Iterated unscented Kalman filter for passive target tracking

被引：9

作者：

Zhan, Ronghui ^{[1
]}

Wan, Jianwei ^{[1
]}

机构：

[1] Natl Univ Def Technol, Sch Elect Sci & Engn, Signal Proc Lab, Changsha 410073, Peoples R China

来源：

IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS | 2007年 / 43卷 / 03期

关键词：

Target tracking;

D O I：

10.1109/TAES.2007.4383605

中图分类号：

V [航空、航天];

学科分类号：

08 ; 0825 ;

摘要：

It is of great importance to develop a robust and fast tracking algorithm in passive localization and tracking system because of its inherent disadvantages such as weak observability and large initial errors. In this correspondence, a new algorithm referred to as the iterated unscented Kalman filter (IUKF) is proposed based on the analysis and comparison of conventional nonlinear tracking problem. The algorithm is developed from UKF but it can obtain more accurate state and covariance estimation. Compared with the traditional approaches (e.g., extended Kalman filter (EKF) and UKF) used in passive localization, the proposed method has potential advantages in robustness, convergence speed, and tracking accuracy. The correctness as well as validity of the algorithm is demonstrated through numerical simulation and experiment results.

引用

页码：1155 / 1163

页数：9

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