In Inverse Synthetic Aperture Radar (ISAR) imaging, phase error caused by three-dimensional rotation is relevant to the position of the scatterer, so it is difficult to use traditional phase autofocus algorithms to complete phase compensation, in which the uniform phase correction function is applied. In order to resolve this problem, a three-dimensional rotation detection method is put forward to complete the selection of imaging times, in which the motion state of target is two-dimensional rotation. In this method, the phases of two arbitrary scatterers are estimated by adaptive Gaussian chirplet decomposition (AGCD) fast algorithm, and the target rotation state is obtained by measuring the non-linearity of the two phases, which means those intervals that the target just has two-dimensional rotation are selected to obtain the ISAR images. Numerical simulation results prove its good efficiency.

To improve the performance of the imaging on the maneuvering target, a high-resolution imaging method is proposed via airborne multiple-input and multiple-output (MIMO) radar based on a hybrid sampling scheme, in which the single snapshot of MIMO radar and the synthetic aperture of SAR are combined. Different from the classical Synthetic Aperture Radar (SAR), the novel method only compensates the movement by using the geographic information between the target and the airborne radar, instead of the Doppler information. Simulation results validate the effectiveness of the proposed method.

Object detection has been widely used in smart video surveillance system, and many algorithms have been developed. However, these algorithms are sensitive to illumination. In this paper, a robust method has been proposed, which is based on the difference the edge maps between the background image and the image at present in the video. The outline of moving objects is drawn, and then the moving targets are detected and localized. Experiments show that this method is robust to illumination, can detect moving object correctly and be easily adopted in fixed camera environment with real-time application.

Traditional CamShift algorithm has been widely applied in the field of video tracking, but it tends to fail in the complex background and occlusion condition. In this paper, we choose color, texture, and the target motion information as features based on traditional CamShift algorithm, and constantly predict the target state of motion combined with the Kalman filter, in order to improve tracking accuracy in the complex background. In the event of occlusion, we use least squares fitting and extrapolation to predict the target location through the priori motion information of the target before occlusion, and re-capture the target after occlusion. The experimental results show that the algorithm can still track the target well in the case of complex background and short-term occlusion and have good real time ability.

Based on FPGA with an embedded soft-core MicroBlaze, an information processing system for sun sensor is designed. Soft-core MicroBlaze is employed to implement centroid extraction and attitude conversion. The other resources are used to realize the design of logic modules, such as sun sensor driving, image storage and communication interface. A scan-based centroid extraction algorithm is proposed according to the characteristic of MicroBlaze soft-core. The result shows that the high precision of centroid extraction and attitude conversion is achieved by using single precision floating point number in the MicroBlaze soft-core. The scan-based centroid extraction algorithm process is simple and occupies less resource. In the sun sensor based on System on Programmable Chip (SOPC), co-processors such as DSP or ARM are not needed, so complexity of hardware is decreased and the integrity and performance are improved.

To satisfy rigid performance specifications, a feedback control was presented for zoom optical lens plants. In order to improve the angle measurement accuracy of the star sensor, a novel approach is proposed as the model updating and angle measurement accuracy testing of the star sensor using system identification. First, the theoretical measuring model of the star sensor and the spatial relation between image coordinates of the star sensor and target are analyzed. Secondly the basic principle and the measurement model are given for getting more accurate measuring model by updating the model of the star sensor. The correction model of the star sensor is established by means of system identification technique. For improving the angle measurement accuracy of star sensor，the CCD image plane of star sensor is divided into multiple regions, and the model of every region is built by system identification individually. The experiment is conducted with a star sensor. The experimental results show that the angle measurement accuracy of x and y directions is 1.68″ and 1.91″ after calibration, but 17.43″ and 23.46″ before calibration. The results show that the angle measurement accuracy of the star sensor is improved with this method.

According to the requirements of PCF splice system that the microscope objectives must work long distance, high magnification and high resolution, special optical lens is designed to get PCF information of end face, which is optimized through the ZEMAX simulation. The optical lens has 40×high magnification, 5 mm long working distance, 1 μm high resolution, and 500 μm×500 μm field. Finally, it is proved that the lens meet all the requirements by the experiments.

To assure the effectiveness of the optical system in an aerial camera and high image quality, thermal design was taken according to the thermal environment and the structure characteristic of the camera. Passive control methods such as thermal insulation were taken to overreach the thermal time constant and to reduce the sensitivity of the optical system to the external thermal environment. Heat transfer model and thermal resistant network model of the lens and the window unit were created, and the highest thermal leakages under extreme working conditions were analyzed and calculated. The heating power for maintaining the optical system temperature was obtained. According to the calculating results, the heating loops and heating power were designed. Steady-state and transient simulation was taken based on the thermal control methods and the work condition, and the heating powers were optimized. The steady-state temperature distributions of the lens and optical window were in the range of (20±1)℃, which indicated that the heat dissipation was well compensated. The transient results showed that the temperature of optical system was between 17.5℃~20.5℃, which met the thermal control index. Through the analysis, a theoretical warrant for reliability of optical system and optimization of thermal design was provided.

The focus mirror is a cell of space camera structure’s design. The imaging quality of space camera depends on its structure design directly. Based on a wide cover camera, the focus mirror has long figure of length-breadth ratio 3:1, which makes the design of supporting structure more difficult. For insuring the imaging quality of focus mirror optical surface all the time, the flexible supporting structure has to be provided with dynamics and statics, as well as smaller mass, higher ratio-rigidity, well machining and assembling capability. By analyzing, focus mirror with the flexible supporting structure can meet quality targets, whose surface quality is 1/50λ and first mode is 275 Hz.

In order to acquire polarization information of target and background, hyperspectral polarization image system based on Liquid Crystal Variable Retarders (LCVR) and Acousto-optic Tunable Filter (AOTF) was designed to improve the accuracy of detection of target and background. Firstly, the principle of polarization detection and the work principle of AOTF were described. And then the structure of the system was given. In the mean while, the parameter of optic component was distributed reasonably. Finally, the hyperspectral polarization images captured by the system were analyzed through the polarization information process software programmed by MATLAB. The calculated results show that the polarimetric and spectral characteristics of target are obvious. The system is of significance for object detection and recognition.

A new kind of strain measurement Hollow-core Photonic Crystal Fiber (HCPCF) Fabry-Perot (F-P) interferometer sensor is presented. One end of the HCPCF is fused with the single-mode fiber to form the reflecting surface 1. The other end of HCPCF completely collapses to form the reflecting surface 2 by the electrode discharge in the welding machine. So the new F-P interferometer sensor with HCPCF cavity is constituted. The experimental results show that the strain sensitivity of the sensor cavity length of 2 mm at room temperature is 3.1 nm/με, the linearity is 0.999 2 and limit cavity length change is 3 827.3 nm. In the range of 0 ~ 150 ℃, the change of cavity length is about 0.17 μm. Theoretical and experimental results show that the new sensor has a simple fabrication process, high strain sensitivity, low temperature sensitivity and no hysteresis.

Different from traditional sensor, FBG sensor has particular detective probe length in different angle of sensor because the sensitivity of FBG in axial direction is much better than other directions. Thus the layout angle of FBG sensor can affect the performance of FBG sensor network greatly. A detection model is proposed for FBG sensor which fits its feature based on probability model, and the correctness of the model is verified by experiment. Then particle swarm optimization algorithm is used to optimize the placement of FBG sensor network. Finally, the results of optimization method are compared with those of optimization method not considering the layout angle of sensor. It is indicated that the performance of sensor network is greatly improved by considering the layout angle in placement.

The fiber-optic sensor based on Mach-Zehnder interferometer is used in the perimeter alarm system. It can be used for alarming the vibration signal which occurs in the sensing area and has a very high sensitivity. In order to reduce the false alarm rate of perimeter alarm system，for signal processing of perimeter alarm system，by applying the wavelet transform method, the voltage signal outputted by the perimeter alarm system is identified, which could not only filter the noise signal but also retain mutant signal and distinguish very well the vibrations produced by deliberate invasion and rain to reduce false alarm rates of the perimeter alarm system and realize the deliberate invasion positioning. It is a breakthrough for the perimeter alarm system to realize engineering application. A large number of experimental results showed that it could reflect the singular value of measurement signals and remarkably reduce the false alarm rate of perimeter alarm system based on wavelet transform method to analyze signal of perimeter alarm system.

A four-channel single-mode fiber optic rotary joint is designed, which is based on transmission theory of Dove prism. The optical signal coupling is implemented applying bevel gear. Furthermore, a scheme of the coupling adjusting is designed. The coupling loss is also analyzed, which is brought by the error between optical axis and rotary axis of Dove prism so that the installation precision of Dove prism is confirmed. Finally, the technical indicator of four-channel single-mode fiber optic rotary joint has achieved the level of congener foreign products. And this design can be expanded to eight-channel with primary configuration size by the enough optical aperture of Dove prism.

Revolving body measuring machine has been widely used in the measurement of revolving parts with its high efficiency and precision. However, due to its own characteristics, measurement accuracy is affected by the temperature and the drift error is up to 120 μm. In order to solve this problem, a method of online thermal error compensation was presented. The method can acquire the offset and tile parameters of the gauging spindle by using the bidirectional measurement, and then use these parameters to correct the diameter of each elevation. The method is simple and easy to use, and significantly improves the measurement accuracy. The experiments show that this compensation method allows the measurement results stability error of the size to reduce to about 15 μm from 136 μm. And the measurement stability is greatly improved.

In 3D bullet trail measurement system, in order to obtain high measurement accuracy, a sixteen-step phase-shifting technique fringe image processing algorithms is presented. First, the principle of phase distribution and achievement in 3D morphology is analyzed. And then, adaptive Wiener filter is used to remove partial noise in collected bullet trail images and sym4 wavelet decomposition is used to process the original image by three-layer to remove system noise. The proposed system introduces three-layer decomposition of the wavelet coefficients based on soft threshold to calculate phase combined with sixteen-step phase-shifting technique. The results show that the phase curve of bullet fringe is smoother, the maximum height deviation of original fringe image is 1.631 μm, and the deviation is 0.867 4 μm by sixteen-step phase-shifting, which improves the system accuracy.

A calibration method for line structured light vision sensor with large Field of View (FOV) by using 1D target with unconstrained combination is proposed. Several 1D targets, each of which has at least 3 feature-points aligned on a feature-line, are combined freely according to the measuring range of the sensor. All primitive parameters of the line structured light vision sensor are determined with observation of the target shown at a few (at least two) different viewpoints. The intrinsic parameters are solved using the invariability of angle between every two one-dimensional targets in different views. The coordinates of feature-points in the camera coordinate frame are computed in accordance with the property of the vanishing point and the known distance between the feature points. The coordinates of the control points which are the intersection points of the light plane and the feature lines are obtained based on the cross-ratio invariability. The light plane is fitted with at least three nonlinear control points. The experimental results show that the proposed approach can achieve the same calibration accuracy as the planar-target-calibration approach. Compared with existing methods, the proposed method is fast with high accuracy, which is suitable for the field calibration of line structured light vision sensor with large FOV.

An improved method of laser projection photograph to judge the situation of pipeline in service is put forward. The algorithm detects the height of protuberance (which is also called obstruction) through the procedure of track detection which is finished by the combination of laser feature analysis and the comparison method. By Otsu algorithm filtering, parameters of circle are got with least square method. Finally, obstruction height is obtained through obstruction-height table which is calculated off-line. There is no strict light requirement to the pipeline image avoiding the original system’s observation and tests are not synchronous. Three advantages are demonstrated by MATLAB experiments which are obviously better than the original design: higher accuracy, better real-time performance and nice robustness. The average operation time of each frame is less than 0.5 seconds, and the range of height error is 2 mm. Images of almost all situations can be processed through the algorithm.

The normalized cross correlation algorithm is a classic image matching algorithm. The method is simple and has a high matching probability. However, its disadvantage is enormous computation, which is difficult to meet the requirements of real-time. In this paper, first, a method for reducing the computation is proposed. By constructing two searching matrix from the reference image, the searching path of the real-time image is simplified. It completes the matching just along one translation direction and can avoid repetitious computation of the image energy easily based on an iterative operation between the two adjacent sub-based images. Then, the fast matching algorithm is proposed by combining the method and the bounded partial correlation (BPC) algorithm. It improves the computational speed of the algorithm by reducing computation from two aspects. Final, the experiment results show the superiorities of the algorithm.

Fuzzy C-Means algorithm is dependent on the initial value, resulting in easy to fall into the disadvantage of the local optimum value. A combination of quantum ant colony algorithm and FCM clustering algorithm is put forward. Firstly, the original center and numbers of cluster of the image are determined by using global type, robustness and advantages of fast convergence of quantum ant colony algorithm. Secondly, the obtained results are taken as the initial parameters for FCM clustering algorithm, and then the medical image is divided by using FCM clustering algorithm. It is proved that the method has reduced the dependence of FCM clustering algorithm on initial parameters effectively， overcome the shortcomings of easy falling into the local minimum of both algorithms，and greatly improved dividing speed and accuracy, which is simulated by real experiment.

Aiming to improve the point pattern matching accuracy with graphical models, an improved point pattern matching algorithm is proposed using dynamic generating graphical model. First, mixed Gaussian distribution is applied in similarity measure of dynamic generating graphical model to improve the multi-feature ability of model，which make the matching results more robust to noise. Second, a dummy point is introduced in the target point set and the similarity measure including the dummy point is provided. A point in the template would match the dummy point when the similarity measure of a template point with a target point is less than that of the template point and the dummy point, which can reduce the mismatching rate caused by outliers. Experimental results with simulated and real images show that the proposed algorithm is more robust to noise and outlier, and compared with the traditional methods, matching accuracy is improved.

With miniaturization of the UAV of optoelectronic pod, the requirements of miniaturization and rapidity for its zoom system is raised. A small segmented zoom system is designed. The focusing components include stepper motor and permeability type of photo interrupter, and the hardware circuit of system and focus method is designed, which achieves the rapid segmented zoom of the optical lens and the real-time output of focal-length. The focal point position and focal length of system are calibrated by off-line methods. Tenengrad function, Brenner function and square gradient function are utilized to evaluate comprehensively during the calibration process of the focal point position. At the same time，it adopt auto collimation measured focus instrument to calibrate accurately the focal length of lens. Finally, it is achieved that this zoom system weighs less than 100 grams, the errors of focal-length is less than 1%, and the switching time between short focal and long focal is less than 1.7 seconds.

A new method of high-precision homing of getting the optimal homing path automatically has been put forward, and a high-precision visual optical robot system with multi-phalanges has been made. The principle of this method is to compare the position where the robot stops with where the home photosensor is set, thus getting the optimal homing path automatically. The home point depends on signals from the home photosensor and the photoelectric encoder. This robot system works stably in industrial works, and has up to 0.02 mm precision and up to 5.2 m/s speed. The experiments and test results show that, with this new method, the homing time could be as short as 10s for each axes, within 2 pulse’ homing error. As far as we know, it has never been reported home and abroad for this method or application in visual optical robot system with multi-phalanges successfully.