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
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
1. College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China;
2. State Key Laboratory of Urban Environmental Process and Digital Simulation, Capital Normal University, Beijing 100048, China;
3. Key Laboratory of 3D Information Acquisition and Application, Ministry of Education, Capital Normal University, Beijing 100048, China; 4. Chinese Academy of Surveying & Mapping, Beijing 100036, China;
5. Key Laboratory of Land Environment and Disaster Monitoring, Ministry of Natural Resources, China University of Mining and Technology, Xuzhou 221116, China
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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