期刊文献+

幅度信息辅助的海面低空多目标多假设跟踪算法

Amplitude Information Aided Multiple Hypothesis Tracking Algorithm for Low Altitude Marine Multi-target at Sea
在线阅读 下载PDF
导出
摘要 在海面低空多目标跟踪场景下,由于受到海杂波的影响,多假设跟踪算法会生成大量虚假航迹并发生航迹中断。针对此问题,提出一种基于幅度信息辅助的海面低空多目标多假设跟踪算法。首先,算法采用先验的信杂比信息,通过设置幅度门限区分出目标回波量测与杂波量测;然后,利用回波量测的幅度信息修正多假设跟踪算法中的航迹得分,提高数据关联的准确度;最后,针对跟踪处理后出现的航迹中断问题,采用图模型方法实现航迹粘连。仿真实验结果表明,文中提出的算法能够有效降低海杂波的影响,减少虚假航迹与中断航迹的产生。 In the low-altitude marine multi-target tracking scenario,due to the influence of sea clutter,the multiple hypothesis tracking(MHT)algorithm will generate a large number of false tracks and cause track interruption.Aim to solve this problem,an amplitude information aided MHT algorithm is proposed in this paper.Firstly,the algorithm uses a priori signal-to-clutter ratio information to distinguish the target measurement and clutter measurement by setting an amplitude gate.Then,the amplitude information of measurement is used to modify the track score in the MHT to improve the accuracy of data association.Finally,to solve the problem of track interruption after tracking processing,the graph model method is used to realize track sticking.Simulation results show that the proposed algorithm can effectively reduce the influence of sea clutter on the MHT,and reduce the generation of false tracks and interrupted tracks.
作者 马艳琴 陆耀宾 李向前 马永林 MA Yanqin;LU Yaobin;LI Xiangqian;MA Yonglin(Nanjing Research Institute of Electronics Technology,Nanjing Jiangsu 210039,China;School of Electronic and Information Engineering,Beihang University,Beijing 100191,China;The Unit 31001 of PLA,Beijing 100095,China)
出处 《现代雷达》 CSCD 北大核心 2024年第3期9-15,共7页 Modern Radar
关键词 幅度信息辅助 多假设跟踪 航迹得分 航迹粘连 图模型 amplitude information aided multiple hypothesis tracking(MHT) track score track sticking graph model
  • 相关文献

参考文献6

二级参考文献48

  • 1罗守贵,金林.机载预警雷达的发展趋势分析[J].现代雷达,2008,30(12):1-5. 被引量:15
  • 2金文彬,刘永祥,黎湘,任双桥.再入目标质阻比估计算法研究[J].国防科技大学学报,2004,26(5):46-51. 被引量:17
  • 3汤亚波,徐守时.基于D-S证据理论的多源遥感图像目标数据联合关联算法[J].中国科学技术大学学报,2006,36(5):466-471. 被引量:11
  • 4Wang H, Kirubarajan T, Bar-Shalom Y. Large scale air traffic surveillance using IMM estimators with assignment [J]. IEEE Transactions on Aerospace and Electronic Sys terns, 1999, 35(1): 255 -266.
  • 5Kirubarajan. T, Bar Shalom Y, Blair W D, et al. IMMP DAF for radar management and tracking benchmark with ECM [J]. IEEE Transactions on Aerospace and Electronic Systems, 1998, 34(4): 1115-1134.
  • 6Yeom S W, Kirubarajan T, Bar Shalom Y. Track seg ment association, fine-step IMM and initialization with Doppler for improved track pert'ormance[J]. IEEE Trans actions on Aerospace and Electronic Systems, 2004, 40 (1) :293-309.
  • 7Bar-Shalom Y, Li X R, Kirubarajan T. Estimation with applications to tracking and navigation[M]. New York: Wiley, 2001: 453-477.
  • 8Bar Shalom Y, Blair W D. Multitarget/multisensor track- ing: applications and advances[M]. Vol. III. Norwood, MA: Artech House, 2000:267- 295.
  • 9William J F. Interacting multiple model filter for tactical ballistic missile tracking[J]. IEEE Transactions on Aero- space and Electronic Systems, 2008, 44(2): 418- 426.
  • 10Benavoli A, Chisci L, Farina A. Tracking of a ballistic missile with a-prior information[J].IEEE Transactions on Aerospace and Electronic Systems, 2007, 43(3): 1000- 1016.

共引文献30

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部