Journal of Computer Applications ›› 2012, Vol. 32 ›› Issue (11): 3247-3250.DOI: 10.3724/SP.J.1087.2012.03247

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Track prediction of vessel in controlled waterway based on improved Kalman filter

ZHAO Shuai-bing1,TANG Cheng2,LIANG Shan1,WANG De-jun1   

  1. 1. College of Automation, Chongqing University, Chongqing 400044, China
    2. Luzhou Waterway Bureau of Yangtze River, Luzhou Sichuan 646000, China
  • Received:2012-05-09 Revised:2012-06-21 Online:2012-11-12 Published:2012-11-01
  • Contact: LIANG Shan

基于改进卡尔曼滤波的控制河段船舶航迹预测

赵帅兵1,唐诚2,梁山3,王德军1   

  1. 1. 重庆大学 自动化学院,重庆 400044
    2. 长江泸州航道局,四川 泸州 646000
    3. 重庆大学 自动化学院,重庆 400030
  • 通讯作者: 梁山
  • 作者简介:赵帅兵(1986-),男,河南平顶山人,硕士研究生,主要研究方向:智能系统、智能控制;唐诚(1964-),男,四川泸州人,高级工程师,主要研究方向:智能航道、航道工程;梁山(1967-),男,四川泸州人,教授,博士生导师,主要研究方向:采样控制、非线性控制、嵌入式系统、无线传感器网络、智能计算、智能系统;王德军(1987-),男,山东烟台人,硕士研究生,主要研究方向:智能系统、智能控制。

Abstract: Due to the lack of information of Automatic Identification System (AIS) equipment, the location of a vessel cannot be accurately judged by intelligent supporting command system based on AIS. It is difficult to accurately issue the traffic signal from it. Meanwhile, due to the narrow and winding features in controlled waterway, it is difficult for traditional Kalman filter to accurately predict track of moving vessel. In this situation, the real-time estimation of system noise in Kalman filter algorithm was proposed to increase the accuracy of track prediction of moving vessel. Simulation analysis was carried out on the tracking effect of the traditional Kalman filter and improved Kalman filter. The results indicate that the proposed algorithm can solve the lack in information of AIS equipment, and accurately predict the location of a vessel. The accuracy and the reliability of intelligence supporting command system can be ensured in controlled waterway.

Key words: Automatic Identification System (AIS), intelligent supporting command, controlled waterway, Kalman filter, track prediction

摘要: 由于船舶自动识别系统(AIS)设备存在信息缺失现象,导致基于AIS的智能辅助指挥系统无法准确判断船舶位置,难以准确揭示通行信号。同时,控制河段具有航道狭窄弯曲等特征,传统卡尔曼滤波算法无法准确预测运动船舶的航迹。针对以上问题,对卡尔曼滤波算法中的系统噪声进行实时估计,以提高船舶航迹的预测精度,并对传统卡尔曼滤波和改进卡尔曼滤波的跟踪效果进行了仿真分析。结果表明,所提算法可有效解决AIS设备信息缺失问题,准确预测船舶位置,保证控制河段智能辅助指挥系统信号揭示的准确性和可靠性。

关键词: 自动识别系统, 智能辅助指挥, 控制河段, 卡尔曼滤波, 航迹预测

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