基于SRUKF的TSOA/TDOA单站跟踪技术研究
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解放军电子工程学院 安徽省电子制约技术重点实验室 合肥,解放军电子工程学院 安徽省电子制约技术重点实验室 合肥,解放军汽车管理学院 蚌埠,解放军电子工程学院 安徽省电子制约技术重点实验室 合肥

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国防预研基金,基金编号:41101040603


TDOA/TSOA tracking technology based on Square-root Unscented Kalman Filter
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Electronic Engineering Institute of PLA,Key Laboratory of Electronic Restriction,Hefei,Electronic Engineering Institute of PLA,Key Laboratory of Electronic Restriction,Hefei,Automobile Management institute of PLA,Electronic Engineering Institute of PLA,Key Laboratory of Electronic Restriction,Hefei

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    摘要:

    阐述了蜂窝网系统中单台定位设备TSOA/TDOA被动式新型混合定位技术的原理。利用TSOA/TDOA混合定位的数学模型建立系统观测方程,采用受随机加速影响的匀速运动状态模型,描述了移动台的位移和速度。在此基础上推导了基于平方根无迹卡尔曼滤波的跟踪算法,并通过仿真实现了对移动台位置和速度的同时跟踪。仿真结果表明,与扩展卡尔曼滤波及无迹卡尔曼滤波算法相比,平方根无迹卡尔曼滤波算法跟踪性能更优。

    Abstract:

    According to the single location equipment application in cellular networks, the principle of the novel passive location technology is presented in detail based on TSOA/TDOA in the paper firstly. Then the equation of observation is set up by the mathematical model of the TSOA/TDOA location system, and the speed and shift of the mobile are described with the uniform motion state model which is affected by the random acceleration. Finally the locating and tracking algorithm is put forward and derived based on square-root unscented kalman filter, and implements the estimation of the mobile position and speed at the same time. The result of simulation shows the algorithm proposed in the paper has superior performance by comparing with extended kalman filter algorithm and unscented kalman filter tracking algorithm.

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刘翔,宋常建,胡磊,钟子发.基于SRUKF的TSOA/TDOA单站跟踪技术研究[J].数据采集与处理,2012,27(2):259-263

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历史
  • 收稿日期:2011-10-09
  • 最后修改日期:2012-03-13
  • 录用日期:2011-12-26
  • 在线发布日期: 2012-11-06