Target Tracking Technology Based On Intelligent Algorithm Research And Application

In both military and civilian fields, for instance, in air defense and in air traffic control, we all need tracking targets in a reliable and accurate mode. And along with the rapid development of the aerospace technology, all flight vehicles'speed and maneuverability are higher and higher. Combining automatic control, image processing and information technology, target tracking has developed to be an advanced technology, which can automatically distinguish objects in real-time from the video image, acquire and predict the target position information, and track the target movement. Therefore, based on the contribution of other former researchers, the study of this paper focuses on the problem that how to track highly maneuvering targets.At first, the dissertation introduces the development history and the detailed theoretical knowledge of the target tracking: Motion parameters and image information tracking methods and image segmentation discussed several specific problems in the theory. On this basis, the relevant issues were studied, and achieved the following results:(1) Stationary target detection in the context of tracking, the summary of the background static mature target detection algorithm. Pointed out the widely used occasions of variously algorithms and the method of extracting objectives region of the edge, as well as described the context of target tracking static basic idea for the detection, extraction and relevance. Using the method of extracting the edge predicted the target movement position.(2) An adaptive fusion particle video projections, single-target tracking algorithm. In the algorithm, the observation of the target describes the use of particle forecasts, such as templates with the new information. Done a simulation experiment, experimental results show that this method in some complex environment, can achieve better tracking results. Improved the problem how to due to the loss of light caused by the issue of goals.(3) Combined one of the improved algorithms with several other major existing algorithms, the simulation results show that the improved algorithm has a better tracking performance, and it has been made a relatively good balance between tracking accuracy and real-time performance.