Iterated unscented Kalman filter for passive target tracking

作者：Zhan, Ronghui^*; Wan, Jianwei

来源：IEEE Transactions on Aerospace and Electronic Systems, 2007, 43(3): 1155-1163.

DOI：10.1109/TAES.2007.4383605

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.

• 出版日期2007-7
• 单位中国人民解放军国防科学技术大学