随着计算机控制技术的飞速发展,在船舶的航行预测和控制领域,人们相继开发出了各种智能化的预测算法,从而保证了船舶航行的安全。在船舶的行为预测和控制中,需要大量的传感器对船舶的姿态信息、设备状态信息和通信导航设备信号进行采集,因此本文着重研究了信号的滤波算法。本文提出了基于卡尔曼滤波算法的船舶航迹跟踪技术,并针对船舶的航行特点,建立了适当的运动模型和状态方程,最后通过仿真实验,对扩展卡尔曼算法的目标跟踪性能进行验证。
With the rapid development of computer control technology, a variety of intelligent prediction algorithms have been developed in the field of ship navigation forecasting and control, so as to ensure the safety of ship navigation. In the ship behavior prediction and control, a large number of sensors are needed to collect the attitude information, the equipment state information and the communication and navigation equipment signals of the ship, so this paper focuses on the filtering algorithm of the signal. In this paper, the ship track tracking technology based on Kalman filter algorithm is proposed, and the appropriate motion model and state equation are established according to the ship navigation characteristics. Finally, the target tracking performance of the extended Kalman algorithm is verified by simulation experiments.
2017,39(1A): 16-18 收稿日期:2016-10-23
DOI:10.3404/j.issn.1672-7619.2017.1A.006
分类号:U692
作者简介:何静(1982-),女,硕士,讲师,主要从事图像处理及数据挖掘等。
参考文献:
[1] 李昌, 罗国阳. 结合支持向量机的卡尔曼预测算法在VRLA蓄电池状态监测中的应用[J]. 电工技术学报, 2011(11):168-174.
[2] 史国荣, 戴洪德, 孙玉玉, 吴光彬. 基于卡尔曼预测和滤波的视频目标跟踪[J]. 仪表技术, 2014(1):42-44.
[3] 史国荣, 戴洪德, 孙玉玉, 吴光彬. 基于卡尔曼预测和滤波的视频目标跟踪[J]. 自动化与仪器仪表, 2013(6):149-150.
[4] LIM K C, BASTAWROUS H A, DUONG V H, et al. Fading Kalman filter-based real-time state of charge estimation in LiFePO 4 battery-powered electric vehicles[J]. Applied Energy, 2016, 169:654-665.
[5] KULIKOV G Y, KULIKOVA M V. Accurate cubature and extended Kalman filtering methods for estimating continuous-time nonlinear stochastic systems with discrete measurements[J]. Applied Numerical Mathematics, 2016, 187:236-241.
[6] DUAN Jian-min, SHI Hui, LIU Dan, et al. Square root cubature kalman filter-Kalman filter algorithm for intelligent vehicle position estimate[J]. Procedia Engineering, 2016, 137:579-583.