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基于多传感器径向速度测量的目标跟踪方法 被引量:1

A Target Tracking Method Based on Multi-Sensor Radial Velocity Measurement
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摘要 针对基于位置信息的目标跟踪在初始跟踪和运动模型变化阶段航向估计精度低的情况,利用传感器径向速度测量精度较高的特性,提出了一种基于多传感器径向速度测量的目标跟踪方法,以提高在数据更新频率和定位精度低的情况下的目标运动参数估计精度。理论分析和仿真实验证明了文中所提方法能较大地提高目标运动参数估计精度。 To solve the problem that the course estimation precision is low at the beginning phase and at time the target moving model is changing,a target tracking method based on multi-sensor radial velocity measurement is put forward.The method utilizes the high precision of radial velocity measurement of multi-radar and improves the precision of target moving parameter estimation with low-frequency and low-precision data.Theoretic analysis and simulation results show that the target moving parameter estimation precision is well improved by using the method put forward in this paper.
出处 《指挥控制与仿真》 2012年第2期58-61,共4页 Command Control & Simulation
基金 国家重点基础研究开发计划项目
关键词 多传感器 径向速度 目标跟踪 multi-sensor radial velocity target tracking
分类号 E911 [军事]
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  • 1张怀根,张林让,吴顺君.利用径向速度观测值提高目标跟踪性能[J].西安电子科技大学学报,2005,32(5):667-670. 被引量:18
  • 2丁杨斌,申功勋.Unscented粒子滤波在静基座捷联惯导系统大方位失准角初始对准中的应用研究[J].航空学报,2007,28(2):397-401. 被引量:16
  • 3Stimson G W.机载雷达导论[M].2版.北京:电子工业出版社,2005.
  • 4[1]Bar-Shalom Y, Li Xiaolong. Estimation and tracking: Principles, techniques and software[M]. Boston: Artech House, 1993.
  • 5[2]Farina A, Pardini S, Barontini G. Application of nonline filtering theory to a track-while-scan problem[Z]. 1st Int Conf Information Sciences and Systems. Patras, Italy, 1976.
  • 6[3]Farina A, Pardini S. Tracking-while-scan algorithm in a clutter environment[J]. IEEE Trans On AES, 1978,AES-14(5):769-778.
  • 7[4]Jazwinski A H. Stochastic process and filtering theory[M]. San Diego CA: Academic Press, 1970.
  • 8JULIER S J, UHLMANN J K. Unscented filtering and nonlinear estimation [ J ]. Proceeding of the IEEE ,2004,92 (3) :401-402.
  • 9樊红娟.无先导卡尔曼滤波算法分析[D].重庆:西南大学,2007.
  • 10Wang Jiangguo. Use of Radial Velocity Measurement in Target Tracking[J]. IEEE Trans on Aerospace and Electronic Systems, 2003, 39(2): 401-411.

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  • 1贺有.红外、雷达协同探测跟踪模型[J].红外与激光工程,2006,35(z4):306-311. 被引量:5
  • 2李安平,敬忠良,胡士强.基于有源辅助的被动跟踪系统[J].上海交通大学学报,2005,39(12):2048-2051. 被引量:19
  • 3WHITE F E. Data fusion lexicon, ADA529661 [R]. 1991.
  • 4HALL D L. Mathematic techniques in multisensor datafusion[ M]. Boston, MA : Artech House, 1992.
  • 5胡洪涛.主被动目标跟踪研究[D].上海:上海交通大学,2005.
  • 6KALANDROS M. Managing multiple sensor resourcesusing covariance control techniques for tracking systemswith data association [ D]. Boulder: University of Colorado,2000.
  • 7KALANDROS M, PAO L Y. Covariance control for multi-sensor systems [ J]. IEEE Transactions on Aerospace andElectronic Systems, 2002,38(4) :1138-1157.
  • 8CUI N Z, XIE W X, YU X N, et al. Multisensor distributedextended Kalman filtering algorithm and its application toradar/1R target tracking [ C] //Proceedings of the Interna-tional Society for Optical Engineering, 1997 :323-330.
  • 9HUYSSTEEN D V, FAROOQ M. Performance analysis of bea-ring only target tracking algorithm[ C] //Proceedings of the In-ternational Society for Optical Engineering, 1998 : 139-149.
  • 10MALTESE D, LUCAS A. Data fusion: Principles andapplications in air defense [ C] //Proceedings of the Inter-national Society for Optical Engineering, 1998:329-336.

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