基于改进滑动窗口的渔船AIS轨迹数据压缩算法

Automatic identification system(AIS)trajectory data compression algorithm of a fishing vessel based on improved Sliding Window

为解决渔船自动识别系统(AIS)轨迹数据质量不高、渔船轨迹分析需要保留更多特征点的问题,提出了一种基于改进滑动窗口的渔船AIS轨迹数据压缩算法。结果表明:改进的算法利用相邻轨迹点间的经纬度变化趋势确定行驶特征点,在保留时序信息的同时压缩高密度的停滞点,并用采样法保留直行中间点,尽可能多地保留了轨迹特征点,实现了渔船轨迹的有效压缩;本研究中提出的基于改进滑动窗口的渔船AIS轨迹数据压缩算法与Douglas-Peucker算法相比,压缩率从99%降至94%以下,很好地保留了渔船轨迹特征点,同时也避免了Sliding Window轨迹压缩算法存在的轨迹形态失真问题,。研究表明,基于改进滑动窗口的渔船AIS轨迹数据压缩算法更适用于压缩渔船轨迹。

An automatic identification system(AIS)trajectory data compression algorithm of a fishing vessel is proposed based on improved Sliding Window to deal with poor AIS trajectory data quality of the fishing vessels due to requirement for more feature points.The algorithm achieves effective compression of fishing vessel trajectories as much as possible by effective using temporal information and position information of the fishing vessel AIS trajectory data,the feature points determined by the characteristics of the longitude and latitude change trend between the adjacent track points,and effective compression of high-density stagnation points based on retention time information to keep fishing vessel straight intermediate point by sampling method.The comparative tests revealed that the compression ratio of the algorithm was reduced from 99%to less than 94%compared with the D-P algorithm,with good feature points of the fishing vessel trajectory,and improvement of the trajectory distortion of compressing trajectory.The findings indicate that the algorithm is more suitable for compressing fishing vessel trajectory.