计算机与数字工程2018，Vol.46Issue(5)：908-915,8.DOI:10.3969/j.issn.1672-9722.2018.05.013
一种改进的双站时频差目标跟踪高斯和滤波算法
Enhanced Gaussian-Sum Filter for TDOA and FDOA-Based Tracking with Two Sensors
曹亚琴 1秦宁宁 1杨乐1
作者信息
- 1. 江南大学物联网工程学院 无锡214122
- 折叠
摘要
Abstract
This paper considers the problem of tracking a moving object using the time difference of arrival(TDOA)and fre-quency difference of arrival(FDOA)measurements obtained at two sensors.On the basis of the existing Gaussian mixture represen-tation of measurement-extended Kalman filter(GMM-EKF)technique,an enhanced tracking algorithm termed as GMM-AEKF is developed.A new method that can yield a uniform GMM representation of the TDOA measurement is introduced,alternative extend-ed Kalman filter(AEKF)for FDOA track update,and an effective sample size(ESS)-based Gaussian component management scheme.Simulation results show that compared with the conventional GMM-EKF,the newly proposed GMM-AEKF algorithm has more uniform GMM representations of TDOAs,which leads to improved estimation performance.More importantly,the target veloci-ty estimation accuracy of the GMM-AEKF converges more quickly,due to the use of AEKF that makes its track update identical to that of a standaed linear Kalman filter(KF).This renders GMM-AEKF are more suitable for the scenarios where the fast filtering convergence speed is desired.关键词
时差/频差/高斯和滤波/替代扩展卡尔曼滤波/有效样本大小Key words
TDOA/FDOA/gaussian sum filtering/alternative extended kalman filter/effective sample size分类
信息技术与安全科学引用本文复制引用
曹亚琴,秦宁宁,杨乐..一种改进的双站时频差目标跟踪高斯和滤波算法[J].计算机与数字工程,2018,46(5):908-915,8.
