雷达与AIS的船位点会因测量原理、设备特性、环境因素及船舶自身因素的影响而存在偏差。由于雷达测量的是船舶的外沿边界点，而AIS通常获取的是GPS天线的位置，二者的物理位置并不重合，导致他船获取同一船舶的位置数据存在固有的几何偏差。本文采用最小二乘法将雷达测得的船舶外沿边界点拟合成椭圆曲线，并基于此椭圆曲线推算更接近GPS天线位置的拟合点进行融合计算，从而减少了船舶尺度、相对位置及船型对雷达测量数据造成的误差。对于所选VLCC船舶，采用该方法将平均距离误差从155.74 m减少至33.47 m，误差降低了78.51%。此方法提高了轨迹估计的精度，为船舶航行和海上交通管理提供了更精确的导航信息。
The position data from radar and AIS systems can exhibit discrepancies due to differences in measurement principles, equipment characteristics, environmental factors, and the ship's own characteristics. Radar measures the ship’s outer boundary points, while AIS typically provides the position of the GPS antenna, resulting in a natural geometric discrepancy as these two positions do not coincide. This leads to inherent positional differences when other vessels attempt to obtain data for the same ship. In this paper, a least-squares method is employed to fit the outer boundary points measured by radar into an elliptical curve. Based on this curve, a point closer to the GPS antenna’s location is calculated to fuse the data. This reduces errors caused by the ship's dimensions, relative position, and ship type on the radar measurement data. For the selected VLCC vessel, this method reduced the average positional error from 155.74 m to 33.47 m, a reduction of 78.51%. This approach improves trajectory estimation accuracy, providing more precise navigational information for maritime navigation and traffic management.
2025,47(13): 113-119 收稿日期：2024-9-21
DOI：10.3404/j.issn.1672-7649.2025.13.020
分类号：U675.7
基金项目：国家自然科学基金面上项目（52178067）
作者简介：夏志超(2000-),男,硕士研究生,研究方向为船舶避碰
参考文献：
[1] 马军, 丁希雅, 朱文祥. 一种基于AIS数据的机载雷达系统误差实时自动标校方法[J]. 空天预警研究学报, 2024, 38(2): 90-95.
MA J, DING X Y, ZHU W X. A method for real-time calibration of airborne radar system errors based on AIS data[J]. Journal of Space and Airborne Early Warning Research, 2024, 38(2): 90-95.
[2] 刘敬一, 高晓倩, 郭琦, 等. 基于运动属性约束的船舶AIS航迹去纠缠方法[J]. 无线电工程, 2023, 53(3): 678-685.
LIU J Y, GAO X Q, GUO Q, et al. A method for removing entanglement of ship AIS trajectory based on constraints of motion attributes[J]. Radio Engineering, 2023, 53(3): 678-685.
[3] S HONG, PENG D, SHI Y. Track-to-track association using fuzzy membership function and clustering for distributed information fusion[C]//2018 37th Chinese Control Conference (CCC). Wuhan, China, 2018.
[4] CHEN D, CHEN P, ZHOU C. Research on AIS and radar information fusion method based on distributed Kalman[C]//2019 5th International Conference on Transportation Information and Safety (ICTIS). Liverpool, UK, 2019.
[5] 武亚伟. 基于雷达和AIS融合的无人船动态避碰系统研究[D]. 武汉: 武汉理工大学, 2021.
[6] 代广树. 海上无人驾驶技术中的数据融合应用技术[J]. 舰船科学技术, 2019, 41(14): 55-57.
DAI G S. Data fusion application technology in marine unmanned driver technology[J]. Ship Science and Technology, 2019, 41(14): 55-57.
[7] 严庆新, 郑帅祥, 关宏旭, 等. 船舶AIS和雷达航迹数据的关联及融合[J]. 武汉理工大学学报(交通科学与工程版), 2023, 47(1): 185-190.
YAN Q X, ZHENG S X, GUAN H X, et al. Association and fusion of ship AIS and radar track data[J]. Journal of Wuhan University of Technology (Traffic Science and Engineering Edition), 2023, 47(1): 185-190.
[8] WITOLD K, ANDRZEJ S. Radar and Automatic Identification System Track Fusion in an Electronic Chart Display and Information System[J]. Journal of Navigation, 2015, 68(6): 1141-1154.
[9] 赵海林, 汪永军, 候小丽. 基于航迹关联的系统误差自适应校正方法[J]. 舰船电子对抗, 2023, 46(1): 61-67+77.
ZHAO H L, WANG Y J, HOU X L. An Adaptive Correction Method of System Error Based on Track Association [J]. Shipborne Electronic Countermeasure, 2023, 46(1): 61-67+77.
[10] 肖德柱. AIS和ADS-B信息在高频地波雷达中的综合分析方法研究[D]. 哈尔滨: 哈尔滨工业大学, 2021
[11] 黄善稳. 基于神经网络的AIS和雷达的目标信息融合研究[D]. 重庆: 重庆交通大学, 2023.
[12] 张津铭. 基于AIS数据的船舶轨迹聚类分析及异常检测研究[D]. 广州: 华南理工大学, 2023.
[13] 林长川. 雷达与AIS目标位置信息融合方法的研究[C]//2002航海实用新技术论文集, 2002.
[14] 贾景钧. 基于北斗和AIS信息融合的船舶定位监控系统设计[D]. 桂林: 广西师范大学, 2023.
[15] 张秋涌, 陈长明. 雷达局限性对船舶引航安全影响的探讨[J]. 中国水运, 2023(8): 126-128.
ZHANG Q Y, CHEN C M. Discussion on the impact of radar limitations on ship pilotage safety[J]. China Water Transport, 2023(8): 126-128.
[16] 陈若珠, 孙岳. 基于最小二乘法的椭圆拟合改进算法研究[J]. 工业仪表与自动化装置, 2017(2): 35-38+46.
CHEN R Z, SUN Y. Research on improved ellipse fitting algorithm based on least squares method[J]. Industrial Instrumentation and Automation Devices, 2017(2): 35-38+46.
