| 基于卡尔曼滤波和ISODATA的航标漂移预警方法 |
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| 引用本文： | 甘浪雄,徐才云,周春辉,郑元洲,陈润.基于卡尔曼滤波和ISODATA的航标漂移预警方法[J].上海海事大学学报,2017,38(4):26-31. |
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| 作者姓名： | 甘浪雄 徐才云 周春辉 郑元洲 陈润 |
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| 作者单位： | 武汉理工大学a.航运学院；b.内河航运技术湖北省重点实验室,武汉理工大学a.航运学院；b.内河航运技术湖北省重点实验室,武汉理工大学a.航运学院；b.内河航运技术湖北省重点实验室,武汉理工大学a.航运学院；b.内河航运技术湖北省重点实验室,武汉理工大学a.航运学院；b.内河航运技术湖北省重点实验室 |
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| 基金项目： | 国家自然科学基金(71372202)；中央高校基本研究经费（2015IVA042）；湖北省自然科学基金（2014CFB856） |
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| 摘 要： | 为解决目前航标遥控遥测系统中航标漂移误报警过多的问题,提出一种基于卡尔曼滤波和迭代自组织数据分析算法(iterative self-organizing data analysis technique algorithm,ISODATA)的组合优化方法。该方法如下:对航标GPS接收机原始坐标数据进行滤波,消除波动较大的数据后得到较可靠的航标位置数据;使用ISODATA得出其聚类中心;以该聚类中心取代航标抛设位置作为航标回旋中心,计算航标漂移距离。测试结果表明,该组合优化方法能够获取较为准确的航标漂移距离,在降低航标维护成本的同时,还能有效减少误报警。
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| 关 键 词： | 航标 卡尔曼滤波 迭代自组织数据分析算法（ISODATA） 误报警 |
| 收稿时间： | 2017/6/18 0:00:00 |
| 修稿时间： | 2017/8/31 0:00:00 |
Early-warning method of buoy drift based on Kalman filtering and ISODATA |
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| ganlangxiong,xucaiyun,zhouchunhui,zhengyuanzhou and chenrun.Early-warning method of buoy drift based on Kalman filtering and ISODATA[J].Journal of Shanghai Maritime University,2017,38(4):26-31. |
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| Authors: | ganlangxiong xucaiyun zhouchunhui zhengyuanzhou and chenrun |
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| Institution: | Wuhan University of Technology, School of Navigation,Wuhan University of Technology, School of Navigation,Wuhan University of Technology, School of Navigation,Wuhan University of Technology, School of Navigation and Wuhan University of Technology, School of Navigation |
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| Abstract: | In order to solve the too much false alarm problem of the buoy drift in the remote control telemetry system, a combinatorial optimization method based on Kalman filtering and the iterative self organizing data analysis technique algorithm (ISODATA) is proposed. The method is as follows: the buoy initial coordinate data from GPS are filtered to eliminate the fluctuated data, and the reliable buoy position data are obtained; the clustering center of the data is got by ISODATA; the clustering center is used as the buoy motion center instead of the buoy throw position to calculate the buoy drift distance. The test results show that, by the combinatorial optimization method, the more accurate buoy drift distance can be obtained, and the buoy maintenance cost and false alarm are both reduced. |
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| Keywords: | buoy Kalman filtering iterative self organizing data analysis technique algorithm (ISODATA) false alarm |
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