Since the recognition of 2D marginal Fisher analysis is sensitive to the size of neighbors and a sole feature extraction method can’t meet the requirements of further improving recognition rate for variations in expression and pose of facial images, 2D Nonparametric Marginal Fisher Analysis (2DNMFA) based on person correlation coefficient is proposed firstly, and then a novel algorithm is proposed which integrated with 2DNMFA and Singular Value Decomposition (SVD). The algorithm extracts algebraic features and identifiable structural characteristics by SVD and 2DMFA method respectively, and then fuses membership degree by using fuzzy decision theory based on the advantages of two characteristics. Experimental results on CIS face database, Texas face database and UMIST face database demonstrate that this algorithm improves the recognition rate and is more robust than 2DMFA or SVD.

The conventional Maximum Margin Criterion (MMC) is sensitive to noise. To address this problem, a Robust Maximum Margin Criterion (RMMC) based on complex kernel is proposed. The samples are first mapped to the Complex Reproducing Kernel Hibert Spaces (CRKHS), and then the MMC is conducted in CRKHS. Besides, an efficient algorithm for implementing MMC is also proposed in this paper. The experimental results shows that RMMC is robust to the noise images and its recognition rates are higher.

For the pixel gradient direction of the top of the head having a fixed scope, this paper firstly selects the candidate pixel points in the foreground. Then it locates the areas of human head-shoulder quickly by these points, which is defined as the windows to be tested. Secondly the illumination invariant color features and the rotation invariant LBP texture feature are extracted and combined together with the Background-weighted Histogram (BWH) algorithm. Lastly, Histogram Intersection Kernel Support Vector Machine (HIKSVM) classifies objects. Experimental results show that based on the pixel gradient direction of the top of the head, the windows which contain head-shoulder can be located more quickly than the traditional method, sliding window, which improves the efficiency of the detection. Furthermore, the accuracy of detection is also improved by the fusion feature of HSV and LBP. Experimental results show that the proposed algorithm is robust and accurate against cluttered dynamical background, occlusion and the object deformation, and tested in many pedestrian datasets and achieved good results.

In pedestrian classification, there are many factors, such as light changes, posture changes and occlusion problems etc, which brings many difficulties for feature extraction process. A hierarchical feature method is put forward based on sparse coding. The method trains optimal sparse coding with forward prediction function, and then learns the two levels networks one by one in unsupervised manner with Convolution Predictive Sparse Decomposition algorithm (CPSD) under framework of the deep convolution network model. Then we make the feature fusion. Finally, we implement classification with SVM algorithm. Experimental results demonstrate the effectiveness of our method for pedestrian classification, which has significant performance improvement compared with similar methods.

Aiming to address the problem that segmentation based face recognition is sensitive to illumination imbalance, an illumination equalization preprocessing for face image is proposed. Firstly, a set of extended test images are generated by considering the fact that the face image has symmetry. Then, the extended test face images are vectorized to concatenate a matrix, from which the illumination equalized test face image is extracted by low rank decomposition technique for the following recognition. Simulation experimental results based on AR database primarily demonstrate that the proposed method could efficiently improve the performance of detecting the bilateral symmetry occlusion of face, and thus promote recognition rate considerably.

Among the abnormal behavior detection methods, it is difficult to describe the crowd behavior. For this case, an abnormal behavior detection approach based on behavioral similarity (collectiveness features) between individual and other individuals in the group is proposed. Firstly, Gaussians mixture model was used to extract the background of the video. Then, Kanade-Lucas-Tomasi (KLT) algorithm was used to track the moving crowd. Next, collectiveness features integrated the motion information of the whole crowd are extracted from the direction and speed of the crowd movement. Finally, a histogram derived from the collectiveness features was defined to measure the anomaly of crowd activity, and the entropy of the histogram was computed to recognize abnormal events. Experiments were conducted on various video datasets, and results were presented to verify the effectiveness of the proposed scheme.

Aiming for objects' unsteadied inter-salience properties in person re-identification, a new algorithm of person re-identification is proposed in the base of multi-salience fusion. Two-stage Manifold Ranking (MR) is established to obtain image intra-salience. A more accurate multi-salience fusion description method is presented after combining intra-salience with existing inter-salience. The approach considers not only inter-salience of the patch with other person images' patches, but also the intra-salience of the patch in the own image. It improves the description of the patch in salience. Compared with the similar algorithm, the method can describe the salience of objects more accurately, reaching high re-identification rate.

In order to solve the problem of space manipulator path planning with minimum energy consumption, the energy function of space manipulator is derived first, and then the energy function is regarded as the functional of 3 joint angle functions. The problem of space manipulator path planning with minimum energy consumption is translated into a problem of the functional extreme with fixed boundary. A system of equations for expressing the path with minimum energy consumption is derived from resolving the problem of the functional extreme by using variational method. By means of the inverse matrix expression of the upper triangular matrix, the system of equations is translated into a new one consisted of normal state equations. The method can avoid complex inverse matrix computing, and make the computation of the transition process simpler when compared with differential geometry method. For a group of parameters of the 3R manipulator, the initial value problem of the new system of equations is solved by using Matlab simulation method. The solution of the boundary value problem of the new system of equations, representing the path with minimum energy consumption, is obtained from the solutions of initial value problem of the same system of equations by using random search method, and the feasibility of variational method for solving this kind of problem is also validated.

Finite element analysis of shafting structure containing bearing is difficult in the current. According to the structure of large-aperture telescopes azimuth shafting, we designed and built an experimental platform to measure the elastic approaching of the plane thrust bearing. The experimental platform was based on the Dantec dynamic company’s non-contact measurement and analysis system for displacement. We got the stiffness curve of the plane thrust bearing by the experimental study of the contact problems. A finite element model in line with the actual working conditions was established and the recommended values of key parameters were given. The results show that, compared with the experimental results, the difference of elastic approaching which was calculated by ANSYS is within 2.47 μm and the maximum error is 11%. The results verify the accuracy of the finite element model and provide a reliable basis for the static analysis of the azimuth shafting of large-aperture telescopes.

In order to compensate the effect of off-axis TMA aerospace mapping camera defocus from engineering practice side, one kind of defocus offsetting compensation mechanism is proposed based on ball screw and rod. The design requirement is analyzed, the adjustment position is determined, and the reliability design and performance indicator detection is carried out. The oscillation angel along the X axis is ±2.7″, the oscillation angel along Y axis is ±3.3″, the residual error is less than 2 μm, the maximum error of sampling is 5 μm, and the mechanism has good self-locking performance, which could be used in off-axis TMA aerospace mapping camera.

A toroidally bent crystal X-ray imaging system was designed in order to detect the X-ray spectrum and diagnose the image of target on fusion device. The Johann point-focusing geometry aberration was calculated in theory. Ray-tracing simulations of an optical X-ray system based on the bent crystal working operating in Bragg conguration for monochromatic projection imaging of grid samples are presented, and the relation between the Bragg angle and the spatial resolution of the imaging system is investigated. The X-ray radiation from a small source is dispersed by a transmission grid placed in front of the toroidal crystal imager. Our successful applications suggest that the bent crystals may be used to image with high spatial resolution. This configuration retains the advantages of the bent mica crystal spectrograph while enabling the analysis of the spectral radiation. Spectrally and spatially resolved Kα spectra of Cu were observed.

In order to upgrade the communication system from direct detection to coherent detection, an upgrade scheme is proposed by using optical coupling from space to fiber hybrid and Decision Driven Phase Locked Loop (DDPLL). The pointing error would cause coupling loss and then influence the optimal bandwidth of DDPLL. Therefore, the theoretical analysis about the optimal bandwidth of DDPLL and simulation are carried out with considering the pointing errors of transmitter and receiver. The results shows that the optimal bandwidth of DDPLL decreases with pointing errors of transmitter and receiver, and the minimum phase error increases with pointing errors of transmitter and receiver. Both of these parameters are more sensitive to the receiver pointing errors.

In order to suppress the third-order intermodulation distortion of the down converting Radio-over-fiber (ROF) link, linearized down converting ROF link based on a Polarization Modulator (PolM) in a Sagnac loop is proposed. First, the modulation method and the principle of this technique are described theoretically. And then, simulation analysis about ROF link based on the technology is carried out. The analysis results show that the technology can get optimized link gain, and spurious free dynamic range reach 127.4 dB.Hz2/3 by optimizing the parameters of the three Polarization Controllers (PCs) and the polarization angle between the polarizer and the spindle of PBS.

In order to solve the problem of long distance energy transmission, divergence angle of laser transmitted by space-borne laser communication terminal must be usually very small, typically on the order of tens of microradians. But the ground testing must properly amplify the divergence angle, to ensure that the communication terminal can always in the beacon beam and communication beam range with a certain tracking accuracy. This paper uses the communication light which sensitive the intensity distribution as an example, building the theory molding and simulating for different distance and position, analyzing the influence, which provides scientific basis for space laser communication ground demonstration. Meanwhile, defocus and magnification of two kinds of divergence angle amplification method was compared. In the ground testing of a space laser communication, we give the optimal selection scheme. The result provides scientific basis and accumulated experience for the space laser communication ground test.

A reliable and accurate method based on multilayer film model by spectroscopic ellipsometry is proposed to measure optical constants of UV weak absorption films. Take examples of HfO2 film and SiO2 film, multi-angle ellipsometry parameters Psi and Delta had been measured by spectroscopic ellipsometry to inverse optical constants of HfO2 and SiO2 film between 200 nm and 900 nm in Wavelength, which were fitted by point-by-point method using the Cauchy with urbach absorption model. Comparing the fitting result of ellipsometry and the test result of scanning electron microscopy (SEM), we verified the accuracy of the optical constants of HfO2 and SiO2 film. The results show that the structure and optical constants of weak absorption coating can be better described by Cauchy with urbach absorption model using point-by-point method, and the results are important for the fabrication of UV filters.