The Target Detecting And Tracking Under Star Background

As the detectors operate in the outer space radiation exposure, the star images are affected by space radiation noise interference except the internal noise when using the detectors to get optical observations of space targets .The fixed star and moving targets from far away image as the distribution of dark spots on the spot of the detectors focal plane , with only a finite number of pixels but without structure and texture information, Under the influence of noise and the interferencethe of the vast fixed star, it becomes a complex and challenging task while detecting the small targets and extracting their trajectorys effectively. This problem is studied in this paper around this topic.In this paper, the working principle and the relation between temperature and gain characteristics of the EMCCD is researched, the noise distribution and the spatio- temporal ampling characteristics of the star image is analysed from the mean,variance, correlation coefficient of the statistics. After using the means of subtracting the mean rank to revise the non-uniformity of the image and remove the fixed noise , the revised image sequences are regarded as a two-dimensional stationary random process. The spatial distribution and the time fluctuation characteristics of the moving object is analysed. When the targets move, the process of their gray-scale changing is characterized as occuring around a stationary value of a sinusoidal process .Based on this result,it establishes the Star image scene model and the target signal model , regards the problem of detecting target and fixed star under star background as a binary hypothesis testing problem,and proposes the best method based on generalized likelihood ratio test to extract the star chart and objectives.The strategy of suppressing stars background is given to remove the fixed star ,to select the target from the chart , and to separate the target from stars effectively. In order to distinguish stars from targets .Two algorithms to extract the star points and recognise the star charts are proposed.The first algorithm is based on the structural information of the star pattern, according to the characteristics that the star topology is relatively stable between the same features, which selects the Markov distance and the center of correlation coefficient as the structure similarity measure to characterize the structural information between the star point,use structural information to identify whether it's the star point or the target, so as to achieve the purpose of star pattern recognition. The second algorithm is the pattern matching recognition algorithm which based on the improved triangular algorithm.After extracting the star points using those algorithms above, it generates the background mask image with the extracting stars ,uses the background subtraction method to suppress off stars, gets real interested objectives and its continuous trackings.For the situation that the numbers of stars are uncertain during identifying targets, the strategy based on structural information change and anti- recognition guide star catalog is proposed.It gives a detailed study on the Pseudo Hough Differential Recognition Algorithm when the target is close to the star ,which is difficult to separate from them only using the angular distance information.