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[9]BAUM M,HANEBECK U D.Shape tracking of exten- HE Xiongxiong,GUAN Junyi,YE Xuanzuo,et al.A步长的选取是对大量数据实验并统计得出的。本 文中步长的选取是一个具普遍性的定值。若在网 格划分过程中综合考虑网格密度与网格间距自适 应设定步长，其划分效果会更加准确。因此，以后 的研究将深入考虑划分步长的自适应选择与优化。 参考文献： 王雪, 李鸿艳, 孔云波, 等. 基于星凸 RHM 的扩展目标 SMC-PHD 滤波 [J]. 计算机应用研究, 2017, 34(7): 2144–2147. WANG Xue, LI Hongyan, KONG Yunbo, et al. SMC￾PHD filter for extended target tracking based on star-con￾vex random hypersurface models[J]. Application re￾search of computers, 2017, 34(7): 2144–2147. [1] LI Zhifei, ZHANG Jianyun, WANG Jiegui, et al. Exten￾ded object tracking using random matrix with converted measurements[J]. IET radar, sonar & navigation, 2020, 14(7): 981–991. [2] 范建德, 谢维信. 一种高效的分布式多传感器多目标跟 踪算法 [J]. 信号处理, 2021, 37(3): 390–398. FAN Jiande, XIE Weixin. An efficient distributed multi￾sensor multi-target tracking algorithm[J]. Journal of sig￾nal processing, 2021, 37(3): 390–398. [3] 李波, 昝珊珊. 基于自适应遗传 PHD 滤波的多群目标 跟踪方法 [J]. 计算机应用研究, 2018, 35(11): 3466– 3468,3496. LI Bo, ZAN Shanshan. 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Shape tracking of exten￾ded objects and group targets with star-convex RHMs[C]// 14th International Conference on Information Fusion. Chicago: IEEE, 2011: 1−8. MAHLER R. Random sets: unification and computation for information fusion a retrospective assessment[C]// Proceedings of the 7th International Conference on In￾formation Fusion. Stockholm: Information Fusion, 2004: 1−20. [10] 张俊根. 一种粒子势概率假设密度滤波纯方位多目标 跟踪算法 [J]. 控制理论与应用, 2020, 37(6): 1319– 1325. ZHANG Jungen. A particle cardinalized probability hy￾pothesis density filtering algorithm for bearings-only multi-target tracking[J]. Control theory & applications, 2020, 37(6): 1319–1325. [11] VO B N, MA W K. The Gaussian mixture probability hypothesis density filter[J]. IEEE transactions on signal processing, 2006, 54(11): 4091–4104. [12] MAHLER R. PHD filters of higher order in target num￾ber[J]. IEEE transactions on aerospace and electronic systems, 2007, 43(4): 1523–1543. [13] ZHANG Le, LAN Jian. Tracking of extended object us￾ing random matrix with non-uniformly distributed meas￾urements[J]. IEEE transactions on signal processing, 2021, 69: 3812–3825. [14] GRANSTROM K, ORGUNER U. A phd filter for track￾ing multiple extended targets using random matrices[J]. IEEE transactions on signal processing, 2012, 60(11): 5657–5671. [15] 王子龙, 李进, 宋亚飞. 基于距离和权重改进的 K￾means 算法 [J]. 计算机工程与应用, 2020, 56(23): 87–94. WANG Zilong, LI Jin, SONG Yafei. Improved K-means algorithm based on distance and weight[J]. Computer engineering and applications, 2020, 56(23): 87–94. [16] TSAI C F, SUNG C Y. EIDBSCAN: an extended im￾proving DBSCAN algorithm with sampling techniques [J]. International journal of business intelligence and data mining, 2010, 5(1): 94. [17] 胡忠旺, 丁勇, 杨勇, 等. 基于时空关联—网格聚类的 多扩展目标跟踪算法 [J]. 传感器与微系统, 2019, 38(2): 129–132. HU Zhongwang, DING Yong, YANG Yong, et al. Mul￾tiple extended target tracking algorithm based on spati￾otemporal correlation and grid clustering[J]. Transducer and microsystem technologies, 2019, 38(2): 129–132. [18] 何熊熊, 管俊轶, 叶宣佐, 等. 一种基于密度和网格的 簇心可确定聚类算法 [J]. 控制与决策, 2017, 32(5): 913–919. HE Xiongxiong, GUAN Junyi, YE Xuanzuo, et al. A [19] ·812· 智 能 系 统 学 报 第 17 卷