LiDAR waveform decomposition based on modified differential evolution algorithm
投稿时间:2020-04-15  修订日期:2020-10-23  download
Citation:
摘要点击次数: 687
全文下载次数: 157
作者单位邮编
赖旭东 武汉大学遥感信息工程学院湖北武汉430079
地理国情监测国家测绘地理信息局重点实验室湖北 武汉 430079 
430079
袁逸飞 武汉大学遥感信息工程学院湖北武汉430079 
徐景中 武汉大学遥感信息工程学院湖北武汉430079 430079
王明威 中国地质大学地质调查研究院湖北武汉430074 
Abstract:Full-waveform airborne LiDAR (FWL) is able to record complete echo signals as waveforms, including useful information such as elevation details and backscatter coefficient of the target, but the waveform information data cannot be obtained directly. Waveform decomposition is an important method to process waveform data to extract effective information. In view of the shortcoming of common used parameter optimization algorithm in waveform decomposition which is sensitive to initial value and prone to local optimization, a waveform decomposition method based on Modified Differential Evolution (MDE) algorithm is proposed: the generalized gaussian function is taken as the model, after the initial estimation, a globa lMDE optimization algorithm is used for the parameter optimization, and the point cloud is finally generated. Experimental results show that, compared with the waveform decomposition method based on other optimization algorithms, this method has been obviously improved in terms of the decomposition and point position accuracy.
keywords:LiDAR  full-waveform  waveform decomposition  optimization algorithm  modified differential evolution algorithm
  HTML  查看/发表评论  下载PDF阅读器

Copyright:《Journal of Infrared And Millimeter Waves》