摘要
激光雷达所处环境噪声较大,船舶航线辨识困难,为解决该问题,提出基于激光雷达回波信号的雾天船舶航线快速辨识方法。采用信号累积增强算法增强雾天激光雷达回波信号,利用改进经验模态分解算法去噪处理增强后的回波信号,结合回波信号通过最小类内方差获取得到船舶航线和水面最佳分割阈值,提取船舶航线特征点。利用最小二乘法拟合法拟合船舶航线特征点,完成雾天船舶航线辨识。实验结果表明,所提方法应用后激光雷达回波信号更平滑,输出信噪比更高,均方根误差更低,船舶航线辨识准确率更理想。
In order to solve this problem,a fast identification method of ship route in fog based on lidar echo signal is proposed.The signal accumulation enhancement algorithm is used to enhance the lidar echo signal in fog,and the improved empirical mode decomposition algorithm is used to denoise the enhanced echo signal.Combined with the echo signal,the optimal segmentation threshold of ship route and water surface is obtained through the minimum within class variance,and the ship route feature points are extracted.The least square fitting method is used to fit the characteristic points of the ship route to complete the identification of the ship route in fog.The experimental results show that the lidar echo signal is smoother,the output signal-to-noise ratio is higher,the root mean square error is lower,and the accuracy of ship route identification is better.
作者
杨喜旺
黄晋英
YANG Xi-wang;HUANG Jin-ying(School of Data Science and Technology,North University of China,Taiyuan 030051,China;School of Mechanical Engineering,North University of China,Taiyuan 030051,China)
出处
《舰船科学技术》
北大核心
2024年第6期135-139,共5页
Ship Science and Technology
关键词
激光雷达回波信号
船舶航线辨识
回波信号累积增强
经验模态分解
特征提取
lidar echo signal
ship route identification
echo signal accumulation enhancement
empirical mode decomposition
feature extraction
