Optimization of PSInSAR networks with application to TomoSAR for full detection of single and double persistent scatterers
Publication in refereed journal

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摘要In this paper, we develop an optimized network to achieve the full detection of single and double persistent scatterers (PSs) in SAR tomography (TomoSAR). The two-tier network used in persistent scatterer interferometry (PSInSAR) is applied to TomoSAR. Adaptive network densification is constructed to improve global connectivity in the first-tier network. This optimization contributes to improving the connectivity of different clusters by sacrificing computational efficiency slightly. In the second-tier network, we develop an omnidirectional point extension method by progressively constructing local networks and multi-directional extension. This contributes to identifying scatterers that are far away from the reference points in the first-tier network. This improved point extension method can achieve the full extraction of single and double PSs, which is especially applicable in areas with unevenly and sparsely distributed PSs. To validate these improvements, we applied the method to the western reclaimed area of Shenzhen, China with offshore islands and facilities using 30 COSMO-SkyMed images.
著者Ma PF, Liu YZ, Wang WX, Lin H
期刊名稱Remote Sensing Letters
出版年份2019
月份8
卷號10
期次8
出版社TAYLOR & FRANCIS LTD
頁次717 - 725
國際標準期刊號2150-704X
電子國際標準期刊號2150-7058
語言英式英語
Web of Science 學科類別Remote Sensing;Imaging Science & Photographic Technology;Remote Sensing;Imaging Science & Photographic Technology

上次更新時間 2020-29-05 於 00:28