For long-term robust tracking to single target, a corrected tracking algorithm based on static-adaptive appearance model was proposed. Firstly, the interference factors that may be encountered in the tracking process were divided into two categories from environment and target itself, then a static appearance model and an adaptive appearance model were proposed respectively. The static appearance model was used for global matching while the adaptive appearance model was employed for local tracking, and the former corrected tracking drift of the latter. A single-link hierarchical clustering algorithm was used to remove the noise introduced by the fusion of the above two models. To capture the re-occurring target, static appearance model was applied for global search. Experimental results on standard video sequences show that the accuracy of tracking the target center is 0.9, and the computer can process 26 frames per second. The proposed tracking algorithm framework can achieve long-term stable tracking with good robustness and real-time performance.

Concerning the problem that there is a lot of data which need to be real-time processed during the production process, the local processor, based on multi-thread and co-processing architecture and two data buffer mechanisms was accomplished. As a reference, multi-functional thread in Hadoop's parallel architecture has an impressed impact on the design of the local processor, especially MapReduce principle. Based on the user-defined architecture, the local processor ensures data concurrency and correctness during receiving, computing and uploading. The system has been put into production for over one year. It can meet the enterprise requirements and has good stability, real-time, effectiveness and scalablility. The application result shows that the local processor can achieve synchronized analysis and processing of mass data.

In view of the fact that Multilateration (MLAT) technique locates the target according to the Time Difference Of Arrival (TDOA) from target to each station and the fact that the precision of clock in each station is crucial to the precision of target locating, an anti-interference method based on the residual error of TDOA was proposed. It estimated the clock precision of each station by the residual error, and archived the goal of the optimal stations selection and the locating precision improvement. The experimental results based on both simulation and practical data illustrate the proposed method can significantly enhance the locating precision, not only feasible but also effective.

A new method to design a 3D surface movement simulation system for A-SMGCS based on Linux operation system and FilightGear flight simulator was proposed. The simulation system was driven by real-time track data of ADS-B. An airport model was built up according to a real airport prototype by modeling of aircrafts, airport layout, terminal, tower and terrain. Because ADS-B track data had no flight attitude data, an algorithm to extract flight attitude from a space vector, which was connected by two pre and post track points, was proposed. Six degrees of freedom (6-DOF) aircraft movement simulation was realized by importing position and attitude data into FlightGear through its multiplayer interface to drive aircraft models. The simulation results show that, the system can simulate surface movement accurately and realistically. The simulation system is low-cost because it is based on free, open source software.

 In fractal image compression, it takes quite long time to look for the best matching block.A method of fractal image coding was put forward based on quadtree image partition and class fuction as well as Y function. The method divides image blocks into 24 species, and then determines one transformation efficiently without carrying out various transformations on every definition domain block. Experiments prove that this method accelerates the speed of coding and the image quality of decoding dosen’t decline obviously.