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地面目标的强机动性和背景环境的复杂性,使得传统关联方法的目标分布类型和先验概率不易获得,且传统方法仅利用状态信息进行关联,导致目标关联正确率不高。针对这些问题,采用无需先验假设的灰色关联方法,在状态信息的基础上引入属性信息,共同作为灰色关联的多个特征指标,并利用最大离差法确定指标权重。仿真结果表明这里的算法有效地改善了关联正确率,增大关联区分度,满足实时性要求。
The strong mobility of the ground targets and the complexity of the background environment make the target distribution types and prior probabilities of the traditional correlation methods difficult to obtain, and the conventional methods only use the state information to make correlations, resulting in a low target association rate. In order to solve these problems, the gray relational method which does not need a priori hypothesis is introduced. Based on the state information, attribute information is introduced as a gray relational multiple feature index, and the maximum deviation method is used to determine the weight of the index. Simulation results show that the proposed algorithm effectively improves the accuracy of association, increases the degree of association and satisfies the real-time requirements.