期刊文献+

基于阵元域数据的联合检测与跟踪算法 被引量:3

A unified method for target detection and tracking based on data from sensors of array
下载PDF
导出
摘要 为了提高对弱目标的检测与跟踪能力,采用一种基于阵元域数据驱动的联合检测与跟踪算法。在假定多目标信号互不相关,且目标个数已知的条件下,采用最大后验(MAP)方法从阵元域数据中直接估计目标的状态。与传统的检测跟踪算法不同,该算法在目标方位信息的基础上,增加能量信息,用于目标跟踪从而提高跟踪能力,同时又通过跟踪目标轨迹的预测以提高检测能力。仿真结果显示,该算法可提高对弱目标的检测能力和跟踪能力,解决传统的跟踪算法对于交叉目标的错跟与失跟问题,在目标非快速机动的情况下得到很好的检测跟踪结果。海试结果显示该算法具有重要的实际工程应用价值。 A unified method for target detection and tracking based on data from sensors of array is presented in order to improve the detection and tracking ability of the weak targets with low signal-to-noise ratio. Assuming that the multiple targets are uncorrelated each other and the number of the targets is known as a prior, then the status of the targets can be estimated with the Maximum A-Posteriori (MAP) method directly through the data from sensors of array. The proposed method is different from the classical method in that it can detect and track targets simultaneity based on energy and information about Direction of Arrival (DOA). Simulation results show that the detection and tracing capabilities of the weak targets can be improved and the wrong tracing and the missing tracing, which lies in the general tracing method when it comes to the cross targets, can be solved with the proposed method. The real trail results show that the proposed method is of practical engineering value.
作者 王忠 陈伏虎
出处 《声学学报》 EI CSCD 北大核心 2007年第6期553-558,共6页 Acta Acustica
  • 相关文献

参考文献16

  • 1Singer R A, Stein J J. An optimal tracking filter for processing sensor data of imprecisely determined origin in surveillance system. Proceedings of 10^th IEEE Conference on Decision and Control, Miami Beach, 1971:171-175
  • 2Bar-Shalom Y, Jaffer A G. Adaptive nonlinear filtering for tracking with measurements of uncertain origin. In: Proc. the 11^th IEEE Conf. on Decision and Control, 1972: 243- 247
  • 3Fortmann T E, Bar-Shalom B, Scheffe M. Sonar tracking of multiple targets using joint probabilistic data association. IEEE Transactions on Oceanic Engineering, 1983; 8(3): 173-184
  • 4Reid D B. An alogrithm for tracking multiple targets. IEEE Transactions on Automatic Control, 1979; 24(6): 843-854
  • 5Peter Willett, Yanhua, Roy Streit. PMHT: problems and some solutions. IEEE Transcaction on Aerospace and Electronic Systems, 2002; 38(3): 738-753
  • 6Efe M, Ruan Y, Willett P. Probabilistic multi-hypothesis tracker: addressing some basic issues. IEE Proc-Radar Sonar Navig, 2004; 151(4): 189-196
  • 7胡青,宫先仪.方位/频率目标运动分析实验研究[J].声学学报,2005,30(2):120-124. 被引量:10
  • 8王燕,岳剑平,冯海泓,余征明.双基阵纯方位目标运动分析研究[J].声学学报,2001,26(5):405-409. 被引量:26
  • 9胡友峰,詹艳梅,孙进才.基于状态矢量融合的多基地无源目标运动分析[J].声学学报,2002,27(4):316-320. 被引量:8
  • 10郑援,胡成军,李启虎,孙长瑜.一种多目标方位历程实时提取方法[J].声学学报,2005,30(1):83-88. 被引量:13

二级参考文献41

  • 1郑援,胡成军,李启虎,孙长瑜.一种多目标方位历程实时提取方法[J].声学学报,2005,30(1):83-88. 被引量:13
  • 2潘志坚,阎福旺,刘孟庵,王广恩.纯方位水下目标运动分析方法研究[J].声学学报,1997,22(1):87-92. 被引量:18
  • 3蔡庆宇 薛毅 等.相控阵雷达数据处理及其仿真技术[M].北京:国防工业出版社,1997.4-7.
  • 4项楚琪 田坦.离散估计导论[M].哈尔滨船舶工程学院出版社,1989..
  • 5(美)许与兹 L.肖.信号处理:离散频谱分析、检测和估计[M].北京:科学出版社,1982.211-213.
  • 6王燕.水下目标无源定位仿真研究:硕士学位论文[M].哈尔滨工程大学,2000.31-33.
  • 7樊羚珂.卡尔曼滤波在无源测距声呐中的应用[J].哈尔滨船舶工程学院学报,1986,7(2):58-69.
  • 8CastlemanKR著 朱志刚 林学阎 石定机译.Digitalimageprocessing,数字图像处理[M].北京:电子工业出版社,1998.127-137.
  • 9Mourad Oussalah, Joris De Schutter. Hybrid fuzzy probabilistic data association filter and joint probabilistic data association filter. Information Sciences, 2002; 142(1-4):195-226.
  • 10Ding Z, Leung H, Hong L. Decoupling joint probabilistic data association algorithm for multiple target tracking.IEE Proceedings RADAR, SONAR and Navigation, 1999;146(5): 251-254.

共引文献45

同被引文献13

引证文献3

二级引证文献5

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