点目标和扩展目标联合跟踪算法
发布时间：2018-09-17 16:55
【摘要】：目标跟踪问题在国防领域,如雷达对飞机、轮船和导弹等机动军事目标的精确探测和定位很大程度上决定了战争武器的有效性。针对点目标和扩展目标同时存在的特殊情况,提出基于随机集的点目标和扩展目标联合跟踪算法。该算法探索基于随机有限集的扩展目标滤波器对于点目标跟踪的不足,并尝试通过放宽约束条件的方式对其进行改进。仿真结果表明,在点目标和扩展目标同时存在的情况下,所提算法相比于已有基于随机集理论的扩展目标跟踪算法具有更好的鲁棒性。
[Abstract]:The target tracking problem in the field of national defense, such as radar accurate detection and positioning of mobile military targets such as aircraft, ships and missiles, to a large extent determines the effectiveness of war weapons. A joint tracking algorithm based on random set for point and extended targets is proposed for the special case where both point targets and extended targets exist at the same time. The algorithm explores the shortcomings of the extended target filter based on random finite sets for point target tracking and attempts to improve it by loosening the constraints. Simulation results show that the proposed algorithm is more robust than the existing extended target tracking algorithm based on random set theory.
【作者单位】： 空军工程大学防空反导学院;
【基金】：国家自然科学基金青年基金资助项目(61501495)
【分类号】：E919;TN713
本文编号：2246544
[Abstract]:The target tracking problem in the field of national defense, such as radar accurate detection and positioning of mobile military targets such as aircraft, ships and missiles, to a large extent determines the effectiveness of war weapons. A joint tracking algorithm based on random set for point and extended targets is proposed for the special case where both point targets and extended targets exist at the same time. The algorithm explores the shortcomings of the extended target filter based on random finite sets for point target tracking and attempts to improve it by loosening the constraints. Simulation results show that the proposed algorithm is more robust than the existing extended target tracking algorithm based on random set theory.
【作者单位】： 空军工程大学防空反导学院;
【基金】：国家自然科学基金青年基金资助项目(61501495)
【分类号】：E919;TN713
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