In order to improve the intersection precision of optical measurement under the conditions of high altitude and far distance, the systematic error of optical measurement data must be accurately corrected, and the unpowered orbit characteristics of high altitude space craft can be used to realize the orbit restrain self–calibration. Firstly, the systematic error model of optical measurement data and the coordinate transition were analyzed. Then, the orbit restrain self-calibration algorithm of optical measurement data was set up. Finally, the simulation test in typical cases was implemented in order to verify the effectiveness of the method. The simulation results show that the systematic error of optical measurement data can be accurately corrected by the technology of orbit restrain self-calibration when the redundant observing data of multiple photoelectric theodolites are used in post data processing.

Currently a large number of remote sensing device use a Charge Coupled Device (CCD) sensor as its photographic equipment, and the ground resolution is one of most important performance parameters of the CCD sensor. For all types of CCD sensor, the tradition method to obtain the ground resolution is implemented through human eyes’ observation. Based on the imaging performance of the ground radial targets in the CCD sensors and combined with optical principle, a new method of automatically detecting the dynamic ground resolution of the CCD sensors was proposed. This new method has considered various factors which influence ground resolution. Besides, it has overcome the shortcoming of the traditional method. The experiment results validate the reliability and stability of this automatic detection method with different remote sensing images.

Evaluation and testing system of CCD video processor for space application is proposed, and used in the aerospace reliability screening of industrial grade video processor. By using Field Programmable Gate Array (FPGA) as control processing core, these functions are designed and implemented including multi-channel analog CCD signal generation，the video processor work mode control, communications, data acquisition and etc., The system functional composition and working principle were introduced in detail. Actual evaluation and testing system was completed with integrating the forty CCD video processors in a single board. The system has been successfully applied in the dynamic build-in screening test of industrial grade video processor XRD98L63, and the system is stable and reliable. The test conditions was being maintained at 85℃ and 192 hours power on operation, and the effective test was finished about the function and performance of the video processor used in the same batch. Test result is zero on the nonconforming product rate, satisfying the qualification that single batch screening nonconforming rate is less than 5%. Reliability screening of industrial grade components for the space load applications is implemented.

Sub-pixel centroid algorithm is widely used in spacecraft attitude measurement, astronomical observations, space precision image stabilization control system, space laser communication and other fields. As the detection module of spatial precision stabilization system, the fine guidance sensor detects the jitter of the guide star at a high speed of 100 frames per second, to provide compensation information for the vibration compensation mechanism. It is required that the algorithm has high accuracy as well as high speed real-time performance. In order to meet the needs of the fine guidance sensor, through simulations and experiments, firstly, analyze the influence of spot drift during exposure time on sub-pixel centroid locating accuracy. In order to obtain certain accuracy, the allowed maximum drift speed of spot must be calculated. Then the author put forward an improved real-time grayscale centroid algorithm, which uses Gaussian surface fitting, digital correlation method and grayscale centroid method in different stages of sub-pixel centroid locating. The simulation and experiment results prove that the method can receive balance between efficiency and accuracy.

Joint transform correlator is a technology used on space camera image motion measurement. The traditional optical joint transform correlator implemented by space light modulator is replaced by electronical joint transform correlator implemented by running the algorithm in a digital processor, which makes correlator adapt to the space radioactive environment and enhances the reliability. By doing massive simulation experiments, the influence of the size of the input images and the relative movement between two input images on the measurement precision of joint transform correlation is analyzed. Results of simulation experiments show that it is necessary to enlarge the size of the input images to increase the precision and sensitivity of joint transform correlator when designing a correlator, and enlarging size of the input images can also prevent singular values showing in the measurement results.

An image matching approach which integrates Maximally Stable Extremal Regions (MSER, Maximally Stable Extremal Regions) and Scale Invariant Feature Transformation (SIFT, Scale Invariant Feature Transformation) complementary invariant feature automatically is proposed for the tilt Remote Sensing image registration. Firstly, the images are coarsely matched by applying currently recognized as the best affine invariant MSER features, and the large deformation images are corrected initially. Then the images are fine matched by the matching ability of the SIFT descriptor joint the moments based on the coarse matching. The remote sensing image matching accuracy is improved through the above two steps, especially, the more pronounced effect on the large tilt images. Finally, the UAV(Unmanned Aerial Vehicle) image experiments show that this algorithm is more effective than SIFT algorithm in the affine invariant and matching the correct rate.

Aiming at higher desire of robust and veracity brought by increasing variety of remote sensing images, by analyzing the problem that the decrease of original date’s size and the loss of original information in the matrix’s decomposition exist in the arithmetic, based on Independent Component Analysis (ICA, Independent Component Analysis) change detection, an improved decompose method with Undecimated Discrete Wavelet Transform (UDWT, Undecimated Discrete Wavelet Transform) was proposed. For removing the influence of the noise to detection result, the segmentation method of object-oriented was used to get the image objects, and distilled the shape character of the image objects to replace the original images. Finally, the robust and veracity of proposed method has been proved through simulation.

High area-to-mass ratio space debris currently poses an increasing hazard to active satellites in orbit and manned space activities. Due to the difficulties in recognition and cataloging of high area-to-mass space debris, a method based on spectroscopic observations is proposed. This method corrects atmospheric extinction and the impact of telescope optical system on the basis of image preprocessing, extracts space debris reflectance spectroscopy, then compares with the spectral curves of sample materials and recognizes surface materials of high area-to-mass ratio space debris. Results of spectroscopic observations show that it will be fairly accurate if high area-to-mass ratio space debris is composed of a single material, such as aluminum and white paint, and the correlation coefficients of aluminum and white paint are approximately 0.9.

Generally, two star trackers with small FOV (field-of-view) are used to maintain a high accuracy for micro-satellite’s attitude determination. Due to the small FOV, a sufficient number of stars for identification cannot be always captured. Combined images technique can be used to ease this problem, but its efficiency is highly affected by the mounting angle between two star trackers. The role made by the mounting angle is analyzed and simulated here. Results show that the number of guide starpairs matched to the reference angular distance changes like the sine function as the reference angular distance changes, and it reaches its extremum when the angular distance is about 90 degrees. And it increases as the tolerance increase. The extremum difference of the numbers of guide starpairs is highly affected by the tolerance. Therefore, the mounting angle should not be 90 degrees in combined images technique. The efficiency of the identification is higher as the mounting angle is smaller.

The long focal length remote camera frame structure has a large primary and secondary mirror magnification ratio, structure stability and other issues which are difficult to be designed. For this type of camera structural design problems, by analyzing a detailed the structural design input of the camera, we propose a double-layer 14 truss structure design. The finite element analysis shows that the first order natural frequency is 114.97 Hz, and secondary mirror substrate around the X-axis angle is 5", along the Y-axis maximum rigid body displacement 0.03 mm. By testing truss structure and dynamics of the static rollover, the test results show that the maximum angle truss structure changes in static flip 6", and the maximum angle changes dynamically loaded 6.5" input indicators meet the design requirements.

Aimed at the problems of partial occlusion, background interference and other issues in visual object tracking technology, the concept of superpixel is proposed. Firstly, Simple Linear Iterative Clustering (SLIC) method is used to segment the target and the surrounding area into superpixels based on texture feature represented by local entropy and color feature. Then confidence map is established by the appearance of training model to endow each pixel with the confidence value. Updating the appearance model ensures the tracking process, which can adapt to the changes of target and background. Finally, the location of the target is found according to the confidence map. The experimental results show that the proposed tracking algorithm can effectively find the target position in the case of partial occlusion or background interference.

For the problem of ship target fast detection and speed estimation of space-flight image, this paper firstly analyzes the feature of sea-land background image. Based on the pixel point gradient extraction and edge detection technique, a detecting algorithm based on gradient map three filtration is proposed. This algorithm can realize the segmentation and extraction of sea area and ship target. Then, by the Fourier fitting model, this paper puts forward a period estimation method of Kelvin wake to calculate the speed of ship. The error range and error source are analyzed in the end.

Applying discrete optical component technology, a novel Reconfigurable Optical Add/Drop Multiplexer (ROADM) based on the four-fiber collimator and thin film filter is designed. Four ports, including input port, drop port, add port and output port, are arranged on the same side of ROADM. Simulations to the designed ROADM, as well as bit error rate and eye diagram in networking, are performed using Optisystem. Simulation results show that the designed ROADM has loss of 2 dB and balanced channel gain. In networking, the bit error rate is less than 10-9 and Q value is more than 6 with clear eye diagrams at speed of 2.5 Gb/s and distance of 75 km, which verifies that the designed ROADM is suitable for the metropolitan area network system.

Maximum detection range is an important parameter for evaluating the performance of photon ladar. In this paper, the maximum detection range of direct-detection pulse photon ladar which uses Geiger-mode Avalanche Photodiode (GM-APD) array as the detector is investigated. Based on the laser radar equation and the model of the minimum acceptable detection probability, and assuming the primary electrons triggered by the echo photons in the GM-APD pixel obey Poisson distribution, the theoretical model estimating the maximum detection range is proposed. By using the system design parameters, the influence of five main factors on the maximum detection range is investigated. The results show that the stronger emitted pulse energy, lower noise level, front echo position in the range gate, large atmospheric transmission, and high target reflectivity can result in larger maximum detection range. When the minimum acceptable detection probability is selected to 0.9, by using emitted laser pulse with pulse width 5 ns and energy 50 μJ, the system maximum detection range more than 1 km can be achieved. At the same time, it is important to select the minimum acceptable detection probability for producing a high system detection performance.

Extrinsic calibration of Lidar is necessary for vehicle-mounted 3D reconstruction system using multiple Lidars. Concerned on the extrinsic calibration of Lidar, as the scanning point of Lidar is invisible and scanning mode is single-lined, according to the 3D frame transforming model based on space vectors, a new calibration method is proposed, in which a trihedron target is adopted. The proposed method, which contains reconstruction of the target, segmentation of plane feature and extraction of corresponding vectors using the Random Sample Consensus (RANSAC) algorithm, solving the extrinsic parameters using the transforming model of 3D frame based on space vectors, was applied to extrinsic calibration of Lidar in a 3D reconstruction system. The effectiveness and precision of the method are proved by simulation and 3D reconstruction importing the calibration results.