| 钟志通,杨秀庭,余家祥,朱慧.非线性Kalman滤波器在纯方位被动跟踪中的应用[J].声学技术,2008,(6):912~916 |
| 非线性Kalman滤波器在纯方位被动跟踪中的应用 |
| The applications of nonlinear Kalman filters in passive tracking with bearing-only measurements |
| 投稿时间：2007-01-21 修订日期：2007-03-26 |
| DOI： |
| 中文关键词: TMA 被动跟踪 UKF |
| 英文关键词: target motion analysis passive tracking unscented Kalman filter |
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| 中文摘要: |
| 目标运动分析(简称TMA)是用于估计水下目标时变状态最主要的技术之一。应用了两种非线性滤波器——EKF和UKF来估计单/双基地情况下的目标运动状态,并由蒙特-卡洛仿真给出其跟踪性能。数值结果表明:在大部分情况下,特别是当目标存在机动时,UKF在估计精度和数值稳定性上都要好于EKF,其代价仅是少量地增加了的计算复杂度。 |
| 英文摘要: |
| Target Motion Analysis(TMA) is one of the most popular techniques for estimation of time-varying state of underwater targets.Two types of nonlinear filters,Extended Kalman Filter(EKF) and Unscented Kalman Filter(UKF),are applied to the monostatic and bistatic bearing-only tracking.The tracking performance of the two filters is demonstrated via Monte Carlo simulations.The results show that the UKF outperforms in most cases in the underwater passive tracking scenarios,especially if the target makes maneuvers frequently.Compared with EKF,UKF shows better numerical stability and higher estimation accuracy with little cost of computational complexity. |
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