层次化的城区机载阵列干涉SAR点云噪声抑制

纪方方, 余洁, 卢丽君, 杨书成, 黄国满, 程春泉, 迟博文

纪方方, 余洁, 卢丽君, 杨书成, 黄国满, 程春泉, 迟博文. 层次化的城区机载阵列干涉SAR点云噪声抑制[J]. 武汉大学学报 ( 信息科学版). DOI: 10.13203/j.whugis20240240
引用本文: 纪方方, 余洁, 卢丽君, 杨书成, 黄国满, 程春泉, 迟博文. 层次化的城区机载阵列干涉SAR点云噪声抑制[J]. 武汉大学学报 ( 信息科学版). DOI: 10.13203/j.whugis20240240
JI Fangfang, YU Jie, LU Lijun, YANG Shucheng, HUANG Guoman, CHENG Chunquan, CHI Bowen. A Hierarchical Urban Airborne ArrayInSAR Point Cloud Noise Suppression Method[J]. Geomatics and Information Science of Wuhan University. DOI: 10.13203/j.whugis20240240
Citation: JI Fangfang, YU Jie, LU Lijun, YANG Shucheng, HUANG Guoman, CHENG Chunquan, CHI Bowen. A Hierarchical Urban Airborne ArrayInSAR Point Cloud Noise Suppression Method[J]. Geomatics and Information Science of Wuhan University. DOI: 10.13203/j.whugis20240240

层次化的城区机载阵列干涉SAR点云噪声抑制

基金项目: 

国家重点研发计划(2022YFB3901605)。

详细信息
    作者简介:

    纪方方,博士生,主要研究方向为SAR数据处理。jiffang@126.com

    通讯作者:

    杨书成,博士,副研究员。yangsc@casm.ac.cn

A Hierarchical Urban Airborne ArrayInSAR Point Cloud Noise Suppression Method

  • 摘要: 在机载阵列干涉合成孔径雷达系统( Array Interferometric Synthetic Aperture Radar,ArrayInSAR)数据成像过程中,由于受到系统热噪声、通道幅度-相位不一致、电磁波多路径干扰等因素影响,机载ArrayInSAR点云中存在大量噪声,严重影响三维重建精度。因此在分析了机载ArrayInSAR点云噪声特征的基础上,提出一种层次化的机载ArrayInSAR点云去噪方法。首先根据机载ArrayInSAR点云中噪声点与非噪声点的分布对噪声进行类别划分,然后集成基于自适应阈值的混合滤波算法、基于法向量和曲率改进的双边滤波算法、基于面状信息拟合的多路径干扰噪声去除算法,实现城区机载ArrayInSAR点云层次化噪声抑制。为验证有效性,将提出方法与其他经典去噪方法进行了效果比较,结果表明,所提方法在去噪完整度、正确率和质量评价指标等方面均优于经典方法,证明该方法能提高机载ArrayInSAR点云精度,为基于机载ArrayInSAR点云的三维重建提供高质量数据。
    Abstract: Objectives: In the process of data imaging in the airborne Array Interferometric Synthetic Aperture Radar (ArrayInSAR), due to the influence of system thermal noise, channel amplitude-phase inconsistency, electromagnetic multipath interference and other factors, there is a lot of noise in the airborne ArrayInSAR point cloud, which seriously affects the 3D reconstruction accuracy based on ArrayInSAR point cloud. Methods: Based on the analysis of the noise characteristics of the airborne ArrayInSAR point cloud, proposed a hierarchical airborne ArrayInSAR point cloud noise suppression(HPCNS) method. Firstly, according to the distribution of noise points and non-noise points in the ArrayInSAR point cloud, the noise is divided into outlier noise, channel amplitude-phase inconsistency errors noise and multipath interference noise. Then, a hybrid filtering algorithm based on adaptive threshold, a bilateral filtering algorithm based on normal vector and curvature improvement, and a multipath noise removal algorithm based on surface information fitting are integrated to process the three kinds of noise, and finally realize the hierarchical noise suppression of the airborne ArrayInSAR point cloud in urban areas. Results: In order to verify the effectiveness of HPCNS method, the denoising effect of HPCNS method is compared with other classical denoising methods. The results show that HPCNS method is superior to other classical denoising methods in the aspects of denoising integrity, accuracy and quality evaluation index. Conclusions: The hierarchical ArrayInSAR point cloud noise suppression method can better remove various types of noise in the ArrayInSAR point cloud data, significantly improve the quality of the airborne ArrayInSAR point cloud, provide high-quality data for three-dimensional reconstruction based on the airborne ArrayInSAR point cloud, and provide better data support for intelligent mapping.
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出版历程
  • 收稿日期:  2025-01-07

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