Study Of Time-critical Target Association Algorithm With Space Based Remote Sensing Information

With the development of the application of satellites, the space and time resolution of the remote sensing data of satellites has been increased. Accordingly, remote sensing about tactical application is becoming available. Targets association is one of the crucial problems to solve in the tactical application. In this thesis, the problem how to associate maneuverable targets by the space based remote sensing data of satellites is explored.At first, this thesis compares the classical targets association algorithms, from which their advantages, shortcomings and the field adapted are analyzed. Then, the targets association algorithms put forward in thfs paper are discussed in three variant points of view.1. This thesis gives a target association algorithm based on the attribute and feature of the target. This algorithm considers the attribute and feature as the basic parameters used to associate the targets. After setting up the models for the targets in terms of the different attribute and feature, by the calculation of probabilities, the algorithm obtain the probabilities matching the attribute and feature of the measurements and that of the existing tracks, and manage the existing tracks in combining soft and hard decision-making logic, through which the final decisions are made. The experiments prove: this algorithm can improve the decisions' veracity against the deficiency of the time resolution.2. An algorithm based on the terrain analysis is explored. The Rule that the terrain influences the targets' movements is obtained. Then, the different algorithms for teams of cars and tanks are presented respectively. The experiments show the efficiency of the algorithms.3. The method based on knowledge reasoning is employed in targets association algorithm. This thesis discusses the huge potential of using commanding rules and situation assessment to improve target association performance. Lately, a project is given.Finally, a framework of target association algorithm, which integrates targets' attribute and feature, terrain and commanding rules, is designed.