Research On The Method Of Aircraft Pose Surveying From Image Sequences Obtained By Photoelectric Theodolite

"It is necessary to measure everything that can be measured and to try making messurable what isn't as yet.", said by Galilei over 300 years ago. Such logion explains the importance of measurement techniques and methods. Actually, the progression of measurement method and improvement of measurement accuracy are also important signs of advancement of science and technology. This dissertation focuses on the study of aircraft pose measurement during the process of aircraft test. Photoelectric theodolite is the main equipment for aircraft pose measurement. The measurement process is as following: Firstly, 3D geometry model of such aircraft is obtained through close-range photogrammetry method; then photoelectric theodolite imaging simulation system has been built by use of such model and computer graphics method; through matching of images produced by such simulation system and real image taken by photoelectric theodolite, the pose of aircraft has been determined. In this process, only monocular image sequence has been used.To measure the pose of moving objects with digital image sequence is a foreland task in the fields of computer vision and digital photogrammetry. This dissertation tried to research such problem in-depth and high accurate and automatic pose measurement is the final goal.The main research content and achievement include:(1) Pose measurement development history is reviewed. The background and literatures of pose measurement is summarized. The trends and prospect applications of pose measurement in the future are expected. The unsolved crucial problems in pose measurement are pointed out.(2) The principle and system structure of pose measurement are introduced in detail. The advantages and disadvantages with respect to various aspects between existing pose measurement methods are discussed in detail. Generally, existing pose measurement methods falls in two main kinds: the first is to set GPS/IMU in the moving objects to be measured and GPS/IMU information is used to calculate the pose of objects, this kind of methods are called " Internal measurement of moving object"; the other is to acquire image sequences of moving objects to be measured with camera outside the object and the image sequences are used to identify the pose of objects, this kind of methods are named "External measurement of moving object".(3) Protective geometry of camera imaging process are studied in detail and imaging mechanism are exploded deeply, two imaging process descriptions respectively in photogrammetry and openGL are analyzed and transition equations between them are derived, their internal consistency are proved by real experiments. Such research impulse OpenGL, such big achievement in the field of computer graphics, tobe absorbed, assimilated and applied by the field of programmetry.(4) Generalized point photogrammetry theory has been established on the basis of the extension from physical point to mathmatics point. Traditional photogrammetry theory is based on collinear of image point, object point and center of camera. Such theory requires that the point must be able to be observed. Such requirement is unnecessary for generalized point photogrammetry theory. The point can be point in infinite far and strict correpondence between points is unnecessary and so its application is flexible and convenient. Because more points have been used, accuracy has been improved greatly. The proposal of such theory impulse the development of photogrammetry theory and can be used urban modeling and industrial photogrammetry and reconstruction of curve and so on.(5 ) Combining generalized point photogrammetry theory and profile matching, a novel algorithm, Generalized point Feedback Iteration, has been presented at first time and used in airplane pose measurement. Experiment results show its high accuracy and reliability. This method makes it possible to automatically extract pose generalized meters of moving objects from image sequences.(6) For the condition that images of aircraft in near distance are clear, feature point trace method has been used to obtain the feature points in each frame and their correspondence between different frames. Then the pyramid method and improved back resection have been used to calculate the pose of aircraft. For images of mid-long distance where the back resection is unstable, improved pyramid method and RANSAC methed has been used. For long distance image where the feature points of aircraft are not clear, GPFI method has been used to determine the profile of aircraft and determine its pose.(7) High accurate aircraft profile extraction algorithm based on line diffusion function has been proposed. In the meanwhile, aircraft model profile generation algorithm based on spatial index has been put forward and made good preparation for matching between image and model profile.(8) Based on Kalman Filter, prediction and smoothing of airplane pose has been researched. The used of KALMAN filter method has greatly improved the speed of pose calculation and works well in accuracy improvement and blunder elimination.