Considering the requirement of system design on evaluating the accuracy of Helmet Mounted Sight (HMS), it is necessary to determine the attitude of a helmet in 6 Degree of Freedom (DOF). All parameters regarding to the helmet characteristics such as activity range, maximal Field of View (FOV), position and direction of sight line, relevant attitude variations, etc, need to be calculated accordingly. Two cameras are mounted in the cabin of a helicopter, and images acquired from different directions are processed simultaneously. A mathematical model is derived and a monocular measurement method is implemented through the introduction of pyramid principle, space resection algorithm and attitude detection method based on exterior orientation elements. Based on the data fusion of multi-Sensor, optimal solutions are obtained by means of the further studies on processing the helmet pose data.

Workspace Measurement Position System (wMPS) is a newly developed system based on multi-directional positioning principle. Initially, the angular measurement model was proposed for angle uncertainty of the transmitter. The uncertainties in the vertical and horizontal angles were analyzed and a feasible method for estimating the uncertainty of parameters was proposed. Then, the uncertainty of parameters was propagated from the angular measurement model using Monte Carlo simulation and the angular uncertainty distribution was determined by the simulation. Finally, horizontal angle uncertainty evaluation platform based on polygonal prism and collimator was designed by using angle dividing table as angle reference. Experiments were then carried out to determine the actual uncertainty in the horizontal angle. Results show that the platform is effective and horizontal angle uncertainty is about 2.2″ in the working space.

To improve the real time performance and robustness, lane coordination detection is executed, which detects the lane parameter by adopting the global extraction based on Hough transformation and the local windows extraction with the help of the lane parameter confidence interval and the Kalman filter. Image preprocessing is conducted including the improved fast median filter, the lane feature filter, the gradient angular histogram selection, and the lane connectivity analysis to cut the computational expense and enhance the lane edge feature after the lane region of interest is defined. Real vehicle experiments show that the proposed method can run at an average speed of 25 frames per second on a Pentium (R) D 2.00 GHz CPU, and the accuracy can reach 97.2%. Meanwhile, it can robustly detect the lane even if there are some interference factors in the road such as shadow, vehicle and landmark etc., as well as fuzzy lane boundaries and relatively weak contrast.

A measurement method of the spacial coordinates using camera calibration based on Genetic Algorithm (GA) and Least Square Support Vector Machine (LSSVM) was proposed for improving the traditional optical measurement method in range. First of all, the idea of camera calibration using LSSVM was presented, and its application in range measurement was discussed. The two crucial problems of choosing the training samples and confirming the samples capacity were solved by simulation analysis in range application. Finally, the measurement method of camera calibration using LSSVM was validated by two tests in range. The result shows that precision of the method is good and it has the characteristics of the simple principle, high precision, easy implementation and data processing compared with the traditional optical measurement method in range, which has important application values.

In order to improve the level of camera automatic calibration, a general algorithm for matching corners and their world coordinate is proposed on account of kinds of board. Major factors of influence on corners’ match are analyzed, lens distortion and geometric deformable caused by projection transformation. The algorithm searches the best projected angle with the “sum of Interval variance”. The algorithm chooses the style of interval partition automatically and corners are classified twice. The capability for resisting geometric deformable and projection transformation is testified through simulation. That the algorithm can match corners accurately and steadily, which is proved in real experiment. The algorithm as an independent module has been used in solution and improves the automatic level of calibration obviously.

In order to accurately measure the target accuracy of the projectile's position, this article used the intersection measuring system with dual liner CCD and introduced the working principles of this system, and the calculated formula of target coordinates had been demonstrated. We analyzed the components and the positioning ways of each measurement module, on the basis of which the measuring system had been established. The target accuracy of the projectile's position is 0.041 7 m (Direction error probable) and 0.031 9 m (Level error probable). The measured value compared with the calibration value in the mm level difference, indicates that the system accuracy is ideal. So the development of this measuring system is successful, and it was able to accurately measure the target accuracy of the projectile's position.

A dual laser heterodyne velocimetry is reported. Two laser beams from different sources are respectively employed in detection and local reference. The velocity of moving surface is measured by means of Doppler effect. Dual laser heterodyne velocimetry can run in frequency down conversion mode or frequency up conversion mode. Operation mode is determined by the frequency difference of the detecting laser and the reference laser. In frequency down conversion mode, the velocimetry converts high-velocity signal’s frequency down, and then one can use a normal high-bandwidth oscillograph to measure velocities higher than 10 km/s instead of using an ultrahigh-bandwidth oscillograph, and solve the problem in which the measurements of ultrahigh-velocities depend upon ultrahigh-bandwidth oscillographs. In frequency down conversion mode, the frequency of low-velocity signal is converted up, and the measurement’s time resolution and precision increase.

It is very difficult to detect the small target over water in the marine environment because of the complexity of the water movement and the physical field produced by the water interacted with environment. So we mainly studied foreground segmentation for small target in visual image based on Markov Random Fields (MRF). A foreground segmentation method was proposed based on kernel function and MRF. In this method, the special and temporal correlation is used in the kernel function between neighbor pixels. We took the probability distribution of the kernel function method as the observed value of the MRF and get the energy function of the MRF. Results show that our method is applicable to low speed small target segmentation in sea image.

Optimum deployment in double-plane passive location system is concerned. Giving the distance of target and my plane and in the sense of the minimum Circular Error Probability (CEP), some significant conclusions are given. The research indicates that the optimum sensors deployment is dependent on the distance of two planes and the cut angle of two planes and target. The optimum deployment should satisfy that the two planes distance D is 1~1.2 times of the distance of my plane and target D1, and the formed cut angle β is in 90°-θ1/2<β<90°. These conclusions can be applied for reference in optimal deployment of double passive sensors to obtain high location accuracy.

To improve tracking performance in bearings-only target tracking problems, a maneuver-adaptive filtering algorithm was proposed in this work. The proposed algorithm based on “current” statistical model adjusted maneuver indices (maneuver frequency and extrema in random acceleration distribution) in the model adaptively by monitoring the filter’s innovation sequence. Thus, the maneuver-adaptive filtering algorithm was able to adjust object adaptively in accordance with practical target motion situation and track time-variant maneuvering target effectively. Simulation results show that the proposed algorithm can achieve high tracking accuracy against weak maneuvering target and high tracking ability against strong maneuvering target.

Kernel function is a normal method for image categorization to map high-dimension features into low-dimension spaces. Most state-of-art researches integrated kernels into Support Vector Machine (SVM) classifiers to solve classification problems. A novel Real Adaboost framework is proposed to involve kernel method to deal with classification. Hierarchical features PHOG and PHOW are used to describe shape and appearance information in multiple image scales first. Kernel function is then employed for evaluating features’ distance and constructing linear learner pool in kernel space. Real Adaboost is finally used to linear learners to obtain final image classifier. Experimental results show that our method significantly improves the image categorization performance.

The photoelectric tracker is interfered by carrier’s swaying which is the key factor of preventing the stabilization and the tracking precision from being improved. Firstly, based on control theory, this article compared direct-stabilization with indirect-stabilization. Secondly, the mathematic model of indirect-stabilization on two-axis optoelectronic tracking platform is established. Finally, a two-axis optoelectronic tracker used indirect-stabilization method to stabilize the tracking platform. Furthermore, the servo system of the two-axis optoelectronic tracker was designed and used effectively.

Adopting the moving object detection algorithm of moving background, an improved three-step search algorithm is proposed. The proposed algorithm can effectively accelerate motion-vectors search and reduce computational complexity while keeping up high search accuracy. Firstly，the same background of three continuous images are fixed to the same position of the same image through the global motion compensation. Secondly, three continuous edge images information are obtained by edge extracting, and the motion information is detected by three-frame-difference operation. Finally, morphologic close-algorithm and morphologic fill-algorithm are used to extract the moving objects. Experimental results demonstrate that this method can accurately extract moving objects, and has strong robustness.

Taking amounts of tests to camera comprehensive management unit is one important segment in aerospace optical camera development. Traditional test system has disadvantages for its single function and lacking of ability to simulate the whole working schedule within on-orbit flight. This paper goes from actual testing angle and put forward a method of establishing new kind of simulation orbit test platform for aerospace optical camera, which is based on DSP hardware and VC software for telemetry and remote control. Then it introduces hardware components and working principles of this platform. Meanwhile, critical software reference codes are provided. Through detailed test in an aerospace camera, it shows that this platform can simulate data stream in arbitrary moment of camera comprehensive management unit during on-orbit flight. And it can record remote measuring parameters in testing process. These functions demonstrate that it can validate the function and performance of camera comprehensive management unit, which achieves the objective of aerospace camera ground test and possesses practical application value in projects.

A control system of multi-detector imaging based on CAN bus has been implemented on opto-electronic imaging tracking and measuring device. The field control nodes use DSP chip TMS320F2812 to support the imaging control system, including motor control, sensor control, temperature measurement and control, etc. A real-time communication protocol is designed to meet the data transmission on the system control network, and this protocol can be applied to other device with little change. On the remote host computer, a main control software is programmed to monitor and control the imaging system. Test results and application in devices show that this system is stable and reliable, and it can be promoted to more opto-electronic imaging tracking and measurement devices.

Since wavelet transform can not fully describe facial curves features, a face recognition algorithm based on curvelet domain and Kernel Principal Component Analysis (KPCA) is proposed. Using multi-scale, multi-directional curvelet transform to extract image features not only has higher approximation accuracy and better sparse expression, but also can effectively express the singularity along the curve. Then, KPCA is used to project curvelet feature coefficient into the more expressive kernel space. Finally, the nearest method is adopted for classification. The results indicate this algorithm has better effect on image dimension reduction and face recognition rate in the JAFFE face database, ORL face database and FERET face database.

Second-order Local Derivative Pattern (LDP) is a general framework to encode directional pattern features based on local first-order derivative variations. Different from Local Binary Pattern (LBP), the second-order derivative pattern extracts local information by encoding various distinctive spatial relationships contained in a given local region and thus it can capture more detailed information than the first-order local pattern used in LBP. A new algorithm based on Fusion of Second-order Local Derivative Pattern in Gabor characteristic (FG2LDP) for face recognition is proposed. According to the good spatial position and orientation of Gabor filter, a Gabor filter with four frequencies and six orientations is firstly applied to filter face images. Secondly, the weight of each frequency and orientation is adaptively estimated for subsequent fusion. Thirdly, the second-order local derivative information of filtered images is extracted and low dimensional features in every direction are extracted by Principal Component Analysis (PCA). Finally, all the likelihoods in every frequency and orientation are fused together for the final recognition result. Experiments show that our method can effectively extract local features. It can consistently outperform other recognition methods based on PCA, Linear Discriminant Analysis (LDA), LBP and Fusion of Second-order Local Derivative Pattern (F2LDP) in gray images.

Feature extraction is a critical step for low contrast palmprint recognition. According to the characteristics with obvious palmprint texture features, a block Radon transform method is presented for palmprint feature extraction. Firstly, the method denoises region of interest of the palmprint and reduces dimension with the first-level wavelet decomposition. Then it blocks the low-frequency sub-image to delineate local primary textures. At last, after all the sub-block images are transformed during 70°～140° by Radon transform method, the line integrals obtained constitute feature vector for the image. The method was tested on the basis of UST palmprint image database. From the experimental results of 94% recognition rate, the method can satisfy the application for authentication systems without excessive demands for collection images.

In order to control rotary angle of reflector accurately in the Fast-steering Mirror (FSM) system, a specialized grating sensor used for measuring the position of reflector to offer feedback information for servo controlling system was designed. On the basis of application requirements of grating sensor in the fast-steering mirror system, small slip track, pattern of scale gratings, pattern of index gratings, form of absolute zero code, moving index gratings and styles of measure probes were designed and chosen respectively on technology principle of grating sensor. Then, the grating sensor was tested after finely manufacturing, assembling and adjusting. The results show that measure length of the grating sensor is about ± 2.5 millimeters, its response frequency is about 1 000 Hz, its measure error is less than 2 microns, its measure differentiate is less than 0.06 microns and it can export absolute zero. Applied results of the grating sensor show that the sensor which has high precision, excellent resolution and powerful dependability can satisfy application requirements of the fast-steering mirror system.

Illuminance detecting of the headlamp has become an obligatory step to keep the traffic safety. Now the full screen video method is used in the production line of headlamps of most relevant industries. This article describes an improving design proposal based on the full screen video method to solve its large floor area and the alignment of its center reference point "HV" lowering system measuring precision problems. By analyzing the optical character of Fresnel Lenses and globe lens, an optical simulation software named "LightTools" is used to set up the whole system model. Laboratory result finally shows globe lens in the improved system is better than Fresnel Lenses in the aspect of improving system measuring precision. Besides, this system has a little floor area, and the assembling light property of globe lens can also easily regulate the center reference point "HV". In view of automobile market, this system must have a broad prospect.

A method by controlling the primary aberration of each surface in the system based on Seidel aberration theory is proposed for reducing system tolerance sensitivity. First of all, it illustrates the principle of small aberrations balancing, and then the relation of the Seidel aberration theory and tolerance sensitivity is indicated by theoretical formula. At last, we enumerate an example which is the optical design of objective lens of aerial camera and make tolerances analysis both on the compensation of big aberration and small aberration. The results show looser tolerances distribution, better stability and great reduction of the cost on the compensation of small aberration.

Diffraction grating is the core part of spectrum instruments. To get a good performance of the instruments, different structure should be designed with different type of the grating. A spectrograph, which works in the spectrum range from 340 nm to 800 nm, was designed, whose the resolution is higher than 15nm, and the dispersion size is 28.71 mm on the focal plane. According to comparison of structure of the common spectrographs, the flat field holographic concave grating structure with many advantages was chosen. The long pass filter was used to constrain the secondary spectrum, and the optical source was also considered. As a result, the resolution of the whole system is better than 10 nm, and the size is only 190 mm×15 mm×60 mm. The flat concave-grating can be got from the market, which greatly decreases the cost of the product. Besides, only a grating can act as the spectrometer system, which can make the system easily assembly and very convenient for mass production.

In the bonding structure of the optical-mechanical system, for researching the influence on lens of the adhesive’s curing shrinkage, the viscoelastic model is used for adhesive’s simulation, and the theory solution can be gotten from the constitutive equation. The method of equivalent temperature and the Finite Element Analysis (FEA) soft ANSYS is used for simulating the shrinkage to analyze the influence on the surface figure error. Compared with the elastic model, the viscoelastic model has its advantages. Change the curing time for analyzing the influence on the lens. The analysis result shows that the simulation result fit the theory solution well, and the viscoelastic model can better describe the relationship between the time and the final shrinkage stress. Moreover, it can better simulate the generation of shrinkage stress. In regard to the same adhesive, through prolonging the curing time properly, there is the smaller influence on the surface figure error of the lens, so it can prolong the time for reducing the shrinkage stress.

A horizontal placing method for the lens of high-precision interferometer is given according to its operating mode. Using Ansys Workbench finite element software, simulation and analysis are carried out on the deformation of mirror surface which is caused by gravity and the support structure. Based on the Finite Element Analysis (FEA) for opto-mechanical structure, optimize the mechanical design of the lens repeatedly, so that the systematic errors caused by support structure get to minimization. Fit deformed mirror surface with Zernike polynomial as an interface tool, and evaluate the effect of support structure on optical performance. The analysis results show that the RMS of aberration of the interferometer lens is less than 1/50λ which can be fulfilled with the image quality demand under the support method.