欢迎您！东篱公司
退出
-
申报数据库
-
立项数据库
-
成果数据库
-
项目获奖数据库
中文摘要：
针对杂波环境下多扩展目标量测集难以划分,且时间代价高的问题,该文引入近邻传播聚类技术,提出一种新的多扩展目标量测集划分算法。该算法先采用密度分析技术对量测集进行预处理,滤除部分杂波量测,然后引入近邻传播聚类技术,通过量测间的相互竞争,初步确定扩展目标的数目和质心位置,然后通过扩展目标PHD滤波方法估计目标数目和状态。该方法可有效避免量测集聚类过程中扩展目标质心初始化的干扰,能够准确地划分杂波环境下多扩展目标量测集。与传统的距离划分,K-means＋＋划分方法相比,所提算法能够自适应地确定目标数目,降低时间成本,提高多扩展目标的跟踪性能。
英文摘要：
It is difficult to accurately and rapidly partition measurement sets of multiple exzenaea zargets in cluttered environment. Hence the affinity propagation method is introduced and a novel measurement partition algorithm is proposed. First, the measurement set is preprocessed by using density analysis to remove clutters from the measurements. Second, the number and location of the extended targets is determined via competition among the measurements. Finally, state estimates are obtained by using the probability hypothesis density filter. Simulations show that the proposed algorithm offers good performance in measurement partitioning of extended target tracking with clutter disturbance. Compared with the distance partition and K-means＋＋ methods, the proposed method effectively minimizes the computation time and retrieves the number of targets iteratively.
同期刊论文项目
同项目期刊论文
Effectof temperature on Chinese rice wine brewing with high concentration pre-steamedwhole sticky ri
期刊信息
位置：