基于双观测站的水下机动目标被动跟踪

赵振轶; 李亚安; 陈 晓; 苏 骏

doi:10.11993/j.issn.2096-3920.2018.01.007

基于双观测站的水下机动目标被动跟踪

doi: 10.11993/j.issn.2096-3920.2018.01.007

西北工业大学航海学院, 陕西西安, 710072

基金项目: 国家自然科学基金项目资助(5140921)

详细信息

作者简介:
赵振轶(1993-), 男, 在读硕士, 主要研究方向为水下信息处理和目标跟踪.

中图分类号: TJ630; TP391.99
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出版历程
- 刊出日期: 2018-02-28

Passive Tracking of Underwater Maneuvering Target Based on Double Observation Station

School of Marine Science and Technology, Northwestern Polytechnical University, Xi′an 710072, China

摘要

摘要: 为了对水下机动目标进行航迹跟踪, 采用双观测站被动跟踪系统, 解决了单观测站利用纯方位角信息进行跟踪时的不可观测问题, 建立了目标状态方程和被动观测方程。将扩展卡尔曼滤波(EKF)和无迹卡尔曼滤波(UKF)与交互式多模型算法(IMM)相结合, 应用于被动跟踪系统中。仿真结果表明, 2种算法都能适用于水下机动目标被动跟踪。随着测量误差的增大, IMM-UKF算法比IMM-EKF算法表现出了更好的稳定性和更高的跟踪精度。
- 水下机动目标 /
- 双观测站 /
- 扩展卡尔曼滤波(EKF) /
- 无迹卡尔曼滤波(UKF) /
- 交互式多模型(IMM)
Abstract: For tracking underwater maneuvering target, a passive tracking system with double observation station is used to solve the unobservable problem of single observation station due to tracking with bearing angle-only information. The target state equation and the passive observation equation are established. The extended Kalman filter(EKF) and the unscented Kalman filter(UKF) are combined respectively with the interactive multiple model(IMM) algorithm to serve the passive tracking system with double observation station. Simulation results show that both IMM-UKF and IMM-EKF algorithms can be applied to passive tracking of underwater maneuvering targets. The IMM-UKF algorithm exhibits higher stability and tracking accuracy than the IMM-EKF algorithm with the increase of measurement error.
- underwater maneuvering target /
- double observation station /
- extend Kalman filter(EKF) /
- unscented Kalman filter(UKF) /
- interactive multiple model(IMM)

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参考文献(10)

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