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基于改进DP算法的船舶轨迹自适应压缩方法

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文中通过结合滑动窗算法.考虑船舶轨迹几何特性与船舶转向角动态因素,自适应分割船舶轨迹中的弯曲段与直线段部分,并自适应选取各自对应的压缩阈值.实现对轨迹数据的压缩.在保留更多重要特征点的前提下,提高了轨迹压缩率.利用尹公洲水域的船舶轨迹数据,通过对比改进压缩方法与传统方法,验证了文中方法能够在保留较多轨迹特征点的前提下,对轨迹数据进行大幅度压缩.
An Adaptive Compression Method of Ship Trajectory Based on Improved DP Algorithm
By combining the sliding window algorithm and considering the geometric characteristics of ship trajectory and the dynamic factors of ship steering angle,the curved section and straight section of ship trajectory were adaptively segmented,and their corresponding compression thresholds were a-daptively selected to realize the compression of trajectory data.On the premise of retaining more im-portant feature points,the trajectory compression rate was improved.By comparing the improved compression method with the traditional method,it is verified that the proposed method can greatly compress the trajectory data on the premise of retaining more trajectory feature points.

vessel trafficship trajectoryAISself-adaptivetrajectory compression

舒田伦、刘奕、刘敬贤、张贵平、周备

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武汉理工大学航运学院 武汉 430063

内河航运技术湖北省重点实验室 武汉 430063

江苏海事局 长安 710064

长安大学运输工程学院 南京 210009

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船舶交通 船舶轨迹 AIS 自适应 轨迹压缩

国家自然科学基金

51709219

2024

武汉理工大学学报(交通科学与工程版)
武汉理工大学

武汉理工大学学报(交通科学与工程版)

CSTPCD
影响因子:0.462
ISSN:2095-3844
年,卷(期):2024.48(5)