When the interval of obtaining data from the spaceborne sensor is relatively long, the effect of existing algorithms for group target data association is not so well. This paper presents a group target data association algorithm that takes full advantage of its relatively stable composition and array feature. Firstly, the mathematics model about the composition feature and the array feature of group targets is established. And the basic probability assignment function of the composition feature and the array feature is proposed respectively. Then the two basic probability assignment functions are synthesized based on D-S evidence theory. And finally, the association result is obtained after making use of the 2D assignment algorithm. The simulation proved the effectiveness of the algorithm.%在星载传感器获取数据的时间间隔较长的情况下,现有的阵群目标数据关联算法的效果不太理想.为此,充分利用阵群目标相对稳定的编成、队形特征,提出了综合利用编成及队形特征的阵群目标数据关联算法.首先,建立阵群目标编成特征和队形特征的描述模型,编成特征由阵群所包含的目标类型以及各类型所包含的成员数量构成,队形特征通过阵群中成员间的距离加以描述；然后分别给出编成和队形特征的基本概率分配函数,并利用D-S证据理论对这两种基本概率分配函数进行证据合成；最后采用二维分配方法实现关联判决.对比仿真实验表明,相对现有的阵群目标数据关联算法,该算法能够有效克服低数据率所带来的影响,保持较高的正确关联率.
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