In consideration of the effect of noise in an optical tweezer on its measuring accuracy, an effective compensation method for the random drift error of the optical tweezer was proposed. Firstly, the time series analysis and Kalman filter methods were introduced. Then the random drift error of the tweezer was modeled by time series analysis method and the Kalman filter was proposed to decrease this drift error. The testing error from an optical tweezer test setup was compensated. The compensating result shows that the error variance is reduced from 188.90 nm2 to 8.41 nm2. The data analysis with the Allan variance method demonstrates that the minimum error is reduced from 0.7 nm to 0.1 nm for an averaging time of 1 s. The experiment shows that the method mentioned above can effectively compensate the random drift error of the optical tweezer. It can be used in aligning the double optical tweezers and can improve the accuracy of initial alignment for a capturing light and a detecting light in the double optical tweezer and can enhance the equipment performance.

As the locating accuracy of a Mach-Zehnder fiber sensing system is effected by the initial phase shift in practical use, a passive digitalized demodulation method based on 3×3 fiber couplers was proposed according to the optical path structure. First, two outputs of the 3×3 couplers were used to form an ellipse curve, and then the signal coefficients were estimated by Least Square Method under constraints. Finally, the required phase signal was demodulated by differential and cross-multiplication. Compared with traditional demodulation methods, it lowers the requirements for the symmetry of couplers, and imposes no extra limits on other parameters. The ellipse fitting is robust under constraints, especially adaptable to those data less ideal in ellipse shapes. Simulation and field experiment prove that the method with a small computation is feasible and practical. The demodulated phase signal correlation is 0.992 0 and the position error is 81.2 m over a pipeline with a length of 43 km. The digitalized demodulation method virtually enhances the system function, and shows considerable application values.

As traditional joint transform correlators based on space light modulators can not adapt to the radioactive environment in space, a new correlator implemented by an electronic processor was introduced and testified. First, the traditional optical device was replaced by a digital processor to allow the new correlator to adapt to the radioactive environment. Then, a self-correlation calculation was added to the joint transform processing to eliminate the influence of zero-level diffraction, and the over-sampled discrete Fourier transform method was introduced to increase the measurement precision. Finally, the static measurement with a linear platform was performed to testify the improved joint transform correlator. Experimental results indicate that the measuring precision of the system on subpixel displacement is within 0.22 pixel(Root Mean Square, RMS). The improved joint transform correlator is good at both space environment adaptability and realization, its measurement precision can satisfy the system requirements of satellite cameras for the image motion compensation, and has a good application prospect.

A polarization angle sensor was designed to gain the azimuth angle of a navigation system by learning from desert ants using the polarized pattern for navigation. To improve the measuring accuracy of the polarization angle, the factors influencing the angular errors were analyzed and the compensation method was researched. Based on the polarization principles, how to obtain the information of polarized azimuth angle from a sky polarization pattern was discussed, the main factors influencing the angular error measurement was analyzed, and a polarization angle error measuring model was built. According to the model, the solution to the polarization azimuth angle was deduced and the Least Square Method(LSM) of error compensation was presented to indirectly compensate the angular error by estimating the error parameters of the model. An experiment was performed eventually when the weather was fine. The experimental results show that the angular error is less than 0.17 degree (3σ), which indicates that the accuracy of the polarization angle is improved. The experiment demonstrates that the algorithm is feasible to compensate angular errors.

To tune the operating frequency of a Frequency Selective Surface (FSS), the load impedance of the loop slot FSS forms was separated to an inductive surface and a capacitive surface, and the coupling mechanism between the two surfaces was used to develop a Complementary FSS(CFSS). An equivalent circuit model of the CFSS was established and its tunable resonance mechanism was analyzed quantitatively. The influences of the rotating angle of the load patch, coupled dielectric thickness and the relative dielectric constant on the transmission characteristics of the CFSS were calculated accurately by using the coupled integral equation method, then the inductive surface and the capacitive surface were fabricated on both sides of the coupled dielectric by the coating and lithography methods. The transmission response of a 250 mm × 250 mm CFSS prototype was measured by using the free space method. The calculated and measured results show that the CFSS resonance will be tuned from 18.2 GHz to 14.8 GHz by rotating the cross patch from 0 degree to 10 degree. The coupling effect between the capacitive surface and the inductive surface will disappear by increasing the physical thickness of the coupling dielectric from 0.1 mm to 1 mm. With increasing the relative dielectric constant of the coupling medium, the coupling between the CFSSs will be strengthened and the operating frequency will shift to lower frequencies. It concludes that the CFSS can realize the active resonance conversion function as the rotating angle changes, which provides references for the design and manufacture of active FSSs.

According to Compressive Sensing (CS) algorithms and the Ghost imaging (GI) model, the CS was applied to the GI system to complete the CS reconstruction of an image. The feasibility of CS applied in GI was firstly validated by a simulation experiment. By using Peak Signal to Noise Ratio(PSNR) as the measure, the restructured images based on CS and traditional GI correlation algorithms were quantified respectively. The simulation experiment results indicate that both the restructured images are getting better with the increase of the number of measurements, however, the PSNR of CS reconstruction image is above 20 dB higher than that of the traditional correlation reconstruction method at the same number of measurements. Furthermore, the CS was applied in an actual two-arm GI experiment. The experiment results indicate that the CS can achieve the image reconstruction of two-arm correlation imaging equipment, but its reconstruction quality is hard to be better than that of the GI correlation algorithm. For this special confliction phenomenon, the paper gives some reasonable interpretations from the two-arm symmetry perspective and then fully validates the interpretations by using the actual speckle pattern from the experiment. Finally, it proposes a solution scheme.

A spectral imaging module was added into a laser scanning confocal microscopic system to discriminate different fluorescence components in biological tissures. A prism was used as a beam split part, and two movable slit edges were used to form a slit whose width and position could both be adjusted on the spectral image plane. The two slit edges were installed on a stepping motor. By adjusting two slit edges, the laser scanning confocal spectral microscopy could work at wavelengths of 400-700 nm and its minimum spectral wavelength for confocal imaging was less than 5 nm. The actual slit positions corresponding to spectral lines of 488 nm laser and low pressure mercury lamp were tested and compared with the theory positions. The results show that the differences of the actual slit positions and theory values are all less than 0.1 mm. A laser scanning confocal imaging experiment with a full spectrum confocal imaging and 2.5 nm spectrum bandwidth (50 μm slit width) confocal imaging was carried out using a mouse kidney tissue slide. The images of nuclei labeled by DAPI and glomeruli labeled by Alexa Fluor 488 were obtained and the different components in biological tissues were distinguished. It concludes that the system can complete the confocal spectrum imaging, by which the application area of laser scanning confocal microscopy has been extended.

An optical system for a multi-target infrared compounded simulator applicable to 1-3 μm and 3-5 μm is designed based on the transmission compounded projection and micorlens array expanding. The disturbance optical path of the simulator adopts transmission compounded projection and uses a micorlens array as the beam expander. To allow the target/disturbance generator to share the same optical path, an afocal system and a back focal lens group are combined and a coupling plane mirror is inserted in the collimation light besides. Moreover, the target optical system, disturbance optical system and the main projection optical system are optimized respectively, then the whole system is optimized further. The designed system contains an entrance pupil distance of 200 mm, field of view of ±4°, and the Modulation Transfer Function(MTF) no less than 0.6 at 20 lp/mm, approaching the diffraction limit. Finally, the measured data of assembled optical system is analyzed and it shows its MTF to be greater than 0.3 at 20 lp/mm. The infrared optical system satisfies application requirements completely and has been applied to a novel infrared simulator for providing reference for design of the infrared simulation systems

To shape the beam with two-lobe far-field property from a dual side Bragg reflection waveguide semiconductor laser, a dual grating structure based on surface plasmons was prepared on the optical outlet facet of a Bragg reflection waveguide.It could combine the two lobes into a single lobe and to increase the optical intensity and quality of the beam. An Au-SiO2 grating was used to couple photons into surface plasmons and to combine the two lobe beams into a single beam. The surface plasmons also were taken to increase the extraordinary optical transmission. On the other hand, the Au-Si3N4 grating was used to help the outlet surface plasmons couple back to photons, meanwhile collimating the outlet beam to increase the far-field property. Numerical simulation results indicate when the parameters for Au-SiO2 show a depth of 50 nm, a filling factor of 0.5 and a duration of 350 nm, and those for Au-Si3N4 show 70, 0.5 and 660 nm, respectively, the outlet far-field beam will has a 6.1° divergence, which means the divergence angle shrinks by 3.6 times as that without the dual grating structure. The far-field optical transmission power reaches 62% of the model source, that is 1.59 times of the power of a single lobe far-field to the structure without the dual grating. Moreover, the cavity facet reflectivity has reduced to 12.4%, 0.53 times as the structure without the dual grating. It concludes that the dual grating structure has optimized the far field properties of dual side Bragg reflection waveguide semiconductor lasers.

After analysis the collecting methods of near backscatter light in laser fusion, a metal ellipsoidal mirror was proposed to collect the near backscatter light of SG-Ⅲ laser facility. Then, the method to determine the parameters of ellipsoidal mirror was discussed. The mirror is composed of four pieces, which makes it entering into the target chamber easily. The mirror is made of super hard aluminum, and a triangular weight reducing slot is designed on the back of the mirror to reduce its weight and improve its mechanical stability. The overall structure of the optical system was introduced, and the light gathering performance was simulated using optical software. The key issues in ellipsoidal mirror design, including material selection and structure selection, were analyzed. In order to avoid rework, a semiconductor laser array was developed specially to test the surface in design processing. The stray lights in the system were analyzed, physical isolation, optical absorbing and optical filters were used to control them. The ring ellipsoidal mirror with a weight of 48 kg has an outside diameter of 1 200 mm, an inside diameter of 400 mm, the maximum off-axis magnitude of 1 411 mm, and the maximum thickness of 67 mm. The image spot size is about 1.2 mm within a field of view 5 mm. This system mentioned above can offer a reference for near backscatter diagnostic in inertial confinement fusion research.

To accurately obtain the 3-D coordinates of key points of large-size industrial products or some work pieces with deep holes, two kinds of optical, contact and portable probe systems were studied and implemented based on the theory of close-range photogrammetry and stereo vision technology. The key technologies applied in the systems were studied, including probe design, probe calibration and 3-D point reconstruction. Two kinds of probes, dot-matrix and hand-camera, were designed to apply to different industrial product measurements. Then, for the dot-matrix probe measurement, a point cloud registration method was proposed to solve the relationship beween probe coordinate system and world coordinate system. Besides, a method of fitting the virtual ball was used to calibrate two probes. Finally, four standard balls were measured in an accuracy test. The comparison results from three-coordinate measuring machine show that the measurement accuracy of the system can be up to 0.1 mm/m. It suggests that the system has met the general accuracy standards of the three-dimensional point measurement of medium and large sized products.

The working principles of Laser Demarcation Instruments (LDIs) and their standard errors were analyzed. A new set of Multi-dimensional Calibration System (MDCS) for the LDIs was developed to solve these shortcomings of traditional calibration systems on larger floor spaces, poor accuracy and high influential artificial factors. A solution based on collimator angle measurement and machine vision measurement was designed to calibrate the LDI by measuring the straightness and verticality of laser lines. The data capturing platform of the system consisted of 8 collimators was used to achieve the multi-dimensional calibration. The software was designed by mixed programming of VC++ and Matlab, and they were connected by calling a Dynamic Lined Library(DLL). Experiments show that the new system is easy to operate, and is more efficient and more credible. The space that the whole system takes up is within 8 m3, which saves the area of work place. Moreover, the accuracy of horizontal and vertical lines can reach ±0.2 mm/5 m, and the orthogonal line is ±23″, which meets the requirement of calibration accuracy.

As the accuracy of wave-front detection of Shack-Hartmann sensors is mainly dependent on the accuracy of centroid detection of a focal spot, this paper proposes a dynamic determination method of array spot centroid detection window based on marked watershed segmentation. This method smoothes the spot image captured by a Shack-Hartmann wave-front sensor based on the marked watershed segmentation and obtains its gradient image, firstly. Then the OTSU method is used to mark the target on the gradient image. Finally, the marked gradient image is segmented by the marked watershed method and the detection window of every spot is determined. Because the detecting window can be matched with the actual size of spot, the affection of the noise on centroid detection is effectively suppressed. The experimental results demonstrate that the precision and stability of centroid detection by this method are higher than that of traditional method. The mean values of standard deviation in every detecting window of statistic multiple images are calculated, which is 0.010 9 , 6 times that of the traditional method (0.073 4). It can satisfy the requirement of Shack-Hartmann wave-front sensors for precision and stability of centroid calculation.

A fast design method for the drive circuit was proposed by combining Genetic Algorithm(GA) with a low frequency model to improve the transient performance of analog drive circuit for a low-power Silicon Resonant Accelerometer(SRA) and to shorten its design cycle. The method decoupled the closed drive circuit model in high and low frequencies to extract a low-frequency model from drive close-loop circuits. Combined the low-frequency model with the GA, an optimization method was proposed to optimize the circuit parameters for meeting the different actual restraints. A simulation model was established in SIMULINK based on one type of micro silicon resonant accelerometer, and the optimal parameters of PI controller with a most start-up speed were obtained under constraint conditions. Finally, a start-up experiment was performed to testify the simulation results. It shows that the start-up time is shorten from previous 0.42 s to 0.19 s and the over-shoot and phase error are less than 50% and 5°, respectively. The difference between the simulation and experiment is less than 5%, which falls within the acceptable range. It proves that the optimization method is correct and effective.

As the three wheel taxiing stage of an Unmanned Aerial Vehicle (UAV) is the most vulnerable in whole flight process, this paper explores linear modeling and a gain scheduling control method of nose wheel steering turning for a tricycle-undercarriage UAV in taxiing on the ground. The force of three wheel taxiing of the UAV was analyzed, and its nonlinear mathematical model was established considering the effect of engine torque, thrust misalignment and ground angles. Then, the nonlinear model was linearized using small perturbation theory under reasonable assumptions, and the transfer function was deduced by using the nose wheel steering angle as a input and the yaw rate, yaw angle, and lateral deviation as outputs. The three gain scheduling control law through nose wheel steering turning was designed. Finally, the method was verified through a field taxiing test. The result shows that the most lateral position deviation is 0.3 m and the most yaw deviation is 4.5° under an initial yaw deviation of 3° and a lateral position deviation of 0.2 m during the process of taxiing from rest to the speed of 32 m/s. Moreover, the crosswind disturbance of not more than 4.6 m/s was inhibited. The control law designed by using the method above is robustness to the uncertain factors of the runway, tire cornering stiffness and tire deflection and has been applied to a practical UAV successfully.

To build a standard test specification for solar cells, various kinds of affect factors on the final uncertainty of solar cell standard tests were evaluated and selected. Based on the secondary solar cell standard test equipment and devices, such as sun simulator, spectral sensitivity, IV tester and standard solar cells, several kinds of testing technologies were researched. Some effect factors in measuring processing were discussed, including the spatial uncertainty of solar cell simulator, temporal stability, measuring repeatability, the uncertainty from sweep directions, the reflection and transparence of cell, the uncertainty for area and External Quantum Efficiency (EQE). Then, the measuring procedure of a high efficiency crystalline silicon solar cell was proposed and the extension test uncertainty of 3.94% was derived under the conditions of existing laboratory measurement .Based on a comparison to conventional solar cell test data, the conventional cell testing method was improved, and the uncertainty of measurement was reduced by 0.19%. Finally, a standard testing procedure for a double-side cell was proposed, which provides a reference for other related cell measurements.

A novel rapid on-machine length measuring system based on 3D laser scanning was developed for mobile and large scale cylinder workpieces. By using the outstanding characters of laser scanners on fast continuously acquiring the mass of measurement points in a very short time, the multi-sensor fusion technique and a 2D error separation method were respectively introduced in this system in a virtual environment. Virtual measurement datum planes were established based on virtual registration sites, which followed the variant surface of measurement target. Then, the 3D displacement field measurements between end points and virtual measurement datum planes were built. A similar cylinder workpiece measured by Coordinate Measuring Machine (CMM ) was applied to calibration of the system. Finally, the experiments on the cylinder workpieces (1 000±25) mm with different diameters were carried out to determine the accuracy and reliability of measuring system. The experimental results indicate that a workpiece with a diameter about 50 mm is perfectly measured in only 1 s with the resolution less than 0.010 mm and the measuring precision over 0.050 mm. According to the actual operation results, this proposed measuring system is characterized by high automation and high efficiency, and can be well acceptable for application as online length detection for large scale workpieces in industrial production.

A micro needle-to-cylinder corona discharge structure was designed to integrate an ambient ion source and a micro air pump. By needle-to-cylinder discharge photos and Trichel discharge waveform recorded with a digital camera and an oscilloscope respectively, it verified that the stable corona discharge of needle-to-cylinder structure could be realized without external air flows and with only 2 mm distance between need and cylinder. The corona discharge characteristics of the needle-to-cylinder structure were researched and the influence of experimental parameters, like discharge voltages, ballasting resistor, the diameter of cylinder and the distance between the needle and cylinder, on the corona discharge was discussed. By analysis of the volt-ampere characteristic curves, it shows that the max velocity ionic wind can be gotten in a discharge voltage of -3 800 V, a discharge resistor of 10 MΩ, a cylinder diameter of 4 mm, and the distance between the need and cylinder of 2 mm. Moreover, the max air flow velocity is 1.15 m/s measured by the test 405-V1 anemometer. The needle-to-cylinder structure can be fabricated by Micro-electro-mechanical System(MEMS) technology, and may be used in the portable analytical instruments to realize the double functions of ambient ion source and micro air pump, such as mass spectrometry, ion mobility spectrometry, and high-field asymmetric waveform ion mobility spectrometry.

The control and design of flexible support structure and warping surface for an aircraft is a key to improve its flight performance. In this paper, an integrated optimal design method for structural parameters and control voltages was presented by using Microfiber Composite (MFC) as a actuator to obtain the desired shape of the surfaces. An integrated optimization model of actuator structural parameters and control voltages was established for minimizing the control deviation through designing electrode width and separation, MFC thickness, the volume fraction of piezoelectric ceramic fiber and controlling the breakdown voltage of MFC. The optimal parameters of the actuator were given by analyzing and comparing the effect of structural parameters on the performance of surface. The warping of a wing surface was used as an example to validate the effectiveness of the method. The results show that the mean square deviation of the multi-voltage control is 45% that of the single voltage control. These results prove that the method presented has potential applications in design of aircraft wing warping.

A new design scheme for fast steering mirrors was proposed according to the requirements of a laser launching system for emission accuracy. A flexible hinge was used in two-shaft fast steering mirror structure as the moving transmission device, a linear voice coil motor was as a driving component and a high precision optical grating micrometer was taken to implement the position closed control. The operational principle and drive mode of the fast steering mirror were introduced, and the drive components and an angle measuring device were selected. Then, the structure of the flexible hinge was designed. On the basis of researching the stiffness characteristics of the straight beam flexible hinge, sequential quadratic programming algorithm was used to optimize the critical dimensions of the hinge. Furthermore, a simplified model of the drive components was established, and theoretical models and finite element analysis software were used to calculate and verify the transmission accuracy of the drive assembly. Finally, angle measurement components and autocollimation were used in the measurement of the rotation accuracy of the fast steering mirror. The experimental results show that the mechanical structure of the fast steering mirror is stable, reliable, and the beam control precision can reach to 0.95", satisfying the precision requirements of real-time control of the transmission direction in the laser launch system.

The application of electrospinning fabrication technology in micro/nano sensor production was investigated. Mixed solutions of praecursor bodies PVP(Polyvinyl Pyrrlidone)/Zn(Ac)2 and PEO(Polyoxyethylene)/Zn(Ac)2 were used as the electrospinning materials to make a precursor nanofiber. The precursor nanofiber was calcined at 500 °C in the air to remove polymers and the Zn(Ac)2 was thermally decomposed and oxidized into ZnO. X-ray diffraction (XRD) was used to charaterize the components of a ZnO nanofiber. The sensing response of a ZnO nanofibrous gas sensor on the ethanol and acetone vapors were tested. The test results indicate that the average diameters of ZnO nanofiber made from PVP/Zn(Ac)2, PEO/Zn(Ac)2 precursor are 308 nm and 184 nm, respectively. XRD spectrograms show that the ZnO nanofiber with high purity can be obtained from a blended precursor nanofiber through thermal oxidation. The response time of the ZnO nanofibrous sensor on the objective gas is less than 1 s at room temperature and its sensitivity increases with the increment of gas concentration. Furthermore, the ZnO nanofiber made from PEO/Zn(Ac)2 precursor shows a roughness surface, a larger specific surface area and higher sensing sensitivity, and the maximal sensitivity of ZnO nanofibrous gas sensor on ethanol and acetone vapor have been up to 215.69 and 118.13, respectively. This work presents a novel method for the integration fabrication of semiconductor micro/nano gas sensors.

To provide building blocks for high-performance Micro-electro-mechanical System (MEMS) devices, Layer-by-layer (LbL) self-assembly of Single-walled Carbon Nanotube (SWNT)/polymer films was proposed and their properties were characterized and tested. The surface morphologies of the SWNT/polymer films observed under a Scanning Electron Microscope(SEM) show high strength, dense and random network structures. Raman spectra of all characteristic peaks for the SWNT in radial breathing mode, disorder mode and tangential mode demonstrate the presence of the SWNT in overall good quality and a loading state. Real time Quarts Crystal Microbalance(QCM) online monitoring illustrates that the deposition thickness and the SWNT loading fraction in the nanocomposite can be controlled in a large range based on LbL sequential deposition process. When the cycle number of polymers increase from 0 to 5, the average film thickness increases from 6.31 to 111.59 nm, and the SWNT volume fraction decreases from 72.35 % to 14.78 %. In addition, the electric properties of the SWNT/polymer films under the influence of SWNT loading fraction and film thickness were investigated through current-voltage characterization. These results provide experimental and theoretical bases for potential applications of SWNT films in MEMS devices.

An ultrasonic phased focusing time delay system was established by using the multi-stage half-band filters to improve the accuracy of ultrasonic phased array instruments. The principle of the focusing time delay and the realization of the corresponding time delay algorithm were investigated. Firstly, the interpolation filter with a half-band one was used as an interpolation filter based on interpolation method. Then, the structure of the 8 × interpolation was improved. With a synthesis technique of a multi-stage half-band interpolation filter, the synthesized filter was divided into 8 sub-filters to work at the same time. In this way, both interpolation and polyphase decomposition could be simultaneously processed. Finally, the feasibility of this delay algorithm was verified by using the simulation analysis and the implementation of Field Programming Gate array(FPGA). The experimental results show that the time delay accuracy of the system is 1.25 ns at a sampling rate of 100 MHz. Comparing with the ordinary Finite Impulse Response(FIR) interpolation filter, the amount of computation with proposed interpolation filter can be reduced by 21.4% under the same condition. The program is characterized by lower computation amount, fast computing speed, excellent resolution and cost efficiency and can improve the overall performance for phased array instruments.

To increase line-of-sight (LOS) tracking and pointing accuracy of an Optic-Electro (O-E) landing guidance system, this work explores how to isolate the LOS tracking and pointing of a O-E theodolite from the carrier motion disturbance. A carrier-based O-E theodolite model was established with various disturbance factors introduced. Three kinds of controllers, Lead-lag,LQG/LTR( Linear Quadratic Gaussian/ Loop Transfer Recovery) and H∞ were designed to improve the stability and performance of the system. The Kalman filter and H∞ weighting matrix were investigated in detail. Then, the controllers were emulated in Matlab and verified on a swing bench. The compared experiments for the three kinds of controllers on time domain, frequency response and stability were performed. Obtained results show that both LQG/LTR and H∞ controllers can satisfy the design specifications, and their decoupling effects are as deep as 50 dB, which can ensure precise tracking and pointing performance of LOSs in O-E landing guidance systems.

For application of the axial vibration micro feeding technology to the quantitative dispensing of an implant control releasing drug micro system, an experimental apparatus based on the axial vibration method was set up. By using a glass capillary hopper and a conical plastic-tip as the dispending tubes, the vibration amplitude between both dispending tubes was researched and the influences of quantitative dispensing control parameters on the starting vibration amplitude, powder flow rate and the powder flow stability were discussed. The results show that the conical plastic-tip is a better dispensing tube with stable dispensing and good resistance to plugging. The higher the frequency, the lower the starting vibration amplitude needed to achieve desired starting feeding. At a constant excitation frequency, the flowing powder in the tube increases with the flow rate first, and then decreases to a stable value, meanwhile being a full flow state. Under both conditions with the excitation frequencies of 50 Hz, 150 Hz and the amplitude between 200-300 μm and 35-50 μm, the maximum and stable powder flow rate can be obtained. It concludes that the axial vibration micro feeding technology can achieve stable, accurate dispensing of the drug powder.

To measure the chip-level temperature and to achieve close-loop control for a Micro-Electro-Mechanical(MEMS) resonant accelerometer system, this paper investigates non-inertial parts of the system, proposes a method to measure the temperature of the MEMS structure and optimizes the parameters in the close-loop control. Different from the traditional method that using a temperature from a temperature control cover as the conference, this paper proposes design methods of MEMS structures, processing technology and circuits, and achieves the temperature compensation by measuring the MEMS structure temperature directly to improve the temperature measuring accuracy. Furthermore, a diode pre-circuit is applied to detection of the variation of the tiny capacity instead of the transimpedance amplifier and transconductance amplifier, which reduces the requirement for high-performance components from pA to nA magnitudes. Based on the analysis in the time domain, analytical solution of diode pre-circuit is proposed to optimize the parameters and to guarantee the linear relationship between input and output. Moreover, a second-order optimal mode is applied to control of the settling time of the post-circuit. Experiment shows that after compensation on temperature, the MEMS resonant accelerometer has the performance of bias stability of 52.0 μg, scale factor stability of 16.0×10-6, resolution of 34.9 μg. The result indicates that the proposed theories can satisfy the requirements of high-performance MEMS resonant accelerometer systems.

A speed controller was designed based on predictive functional control to reduce the torque ripples of a permanent magnet synchronous motor and to increase the speed control accuracy at a steady state. To solve the problem of controller deterioration due to the load disturbance, a two loop controller was designed based on the predictive functional control and a disturbance observer. The observer was used to estimate the system disturbance and compensation current was produced to feed in the speed controller to attenuate the load disturbance. Experimental results demonstrate that the system has no overshot and the speed fluctuation is 2 r/min when the motor reaches the steady state of 600 r/min from stillness. The speed fluctuation is 5 r/min when the motor is operating at a speed of 600 r/min and a 1.6 N·m torque disturbance is added. Compared with the traditional PI controller, the proposed controller decreases the speed fluctuation by 4.2%. Simulation and experimental results show that the proposed controller can increase steady accuracy and improve anti-disturbance performance.

A method based on angle subdivision approach algorithm and Particle Swarm Optimization (PSO) was proposed to evaluate concicoid profile error accurately in any position and orientation with the requirement of the minimal zone。 Two hypotheses were proposed to realize the angle subdivision approach algorithm. According to the hypotheses, a recursion formula for more reasonable girdding was given. Then, an accurate evaluating model was established according to the definition of conicoid profile error. The angle subdivision approach algorithm was adopted to calculate the distance between measurement points and fitting quadric surface. The position between measured profile and theoretical profile was matched through fitting the general quadric surface equation. A paraboloid antenna was evaluated by the above method in an experiment, and the results were compared with those of parameter subdivision approach algorithm, SMX-Insight and Least Square Method (LSM). Experimental results indicate that the profile error is 0.659 8 mm more accurate than that of other methods. The results show that angle subdivision approach algorithm is more efficient in concicoid profile error evaluation and its calculation is accurate, rapid, and no need to find the division area.

As traditional description vector calculation method used in image registration is too complex, time consuming and taking up more memory, a novel dictionary based local feature description algorithm was proposed. The K-singular Value Decomposition( KSVD ) method was used to generate dictionary and the feature descriptor was obtained by comparing the similarity between feature point region in images and elements in the dictionary. By above, the description vector generation algorithm was simplified and a higher feature matching speed was obtained. The matching process could be carried out by using randomized KD(k-dimension)tree algorithm. Then , the Random Sample Consensus (RANSAC) was used to choose the correct matching pairs. Finally, the transform parameters were estimated by using the least square method and the space geometric transformation of two images to be registrated was obtained. Results from experiments show that the proposed method reduces the description vector storage space, speeds up the feature matching and implements the registration process in real time.

A visual inspection system for small modulus gears was established to realize their industry measurement. A de-noise algorithm based on scale-correlation and direction-correlation in Curvelet transform was proposed according to the de-noising demands in system calibration. First, the theory and process of the Curvelet transform were introduced. Then, according to the gear symmetry itself, a new combined algorithm for image de-noising based on Curvelet scale-correlation and direction-correlation was proposed, the corresponding parameters were calculated, and the processing results of the algorithm were compared under different noises. Finally, the algorithm was compared with 3 de-noise methods (Gaussian filter,Wavelet De-noise and Threshold De-noise). Experimental results indicate that the Peak Signal to Noise radio(PSNR) from the combined algorithm proposed is 6 db, 3 db and 8 db better than those of Gaussian filter, Wavelet De-noise and Threshold De-noise, respectively. It maintains good image edges and satisfies the image quality requirements of camera self-calibration in visual inspection systems for small modulus gears.

The drawbacks of the traditional visual comfort assessment metrics for stereoscopic images by using only global disparity features were analyzed. An objective visual discomfort prediction model of stereoscopic images was proposed based on visual saliency analysis. Firstly, an image saliency map and a depth saliency map were calculated by using covariance matrices and Sigma feature sets respectively according to the stereo visual attention mechanism of human eyes and the stereoscopic saliency map was obtained by combination of the two calculations. Then, visual discomfort perceptual features were obtained by using the stereoscopic saliency map as weighting. Finally, the relationship between the visual discomfort perceptual features and the subjective scores was established by constructing a visual discomfort prediction function with support-vector regression, and the objective visual comfort scores were predicted. Experimental results show that the Pearson Linear Correlation Coefficient (PLCC) index of the proposed method reaches 0.79, and the Spearman Rank Order Correlation Coefficient (SRCC) index reaches 0.81. These results indicate that the proposed model can achieve higher consistency with subjective perceptual of stereoscopic images, and is more consistent with human visual systems.

An experiment platform for laser active imaging and recognition was established based on the traditional laser active imaging system to investigate the target recognition after laser active imaging. The working mechanism of the platform was introduced and the Hu moment feature based BP neural network algorithm with double hidden layers and an experimental process were given. The target feature vector was consisted of seven invariant Hu moments. The BP neural network algorithm with double hidden layers including 136 weight coefficients was trained by 240 original sample libraries. The trained BP neural network algorithm was used to research a distance moving target in the dark condition, a model of 43 submachine gun, and a clear infrared laser active image was obtained. Experiment results show that statistical recognition probability is 68.87% for 2 740 frames of images at 450 m and 72.11% for 2 420 frames of images at 550 m. The corresponding recognition probabilities from rotation transformation are 80.05% and 84%, respectively, which is better than the results by affine transformation.

For the problems of low-resolution and serious effect from noises of infrared images, an approximate sparsity regularized infrared image super-resolution reconstruction algorithm (ASSR) based on K-SVD (Singular Value Decomposition) was proposed. In consideration of the noise effect from infrared images, an approximate sparsity representation model was first established. On the assumption that the low and high resolution image spaces hold a similar manifold, an approximate sparsity regularized K-SVD based dictionary learning method was proposed with approximate sparsity model and K-SVD method to solve the time-consuming problem of existing dictionary training process. Finally, the high-resolution infrared images were recovered by the high-resolution dictionary and the corresponding low-resolution group sparse coefficients. To verify the performance of the algorithm proposed, it was compared with those of the Sparsity Regularized Super-Resolution Reconstruction (SRSR) and Zeyde algorithm. Experimental results show that the proposed method can reduce the noises of infrared images, and can obtain excellent performance in super-resolution reconstruction.

As noise filtering of a star image has a high demand for reserving details of star edge, a new star map noise filtering method on a regularization influence function diffusion model was proposed based on Tukey diffusion model and modified Perona-Malik model. The boundary point set was extracted by a derivative operator and the map noise was processed by filtering with the space distribution characteristics of the original pixel and the noise pixel in the images. Moreover, the image edge was recovered by a given boundary condition. Due to avoiding Variance Stabilization(VS) transform,it could process the Gaussian noise directly. Simulation experiments on a common image and a star map with Gaussian noise show that this method has good capability of noise filtering and can effectively reserve the edges of feature images. Compared with common diffusion function algorithm, the average error is reduced by 13.6% and the Peak Signal to Noise Ratio(PSNR) is improved by 6.1%. Filtering performance of the proposed method is better than that of common diffusion function method, especially suitable for noise filtering of star maps.

A weighted Multiple Instance Learning(MIL) tracking method was proposed to improve the precision and real-time quality of online MIL tracking algorithm. First, target samples and background samples around a selected target were collected. Weak classifiers were generated by online learning the features of collected samples. In order to get K best weak classifiers, the maximum of samples′ log-likelihood was calculated. Every weak classifier was weighted differently and K weak classifiers were combined into a strong classifier. Finally, new unclassified samples were picked from the newly formed frame. The obtained strong classifier was used to separate the target and background. The classifying results were mapped into probabilities and the location of the sample with the largest probability was the target location wanted. Experiments on variant videos show that the accurate rate of the proposed algorithm is 93% and the average frame rate is 25 frame/s when the object size is 43 pixel×36 pixel. Compared with the original MILtracking algorithm, the real-time quality of proposed method increases by 67%.

Traditional Locally Linear Embedding (LLE) manifold learning algorithm uses Euclidean distance to measure neighbor points. However, Euclidean distance represents the straight line distance between two points and does not necessarily reflect the actual data distribution in a high dimension space, which leads to the instability of neighbor point selecttion. In order to solve this problem, an algorithm based on Correlation Neighbor LLE (CN-LLE) and Correlation Nearest Neighbor (CNN) classification is proposed. This algorithm uses the correlation coefficient of data to measure the neighbor points and to achieve more effective local reconstruction to extract the distinguishing character. Then, it uses the CNN to classify the reduced dimension data. The experiment results from KSC and Indian Pine hyperspectral remote sensing data sets show that the total accuracy of the proposed CN-LLE+CNN algorithm is improved by 2.11%-11.55% and the Kappa coefficient is improved 0.026-0.143 as compared with those of LLE, LLE+CNN and CN-LLE. The CN-LLE+CNN algorithm increases the probability of the same class neighbor, can extract the distinguishing characters of the same data effectively and has a better stability. This algorithm can effectively classify hyperspectral remote sensing data of ground objects.

As existing customized shoe-last technologies are lock of perfect foot-last matching algorithm and measurement indexes, this paper proposes a foot-last matching algorithm based on Fuzzy Analytic Hierarchy Process (FAHP). The technological paths were selected through calculating the Matching Degree (MD) value between the customers′ feet and the shoe-lasts from the database. First, eight foot-last characteristic parameters were extracted as the criterion layer of the FAHP to measure the matching of shoe lasts and the triangular fuzzy numbers were employed to calculate the MD value of the parameters between foot and shoe-last. Then, according to the effect of these characteristic parameters on shoe′s comfort and the difficulty of meeting these parameters in the deformation design process, two pairs of comparison matrices were established. The weights of these eight parameters were obtained by solving the corresponding eigenvectors of the maximum eigenvalue of the two matrices. Finally, the MD value was calculated and the best path was decided. With this method, a case was presented with a calculated MD value equal to 0.69. Compared to the threshold value 0.50 and the customized shoe-last standard value of 0.80, it points out that this shoe-last is not the customized one but a mother shoe-last that can be deformed for better fit and comfort. This method can join the customized shoe-last technological path based on shoe-last database and the direct path based on 3D foot data to increase the efficiency for customizing shoe-lasts and to reduce the cost.

An efficient intra prediction method was proposed to decrease the complexity of the video coding of new generation system. Some technologies used in the new generation standard of video coding (High Efficiency Video Coding, HEVC) were introduced, such as angular prediction modes, planar prediction mode, LM prediction mode and the Rate Distortion Optimization(RDO) method for selection of an optimum mode. Firstly, the Sum of Absolute Difference (SAD) was taken as a cost function to process residual errors to obtain optimal RDO initial candidate modes. Then, a simplified rate-distortion cost mode and a Most possible Prediction Mode(MPM) were used to obtain the RDO candidate mode, and the RDO was used to achieve the optimal mode with the least bit rate. Finally, the improved method was verified on the HM 4.0 platform of the HEVC measuring model. Extensive simulation results demonstrate that the proposed method is quite efficient for intra mode prediction speed-up. Compared with the method in HM 4.0, the proposed algorithm reduces the encoding time by 30.18% while the Peak Signal-to Noise Ratio(PSNR) remains almost the same (average reduce 0.06 dB). The bitrate is only reduced by 1.97% on average. Compared with the method in reference , the complexity and the bitrate are reduced by 11.45% and 0.46% respectively, and the PSNR increases by 0.01 dB.

According to the application requirement of information fusion for Digital Surface Model (DSM) data and visual remote sensing images, a two-level registration strategy based on Coherent Point Drift (CPD) algorithm and Relative Phase Histogram(RPH) was proposed to realize automatic registration of the data and images above. Firstly, Canny operator was used to extract edge points,and the extracted points were taken as inputs of CPT algorithm to implement a coarse matching and to obtain the initial matching points. Meanwhile, the scale factor was estimated. Then,the RPH, a robust descriptor characterized by invariance to image rotation and translation, was defined to represent the information of area changes. The RPH was also a scale-invariance under the support of coarse matching results. Finally, ring templates were defined in both images according to the scale factor and the fine registration of DSM data and remote sensing images was achieved by RPH measurement. Experimental results demonstrate that coarse matching results based on CPD are corrected efficiently after fine registration using RPH measurement. The registration error of proposed algorithm is only about two pixels even when images have perspective distortion. These data indicate that the method can satisfy the information fusion requirement of DSM data and visual remote sensing images.