东南大学学报（英文版）2009，Vol.25Issue(3)：294-298,5.
基于TDOA/Doppler测量的联邦UKF移动位置估计算法
Federated UKF algorithm for mobile location estimation with TDOA/Doppler measurements
摘要
Abstract
In order to enhance the location estimation performance of mobile station(MS)tracking and positioning, a new method of mobile location optimal estimation based on the federated filtering structure and the simplified unscented Kalman filter (UKF) is presented.The proposed algorithm uses the Singer mobile statement model as the reference system, and the simplified UKF as the subfilters.The subfilters receive the two groups of independently detected time difference of arrival (TDOA) measurement inputs and Doppler measurement inputs, and produce local estimation outputs to the main estimator.Then the main estimator performs the optimal fusion of the local estimation outputs according to the scalar weighted rule, and a global optimal or suboptimal estimation result is achieved.Finally the main estimator gives feedback and reset information to the subfilters and the reference system for next step estimation.In the simulations, the estimation performance of the proposed algorithm is evaluated and compared with the simplified UKF method with TDOA or Doppler measurement alone.The simulation results demonstrate that the proposed algorithm can effectively reduce the location estimation error and variance of the MS, and has favorable performance in both root mean square error(RMSE) and mean error cumulative distribution function(CDF).关键词
数据融合/移动位置估计/联邦滤波/无迹卡尔曼滤波器Key words
data fusion/ mobile location estimation/ federated filtering/ unscented Kalman filter(UKF)分类
信息技术与安全科学引用本文复制引用
蔡苗红,金乐,何峰,吴乐南..基于TDOA/Doppler测量的联邦UKF移动位置估计算法[J].东南大学学报（英文版）,2009,25(3):294-298,5.基金项目
Foundation item: The Cultivation Fund of the Key Scientific and Technical Innovation Project of Ministry of Education of China(No.706028). （No.706028）
