculate the reflection and transmission of the dynamic grating and the Fabry-Perot cavity based on semi-classical interactional theory and transfer matrix method, and analyze the influence of some parameters on reflection spectra of the dynamic grating and Fabry-Perot cavity. An important feature of the proposed Fabry-Perot cavity is that its output spectra can be dynamically tunable by parameters modulation, in which the parameters include Rabi frequency of the coherent probe field in the dynamic grating, the length of the Er-doped fiber, the refractive index modulation depth of the fiber Bragg grating, the cavity length of the Fabry-Perot cavity and so on. Compared with the Fabry-Perot cavity based on two fiber Bragg gratings with fixed parameters, the proposed Fabry-Perot cavity is more flexible, and is more beneficial for mode selection. It can overcome the asymmetrical drawback of the two fiber Bragg gratings in Fabry-Perot cavity (such as different Bragg wavelengths, refractive index modulation depths of Bragg grating). The proposed Fabry-Perot cavity has potential applications in fiber-optic communication and fiber sensors.

Impact localization can provide accurate location information for structural impact damages. As fiber Bragg grating has low sampling frequency and requires training samples, a method for structural impact localization based on optical fiber Sagnac sensing technique is proposed. The sensing system mainly consists of broadband light source, optical fiber Sagnac interferometers, photo-detectors and data acquisition card. The phase of the interferometer can be modulated when the sensing probe stuck on structure is affected by impact stress waves. Therefore, the output light intensity can be changed and converted to voltage signal by photo-detector. Firstly, the impact response signals are de-noised and direct current interferences are eliminated by wavelet transform. Secondly, the energy characteristics are extracted, time-domain signals are reconstructed by wavelet packet analysis, and the time of wavelet arrival to the two sensors is acquired. Lastly, impact position is calculated by time-difference method. The result shows that 35 impacts on the steel pipe with the length of 100 cm have a maximum error of 0.65 cm, and a maximum root-mean-square error of 0.36 cm, respectively. This research can provide a novel and available method for structural impact localization.

We propose a nanofilm-modified grating biosensor that is able to detect low-concentration antigen biomolecules in order to find a solution for the insensitivity problem of the long-period fiber gratings (LPFGs) when used as refractive index sensors to detect low-concentration solutions. The experimental results show that the sensitivity of this biosensor is significantly improved. When the concentration of goat anti-rabbit IgG is fixed to 0.01 mg·mL-1, the peak loss of the LPFG of the film indicates a significant response to the increase in rabbit IgG concentrations. Herein, the concentration is defined as a mass concentration. The biosensors successfully achieve concentration sensitivities of 2101.5, 1306.5, and 575.9 dB·mg-1·mL measured at 445, 460, and 500 μm, respectively. Furthermore, the concentration of the antigen is related to the peak loss of the grating. The lowest detectable concentration of the rabbit IgG is 0.0003125 mg·mL-1. Given the high sensitivity, free labeling, high stability, simple structure, and immunity from the electromagnetic interference, the sensor promises an excellent application prospect in the biosensing field.

A PbS quantum-dot-doped fiber amplifier (QDFA) is realized experimentally in NIR S-C-L ultra-broad waveband and with low noise. Taking UV-gel as the optical fiber background and PbS quantum dots (QDs) as the gain medium in the fiber, we setup a full-light path structure composed of a 973 nm pumping single mode laser, an isolator, a wavelength division multiplexing and a quantum-dot-doped fiber. The broadband signal light with the range of 1470-1620 nm is amplified in an all-optical structure. There is evidence to show that the QDFA has 75 nm bandwidth around the wavelength region of 1550 nm with the switch gain of 16 dB-19 dB (the net gain of 12.26 dB-15.26 dB) for the input signal power of -23 dBm and the noise figure of about 3 dB. An obvious excitation threshold and gain saturation phenomenon are observed by the experiment. A linear relationship is determined between QD doping concentrations and fiber length. The obtained performances in the bandwidth, C-waveband gain flatness and noise figure of QDFA in this paper are better than those of the conventional erbium-doped fiber amplifiers (EDFAs), while the L-waveband gain flatness is a little lower than that of the optimized EDFAs.

In view of the disadvantages of the indoor visible light three-dimensional positioning system, such as complex calculation and low precision, we propose an indoor visible high precision three-dimensional positioning system based on immune algorithm. The immune algorithm, which is designed according to the biological immune system, is an intelligent algorithm with global optimization ability. The immune algorithm can be used to solve the global optimization problem. In the visible light communication (VLC)-based indoor positioning, it can be transformed into a global optimization problem. Therefore, in the three-dimensional indoor positioning, the best receiver coordinates can be obtained through the immune algorithm. However, owing to the system noise and the imperfection of device used in the system, distance between receiver and transmitters deviates from the real value, and results in positioning error. By introducing the error correction factors into the immune algorithm, we can precisely determine the coordinates of the receiver in three-dimensional space. The simulation result shows that the average distance error is 0.69 cm within 80 iterations in an indoor environment of 3 m×3 m×4 m. The average positioning error of the multi-point positioning test is 2.13 cm. The extended experiment in motion scene positioning also shows that 96.04% positioning errors of the proposed method are below 1.7 cm, which is superior to that of other existing methods for three-dimensional visible light indoor positioning. Therefore, the indoor visible three-dimensional positioning system based on the immune algorithm can achieve high-precision positioning services, and have potential application in various indoor positioning scenes.

To meet the requirements for the rapid, on-site and high-sensitivity detection of mercury ions (Hg2+) existing as the environmental heavy metal pollutant, we have independently developed an all-fiber sensor for Hg2+ detection based on the fluorescent quenching of quantum dots and optical fiber evanescent wave sensing. It is mainly composed of an optical fiber probe module, an optical module and a signal processing module, which realizes the excitation and collection of fluorescent signal and the processing and acquisition of photoelectric signal. The experimental results show that the detection limit of the sensor for Hg2+ reaches 1 nmol/L. Moreover, the fluorescent quenching rate of quantum dots varies linearly with the logarithm of the Hg2+ concentration in the range of 1 nmol/L to 500 nmol/L, and the linear correlation coefficient is 0.9867. Meanwhile, the ion anti-interference experiment confirms that the sensor has good selective recognition for Hg2+ detection. The sensor is also applied to the environmental water sample detection with the recovery of 90.1%-97.3%. The sensor system not only has high sensitivity and fast response speed, but also can realize remote detection and real-time monitoring. It is also conducive to the integration and miniaturization of the instrument. Therefore, it has a broad application prospect in the detection of heavy metal ion pollution.

Aiming at the problems that the stacked sparse denoising auto-encoder(SSDA) is difficult to train on image denoising, such as slow convergence rate and poor universality, an adaptive image denoising model based on stacked rectified denoising auto-encoder is proposed. The rectified linear units is used as a network activation function to alleviate the phenomenon of gradient dispersion. Joint training with the residual learning and batch normalization to accelerate convergence speed. In order to solve the problem of noise poor universality of the new model, it is necessary to carry out the multi-channel parallel training, and make full use of the potential data feature extracted by the network to find the optimal channel weights, and learn to predict optimal column weights via training weight prediction model for realizing adaptive image denoising. The experimental results show that the proposed algorithm is not only better than the SSDA in the convergence effect, but also adaptively processing the non-participating training noise, and has better universality, compared with the current methods of BM3D and SSDA.

The depth map obtained directly is limited by the disadvantages such as low resolution and missing edge information, it greatly affects the application of depth map. In order to solve this problem, a two-channel convolutional neural network for depth map super-resolution is proposed. It consists of two channels, deep and shallow, and there are 21 layers in the deep network. Through joint convolution and deconvolution, combining skip connection and multi-scale theory, the deep channels can quickly learn the detailed features of depth map. Shallow network of 3 layers are used to learn the rough features of depth maps. Finally, the two channels are combined with details and outlines to realize end-to-end mapping from low resolution depth map to high resolution one. The model makes full use of the learning ability of the convolutional neural network to independently extract the effective features of the depth map and avoid the inaccuracy of manually extracting features. The experimental results on the Middlebury RGBD dataset show that the proposed model can achieve good results at a large sampling factor of 8, and has a high practical value.

The traditional blind image deblurring algorithm based on the statistical prior models has the disadvantages of sensitivity to noise and limited detail recovery, while the learning-based image deblurring algorithm has poor adaptability for blurring kernel and noise level. To address the above problems, we propose a simple and effective low pixel sparse prior based on the statistical differences between the histograms of original and blurred images first. Then, in order to remove the noises and artifacts in restored image, a deep convolution neural network is designed to learn image denoising prior, which combines low pixel sparse prior and gradient sparse prior to form a new image deblurring model. Meanwhile, we estimate the blurring kernel in the structure layer so as to get a more accurate one, and the structure layer can be obtained by the image decomposition method. Numerous experimental results show that the proposed algorithm can restore more image details, and show more robustness to image type, blurring kernel type and noise level. The proposed method outperforms other recent state-of-the-art related approaches.

In order to solve the problem of face image retrieval in the field of computer vision, a face image retrieval method based on the deep features is proposed. Firstly, the convolutional neural network model is trained for face classification by face image training data set. Based on this, the triplet loss method is used to fine-tuning the trained face classification network model so that the network can be more efficient to extract face features of different people and construct efficient feature vectors for preliminary face retrieval filtering stage. In order to further improve the performance of system retrieval, the one-stage query expansion method is proposed to reconstruct the eigenvectors of face images to be retrieved. Through exhaustive experimental verification on two public face datasets (CASIA-3D FaceV1 and Labeled Faces in the Wild dataset), the results show that the face image retrieval method based on deep features improves the accuracy of the retrieval results significantly. Moreover, this method is simple and reliable, and can quickly realize the task of face retrieval.

To improve the registration efficiency and accuracy of three-dimensional laser scanning point cloud, we propose a point cloud registration algorithm based on l p space mechanics model. In the algorithm, the center of gravity of the sets data is calculated first, and two point clouds are moved to the same coordinate system with the center as the origin through gravity-centralizing. The complex point sets to be registered are represented as three eigenvectors respectively with the space mechanics model. Then, the singular value decomposition method is used to solve the rigid body transformation rotation matrix according to the corresponding relationship between two point sets’ eigenvectors. Finally, with the initial registration result, the improved iterative closest point (ICP) algorithm leads to perfect registration. The proposed algorithm can deal with disordered and scattered cloud sample. Compared with the classic ICP algorithm, the proposed method increases efficiency by 72% for the Bunny point cloud and is 4 times faster for Dragon scanning data. Experimental results indicate that the proposed algorithm has a fast convergence rate and good effect.

Nighttime hazy image usually has the non-uniform illumination, low contrast and serious color deviation. The existing dehazing methods are mainly proposed for daytime images, which don't fit well with the conditions of most nighttime hazy scenes. Nighttime image dehazing is more difficult. We explore the imaging characteristics under nighttime conditions and propose a new nighttime image dehazing method based on low-pass filtering and joint optimization of multi-feature. Firstly, in order to handle the non-uniform illumination of nighttime scenes, the image is filtered by the low-pass filtering. And then the minimum-maximum filtering is applied to the low frequency components to estimate the local atmospheric light. Secondly, for the current daytime dehazing algorithm prior is not suitable for nighttime image, an effective transmission estimation method is presented based on the joint optimization of multi-feature which combines contrast, saturation and information entropy. Finally, for the non-uniform color deviation exists in nighttime images, the non-overlapping blocking local Shade of Gray is proposed. Experimental results demonstrate that the proposed algorithm has a good subjective visual effect, and the objective evaluation indexes are superior to other algorithms in contrast and color deviation degree. The proposed algorithm can significantly remove haze, improve the contrast and recover more details with the natural color and better visual effect.

Chirped-amplitude-modulated (CAM) laser ghost imaging (GI) is a novel imaging mechanism that combines the principle of correlated imaging with pulse-compression. It can acquire the direction, grayscale, range and velocity of the target, and can effectively reduce the influence of the background noise on imaging quality. At present, the theoretical model and simulation verification of chirped-amplitude laser correlation imaging are preliminarily established. However, the influence of laser source modulation performance is not involved. For this reason, the influence of modulation performance on imaging quality of non-coherent heterodyne CAM GI is deduced and numerically analyzed. The relationships among initial modulation depth, modulation depth decay coefficient, frequency change ratio and bandwidth of photodiode on detection signal to noise ratio and imaging performance of heterodyne GI are obtained. This work has guiding significance for the future design and performance assessment of CAM GI lidar system.

The forward small-angle solar transmittance ratio is more sensitive to ice crystal particles in cirrus clouds compared with aerosol particles. A photometer, named VFOVSP, is developed based on image tracking and automatic fast changing field of view, which can quickly measure transmitted radiation from narrow field of view to wide field of view of the sun. It provides a new technology for ground-based measurement of cirrus. The system composition and measurement principle of the instrument are introduced. In the atmosphere non-absorption band,after the instrument is calibrated with Langley method,the VFOVSP measurement results are compared with the measurement results of POMO2 photometer to verify the reliability of the instrument measurement accuracy. Under different weather conditions, the experimental results show that the transmission ratio at different small angle fields of view is related to the type of particles, which makes it possible to distinguish thin cirrus clouds and aerosol particles. The instrument makes up for the lack of real-time and single-field detection of traditional solar photometers in cloudy weather. It can better identify whether there is cirrus under the current atmosphere and meet actual scientific research needs.

There are obvious moiré fringes and crosstalk in the stereo images of a naked-eye 3D light-emitting diode (LED) display based on a conventional vertical parallax barrier and a slant parallax barrier, respectively. To solve these problems, we present a naked-eye 3D LED display based on a parallax barrier with weak moiré fringes. The naked-eye 3D LED display comprises an LED display and a malposed parallax barrier with discrepant slit widths. The proposed parallax barrier can match the LED displays that have a wide black matrix. We properly enlarge the width of the slits and slightly move the slits in their periods. This method can increase the difference between the periodic structures of the parallax barrier and the pixels of the LED display, which reduces the contrast ratio of the moiré fringes and causes them to appear sparsely. In this way, the weakened moiré fringes are not obvious and the crosstalk of the stereo images does not noticeably increase. We develop a prototype of the proposed naked-eye 3D LED display based on the parallax barrier. The prototype had the weakened moiré fringes, and its crosstalk is insignificant. Thus, the validity of our theory is confirmed.

Based on separated asymmetric large optical cavity, the high power pulsed semiconductor lasers with epitaxially-stacked three-active-region structure at laser central wavelength of 905 nm are investigated. We optimize the critical parameters, including near-field optical intensity model, free-carrier absorption loss, the distance between adjacent luminescent regions and the doping levels of each layer, to obtain higher peak output power, lower internal optical loss and smaller far-field vertical divergence angle. A three-active-region high power semiconductor laser with 1 mm cavity length and 100 μm stripe width is developed. We achieve a peak output power of 122 W driven by 34.5 A pulse current intensity at 150 ns pulse width and 6.67 kHz repetition rate. Slope efficiency of 3.54 W/A, equivalent internal quantum efficiency of 91.75% and internal optical loss of 2.05 cm -1 for each emitter are obtained, and far-field divergence angles of 7.8° and 27.6° (full width at half maximum) are achieved in the lateral and vertical directions, respectively.

H62 brass is subjected to laser shock peening (LSP) with one coverage layer and three coverage layers by high-energy laser beam. Varieties of micro-structure, micro-hardness, and surface roughness before and after LSP are investigated. It is found that the grain size of H62 brass is obviously refined with LSP, and a nanostructure layer is obtained. The micro-hardness and surface roughness of H62 brass increase with the increase of number of LSP coverage layers. The friction and wear test of the as-received sample and LSPed samples (samples subjected to LSP) is carried out by UMT-2 friction and wear test machine. The differences of friction coefficient, wear rate, and wear scar morphology in these samples are analyzed. It is found that under the same friction condition, the friction coefficient and wear rate of LSPed samples are smaller than the as-received sample, which become much smaller with the LSP coverage layers increasing from one to three. It is indicated that LSP can improve the wear resistance of H62 brass, and multi-layer LSP has a better effect on the improvement of the wear resistance of H62 brass. After LSP, the wear mechanism is changed from domination with delamination wear to abrasive wear.

Transmission characteristics of smoothed beam spots near the focal plane were investigated under the influence of nonlinear intensity and phase modulation. Diffraction theory was used to calculate the light field distribution on the defocused surface in three-dimensional space. Spot position drift and intensity symmetry were used to characterize beam spot performance during transmission evolution. The impact of non-linear effects under high-flux laser irradiation on smoothed spot of continuous phase plate was studied. Especially, the small-scale self-focusing intensity modulation difference caused by large difference between the thick and thin ends of wedge lens resulted in gradual deviation of beam spot from the optical axis during the defocusing transmission process, and caused asymmetric bias of intensity distribution. The results show that the effect of nonlinear intensity distortion is far greater than that of phase distortion. Under irradiation with 5 GW/cm2 power density on a given laser device, the spot position offset is more than 0.1 mm on the 4 mm defocused plane, and the asymmetry of light intensity is biased to 30%.

A passively Q-switched Nd∶YAG/Cr 4+∶YAG microchip laser with a low time jitter and a high repetition rate is reported, which uses a single-tube laser diode with a wavelength of 808 nm as the pumping source. Based on the polarization orientation characteristic of a Cr4+∶YAG crystal with a cutting direction of [001] at a certain incident beam power density, the polarized pumping method is chosen to make the polarization direction of the pumping light parallel to the crystallographic axis direction and all of the residual pumping light after absorption by the Nd∶YAG crystal is used for bleaching the electric dipoles along the crystallographic axis direction of the Cr4+∶YAG crystal. The results show that the output pulse time jitter of the Nd∶YAG/Cr4+∶YAG passively Q-switched microchip laser can be effectively reduced with the optimization of the orientation of the Cr4+:YAG crystal with a cutting direction of [001] when the polarized pumping method is adopted.

In order to solve the problems of binocular camera′s optical axis alignment error, low image matching accuracy, and insufficient computing speed in passive binocular ranging systems, a new self-calibrated binocular ranging system based on hardware speeded up robust features (SURF) algorithm is proposed. The scheme uses position sensitive detectors and servo motors as the self-calibrating platform of the binocular cameras, and Zynq SoC is utilized to achieve the hardware acceleration of the SURF algorithm and feature matching of two images. Finally accurate and effective passive ranging is realized. The results show that the position sensitive detector can effectively calibrate the binocular cameras to the same plane position, and the hardware SURF algorithm can match images with high accuracy and speed. The scheme meets the demand of passive ranging systems.

Objecttracking based on correlation filter has become a research hotspot currently. The traditional tracking model trained from circular correlation is sensitive to the pixel arrangement of the target and is difficult to adapt object deformation, but it has good robustness of variety in color of illumination and similar color interference. However, the model based on spatial reliability can adapt to the deformation by establishing the spatial confidence map as the random field constraint of the correlation filter, but it has less robustness for the color change. In order to exert the superiorities of the two tracking methods, the concept of directional reliability is innovative presented and a set of the optimization strategies is proposed to achieve optimal translation estimation of the two tracking models in both the x-axis and y-axis. Comparative results on OTB2013 and OTB2015 show that the method performs favorable against the other state-of-the-art algorithms and can achieve real-time tracking. It has good accuracy and robustness.

In order to improve the real-time and robust performances of the convolutional features for visual tracking, a real-time tracking method of dual model adaptive switching is proposed based on the analysis of different convolution layer features for different object representation capabilities. This method utilizes the feature energy ratio of the object region and searches region to evaluate the features selected from two convolutional layers. The convolution channel whose energy ratio value is greater than the given threshold is selected to train two correlated filter classifiers. Consequently, the object position is predicted by switching correlation filter classifiers using the peak-to-sidelobe ratio of response map adaptively. Finally, the sparse model update strategy is applied to update the classifiers. The proposed algorithm is tested on the standard dataset. The experimental results show that the average distance accuracy of proposed algorithm is 89.3%, which is close to continuous convolution object tracking, and the average tracking speed is 25.8 frame/s, which is 25 times faster than the continuous convolution object tracking algorithm. The overall performance of the proposed algorithm outperforms other tracking methods contrasted in the experiment.

Aiming at the problem of decreasing the recognition efficiency of multi-class Support Vector Machines (SVM) in the detection and classification of lane arrow markings, an improved method for a simple SVM classifier which is applied to realize the multi classification of arrow markings by custom binary encoding for results is proposed. The Harris corner coarseness is detected for the arrow markings region of interest (ROI), and the pseudo corners are screened by improved FAST-9 (features from accelerated segment test-9) algorithm. According to the location of the largest two corners of the ordinate in the final corner set, the recognition area is obtained. The SVM classifier is trained by invariant moments. And the multi classification with one SVM classifier is realized via the binary encoding for results. The algorithm is tested on 500 real images obtained from the real shot, and the recognition rate is superior to 96.8%. The results show that the proposed method does not need inverse perspective transformation. A simple SVM classifier can realize the multi classification of arrow markings, and the accuracy and operation efficiency of arrow marking recognition can be improved effectively.

With a widely available clinical radionuclide probe, Cerenkov luminescence imaging becomes one of the hot research topics in the field of optical molecular imaging. However, a large number of pulse noises on Cerenkov luminescence image, which are produced during the decay of radionuclide, seriously affect the following researches based on Cerenkov luminescence images, such as quantitative analysis, 3D reconstruction and so on. To suppress these pulse noises, we propose a denoising algorithm based on fuzzy local information C-means clustering algorithm and total variation model. The numerical simulation experiment, physical phantom experiment and animal experiment demonstrate that compared to the common used median filter algorithm, the proposed algorithm can remove the impulse noised effectively with the ability of maintaining the shape of Cerenkov Luminescence source.

By analyzing a speckle noise model of optical coherence tomography (OCT) in clinical medical imaging,we propose a despeckling method for OCT images based on the local grouping principal component analysis. On the basis of the statistical characteristics of coherent images, the multiplicative noise is converted into additive noise by homomorphic filtering. By modeling pixel to be processed in the training set and its neighborhoods as a vector, we group the vectors based on the block similarity measure. Then, the principal component analysis is performed. Considering the noise interference in coherent images with the lesion, we perform the algorithm twice. Experimental results show that the proposed algorithm has better results in terms of speckle noise reduction as well as detail preservation, and satisfying objective evaluation index.

Fluorescence molecular tomography (FMT) is a hot research topic in molecular imaging applied to precision medicine. Due to the seriously ill posed FMT inverse problem, background fluorescence noise often degrades FMT reconstruction results greatly. After analyzing FMT reconstruction methods based on the finite element method, we propose a method for suppressing background fluorescence using low rank matrix completion technology. The proposed method builds an incomplete boundary observation matrix which columns correspond to different excitation sources. Then, a low rank matrix completion algorithm is employed to complete the matrix and suppress the background fluorescence. At last, a new FMT inverse problem is formed by the denoised boundary observation matrix, with which the fluorescent targets are reconstructed. The new FMT inverse problem is applied to reconstruct single and double fluorescent targets, numerical experiments illustrate that the reconstruction results are improved greatly.

The nonlinear propagation of a probe pulse in a M-type five-level atomic system is investigated under the condition of electromagnetically induced transparency. As for a long probe pulse, its dispersion effect can be neglected, and the four-wave mixing process and the energy exchange can occur among the four components within the probe pulse with different polarization directions and different side-bands. In contrast, as for a short probe pulse, the dispersion effect must be considered, and a novel kind of four-component ultraslow optical soliton occurs among these four components. In addition, the input power for the generation of such soliton is at micro-watt level, which is much lower than that needed for the generation of the vector solitons in fibers.

One kind of 13 mega-pixel and super-wide-angle mobile phone camera is designed based on concentric lens and the parameters of the mobile phone camera that meet the industrial production requirements are obtained. This camera is composed of 4 concentric lenses with a focal length of 3.3 mm, a F-number of 1.83, a field of view (FOV) of 100°, and a total length of 5.18 mm. The research results show that, at the Nyquist frequency of 223 lp·mm -1, the modulation transfer function (MTF) value is larger than 0.58 in the 0.7 FOV and that in the whole FOV is larger than 0.50. At 446 lp·mm-1, the MTF value is larger than 0.30 in the 0.7 FOV and that in the whole FOV is larger than 0.17. The root-mean-square (RMS) radius of each FOV is less than 2.3 μm and the relative illumination value is larger than 0.65 in the full FOV.

A numerical modeling method for the generation of a Gaussian-type removal (GTR) function is proposed. Based on the idea of the loop integration, a mathematical model for the generation of GTR function by rotating sweep is established. It is clarified that the nozzle height is the key process parameter to determine the GTR function profile and the validity of this model is also verified. Under the guidance of this model, the nozzle height range for the generation of GTR function and the change law of GTR function profiles are further investigated, and it is found that the removal function obtained when the gyration center coincides with the deepest point of a removal function with a fixed oblique incidence is the closest to an ideal GTR function, which provides a theoretical guidance in the optimization of process parameters for the practical fabrication.

In order to make the ship enter port accurately and avoid conflict, we present a water navigation system for assisting ships in entering port based on light-emitting diodes (LED). The system partitions the target water area by three color lights which are flickering in different frequencies. The mariners in the irradiation area can get their position and direction by observing the lights color and frequency. The system can aid the ships enter port more quickly and accurately. In order to achieve this navigation system, we propose a high-power LED optical system. The LED light beam becomes rectangular through the rectangular concentrator and the linear Fresnel lens. A circuit control system is designed to control the flicker of the light source. The modulation of the flicker frequency of the light source is realized through a single chip microcomputer, a digital analog converter and an operational amplifier. The prototype is made according to the designed system. Experiment is conducted to verify the feasibility of the system on the Mulan Lake. The experimental results show that the fabricated prototype and simulation result of design are in good agreement. The divergence angle of the beam in the horizontal direction is 6°. The proposed water navigation system can partition target waters and assist ships in entering the port well by light colors.

A multi-degree-of-freedom uniformity correction method of the illumination system in a lithography machine is proposed. When the partial coherence factor of the illumination pupil changes, the fine tuning of the whole correction fingers along the direction of the optical axis in the proposed method is enough to make the light illumination uniformity meet the requirements. The effect of the three-dimensional spatial movement of correction fingers on the light illumination uniformity is analyzed by simulation, and the high efficiency of this method is verified.

Transmission properties of light through a double-slit compound grating with different slit widths are investigated with the finite-difference time-domain (FDTD) method. The results show that phase resonance (PR) splitting can be achieved with the slit widths modulation, and it can be simultaneously modulated at multiple frequencies. All modes have sharp PR splittings, and the values of some valleys are almost zero. Secondly, based on the electromagnetic field distribution, Fabry-Perot resonant and phase resonant mechanism, the physical origins of the observations have been qualitatively described and explained. In addition, we can realize the control of light spreading through any slit in two slits, and also achieve the design of bandgap by splitting valley. These results can be used to design optical channel selector, frequency selector, filter and optical switch. Compared with the conventional compound gratings, this double-slit grating with different slit widths has obvious advantages, such as simple structure, single material, and easy realization, design and analysis.

We propose a single baffle metal-dielectric-metal (MDM) waveguide coupled disk cavity structure based on the transmission characteristics and photon local characteristics of the surface plasmonic sub-wavelength structures. Two discrete states are provided by the disk cavity, and a metal baffle is used to produce a continuous state. The discrete states coupled with the continuous state lead to two different modes of Fano resonance. Then, the transmission characteristics of the Fano resonance are analyzed with the coupled mode theory, and the finite element analysis is used to simulate. Moreover, the effects of the structural parameters on the refractive index sensing characteristics are quantitatively analyzed. The results show that, at the first mode, the figure of merit (FOM) and the refractive index sensitivity of the optimized structure can reach to 1.7×105 and 710 nm/RIU, respectively. For the second mode, they can reach to 1.36×105 and 1105 nm/RIU, respectively. The structure can provide a theoretical reference for solving the problem of cross-sensitivity of the sensor in refractive index measurement.

We carry out a visible spectra polarization test to the typical satellite surface materials, and accomplish visible reflect characteristic test based on test data. Then, we deduce the visible reflect polarization transfer model which is based on the polarization bidirectional reflectance distribution function, and evaluate the simulated computation accuracy of the model based on measured data. The results show that the reflected polarization degree of the simulated model is in good agreement with the measured results. And the polarization degree of coating materials used for typical satellite surface is usually minimum at the condition of mirror reflection, but the angle of polarization has the maximum value. That is to say, if the surface compositions of materials are different, the polarization characteristics of the visible light reflection are quite different. It is more helpful to distinguish the material composition of the target by considering the polarization characteristics of the target surface. The research results can provide basic data support for improving the effectiveness of satellite detection.

A scheme of strong coupling between the double electron spins and the quantized nano-mechanical harmonic oscillator is proposed based on the diamond nitrogen vacancy (NV) color center. A two-dimensional entangled state of two qubits is prepared by using the dissipative process of the nano-mechanical harmonic oscillator. The numerical simulation results show that, all the systems with different initial states can evolve to the target states with a high fidelity and a high entanglement. This scheme reduces the influence of the dissipation on the system evolution, has no requirement on the quality factors and reduces the experimental operation difficulty, which is proved to possess strong reliability and feasibility.

A foam-irregular-sea-surface hybrid model is established based on the quantum properties of photons and with the consideration of the influences of the foam particle size distribution, scattering coefficient, foam layer thickness, incident angle and wind speed. The error rate formula for an air-water quantum key distribution (QKD) system is obtained. Combining with the Monte Carlo algorithm, the influence of each parameter on the photon polarization state, QKD error rate and transmission distance is simulated and discussed. The performance of the four-intensity BB84 air-water QKD system under the foam-irregular-sea-surface is analyzed. The research results show that, the polarization error rate increases with the increase of the foam layer thickness, scattering coefficient and light incident angle. Besides, the increase of wind speed leads to the rise of the quantum bit error rate of the air-water QKD system and the reduction of the secure transmission distance. Meanwhile, the key generation rate and the secure transmission distance of the air-water QKD system decrease as the foam layer thickness increases, and the maximum secure distance is reduced from 144 m to 101.3 m when the foam layer thickness increases to 6 cm and the maximum polarization error rate is considered, but it still satisfies the requirement of the 100 m safety depth for the underwater vehicles.

The generation of squeezed vacuum quantum optical frequency comb is realized from a singly resonant synchronously pumped optical parametric oscillator (SPOPO) pumped by the second harmonic of a mode-locked femtosecond laser with a central wavelength of 815 nm. With the balanced homodyne detection system, the squeezing degree of the zero-order super-mode pulse is 3 dB and the real squeezing degree is 5.15 dB, which indicates that the experimental result is well consistent with that obtained by the theoretical model. The effects of the transmissivity of the output coupling mirror and the loss of the intra-cavity for the singly resonant SPOPO and the efficiency of the detection device on the squeezing degree are theoretically analyzed, which provides a guidance for the optimization of the experimental measurement of the quantum optical combs.

Non-uniform 3D light detection and ranging (LiDAR) point-cloud data with outlier noises are not conducive to interframe point-cloud-matching in urban environments. Thus, an outlier noise filtering algorithm for large-scale scattered LiDAR point-cloud in urban environments is proposed. This algorithm improves the traditional density-based spatial clustering of applications with noise (DBSCAN) algorithm by applying voxel-grid partitioning to the three-dimensional point-cloud to create a set of grid cells, which greatly reduces the search scope of each object's neighborhood in the data-space range. The improved algorithm can quickly find each cluster, which separates the target point-cloud from the outliers, thus eliminating the outlier noise in the point-cloud. The experimental results show that the proposed algorithm can process point-cloud data in real-time, ensure three-dimensional geometric features of point-cloud, effectively recognize and filter out outlier noise, reduce the scale of point-cloud, and speed up the subsequent processing efficiency of the point-cloud.Using this algorithm, the accuracy of matching between the frames is doubled, and the matching time is only one-third of the time before denoising.

With the support of a pre-calculated land surface reflectance database, the universal dynamic threshold cloud detection algorithm (UDTCDA) can significantly improve the cloud detection accuracy of satellite data. To further improve its precision in the application of cloud detection for high spatial-resolution satellite data with relatively few bands, we improve the spatial matching method between the prior surface reflectance and the satellite observed reflectance. Different with the directly resample method in the UDTCDA, the pixel-by-pixel registration method is adopted to realize the matching between the satellite image and surface reflectance image. This approach preserves the spatial resolution advantage of high resolution images, and effectively reduces the loss of pixel information caused by spatial resampling. Four high-resolution satellite data, namely ZY-3, GF-1, GF-2 and GF-4, are used in cloud detection experiments. The cloud detection results of the improved UDTCDA are verified by the visual interpretation cloud results, and compared with the original UDTCDA cloud results. Results show that the improved algorithm can accurately identify different kinds of clouds in different high-resolution satellite images with an average accuracy of 93.92%. Especially for the broken and thin clouds, the accuracy is significantly improved with overall low omission and commission errors less than 10.40% and 9.57%, respectively.

A measurement method of bidirectional reflectance distribution function (BRDF) on the cutting surface is proposed based on the coaxial optical microscopic imaging. The BRDF measurement values on sample surfaces with different roughnesses are obtained by using the laser confocal microscopy. The measurement results show that, the BRDF on the sample surface varies with the roughness and the micro-topography, and this measurement method can obtain the BRDF measurement value on different microfacets. The BRDF parameter model is built and the optimal model parameters are obtained when the measurement data are processed by the genetic algorithm. The error analysis between the model calculation results and the measurement results is carried out and the maximum relative mean square root error is 9.97%. The results show that the established BRDF model is feasible and can accurately describe the reflection characteristics on the cutting surfaces.

Soil moisture content is an important indicator that reflects the coupled surface water-heat-solute transport in arid regions. The visible and near-infrared spectroscopy has been widely used for soil moisture content prediction owing to its rapid response. The soil moisture content and corresponding spectral data are obtained in the laboratory; then, the calibration datasets (n=77) are selected using Monte Carlo cross-validation algorithm. The competitive adaptive reweighted sampling algorithm is used to optimize spectral variables. Three machine learning algorithms, namely back propagation neural network, random forest regression, and extreme learning machine are used to construct predicting models. The results reveal that competitive adaptive reweighted sampling algorithm can effectively filter and eliminate massive irrelevant variables. Herein, a total of 20 feature bands are divided from all spectral bands, where the band of R1848 is the most prominent (the maximum correlation coefficient is 0.531). The performance of models based on machine learning algorithms is superior to those based on partial least squares regression, with the optimal prediction of the coefficient of determination (R2), root mean square error of prediction (RMSE), residual predictive deviation (RPD), and ratio of performance to interquartile range (RPIQ). Compared with the predictive effects of all the models, the extreme learning machine-based predicting model is the most effective (R2=0.918, RMSE=0.015, RPD=3.123, and RPIQ=3.325). Compared with common linear models, the machine learning algorithms can effectively improve the precision and stability of the quantitative estimation of soil moisture content. The results provide scientific guidance and baseline data for the accurate monitoring of soil moisture content and precision agriculture in arid regions.

The transparent tin oxide thin films with an average transmissivity larger than 90% are fabricated on the glass substrates by the spin-coating method with SnCl4·5H2O as the source material of the precursor solution. The research results show that, the plasma pre-treatment to glass substrates is helpful to improve the surface quality of the tin oxide films and the best surface quality is obtained when the plasma treatment power is 25 W. The increase of the annealing temperature kept below 500 ℃ can not only reduce the residue of organic components but also increase the thin film band gap under the condition that the thin film phase compositions do not change. When the annealing temperature increases to 500 ℃, the thin film phase composition changes from non-crystalline to polycrystalline.