A Group Target Data Association Algorithm Based On D-S evidence theory

It is difficult to track every target steadily and effectively when the interval of obtaining data from the spaceborne sensor is relatively long. Consequently, a scheme is developed which regards the group targets as the study object and this paper presents a group target data association algorithm based on D-S evidence theory that takes full advantage of their relatively stable composition and array features. Firstly, the composition feature and the array feature of group targets are extracted based on their mathematics model which is established. Secondly, the association matching model of group targets is established that makes use of the composition features and the array features. The basic probability assignment function of the composition features and the array features are calculated respectively based on D-S evidence theory. And finally, the synthetical basic probability assignment function is established after the two basic probability assignment functions are synthesized based on D-S evidence theory and the association result is obtained after making use of the 2D assignment algorithm. The simulation has proved the effectiveness of the algorithm.