期刊文献+

纯方位角系统的实用多目标跟踪算法研究 被引量:2

A Multi-target Tracking Algorithm for Bearing-only System
下载PDF
导出
摘要 该文以可变多目标两传感器的纯方位跟踪系统为对象,综合应用目标的速率约束、相关噪声的UKFJ、DPA关联和滑动窗口等方法建立一个新型实用的多目标多传感器纯方位关联跟踪方法。新方法能有效解决目标跟踪过程中所有的关键问题,并具备完整处理可变目标数的多目标关联与跟踪的性能。该文给出了新方法的计算公式,并通过一个计算仿真验证新算法的有效性。 This paper establishes a new type of target tracking method,which is practical,multi-objective,multi-sensor,and bearing-only,this method is based on the uncertain number of targets,two sensors and bearings-only tracking system,and it is integrated with methods of rate constraints of the targets,the UKF with relevant noise,JPDA and sliding window.The new method can effectively solve all the key issues of target tracking process,and it has the function of completely processing the multiple targets association...
作者 张蕊 葛泉波
出处 《杭州电子科技大学学报(自然科学版)》 2009年第6期62-65,共4页 Journal of Hangzhou Dianzi University:Natural Sciences
基金 国家自然科学资助基金项目(60804064) 浙江省科技厅一般面上科研资助项目(C34016) 浙江省研究生创新科研资助项目(YK2008061)
关键词 多目标跟踪 纯方位系统 数据关联 噪声相关 multiple target tracking bearing-only system data association correlated noise
  • 相关文献

参考文献3

二级参考文献78

  • 1[1]Aidala V J, Hammel S. Utilization of Polar Coordinates for Bearings-Only Tracking. IEEE Trans on AC, 1983, 28(2): 283~294
  • 2[2]Fawcett J A. Effect of Course Maneuvers on Bearings-Only Range Estimation. IEEE Trans on ASSP, 1988,36(8): 1193~1199
  • 3[3]Ferial E H, Fred A, Mbamalu G A N. The Generalized Kalman Filter Approach to Adaptive Underwater Target Tracking. IEEE J Oceanic Engineering. 1992,17(1): 129~137
  • 4[4]Rao S K. Algorithm for Detection of Maneuvering Targets in Bearings-Only Passive Target Tracking. IEE Proc Radar Sonar Navigation. 1999,146(3): 141~146
  • 5Arulampalam S,Maskell S,Gordon N,et al.A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking[J].IEEE Trans on Signal Processing,2002,50(2):174-188.
  • 6Thrun S,Fox D,Burgard W,et al.Robust monte carlo localization for mobile robots[J].Artificial Intelligence,2001,128(1-2):99-141.
  • 7Julier S J,Uhlmann J K,Durrant-Whyten H F.A new approach for filtering nolinear system[A].Proc of the American Control Conf[C].Washington:Seattle,1995:1628-1632.
  • 8Julier S J,Uhlmann J K.A general method for approximating nonlinear transformations of probability distributions[EB/OL].http://www.robots.ox.ac.uk/~siju/work/publications/Unscented.zip,1997-09-27.
  • 9Julier S J,Uhlmann J K.A consistent,debiased method for converting between polar and Cartesian coordinate systems[A].The Proc of AeroSense:The 11th Int Symposium on Aerospace/Defense Sensing,Simulation and Controls[C].Orlando,1997:110 -121.
  • 10Julier S J,Uhlmann J K.A new extension of the Kalman filter to nonlinear systems[A].The Proc of AeroSense:11th Int Symposium Aerospace/Defense Sensing,Simulation and Controls[C].Orlando,1997:54-65.

共引文献239

同被引文献5

引证文献2

二级引证文献6

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