{"title":"基于TSPA框架的多基线SAR干涉图无限范数相位展开方法","authors":"Yang Lan, Hanwen Yu, M. Xing, Jixiang Fu","doi":"10.1109/IGARSS39084.2020.9323551","DOIUrl":null,"url":null,"abstract":"Phase unwrapping (PU) is a key step for the synthetic aperture radar (SAR) interferometry (InSAR). Single-baseline (SB) PU and multi-baseline (MB) PU are two independently developed technologies, each of which has its own advantages and disadvantages. A two-stage programming-based MB PU method (TSPA) proposed by Yu [1] establishes a connection between the MB and SB PU methods. TSPA breaks the limitation of the phase continuity assumption by using the Chinese remainder theorem (CRT), and uses the minimum-cost flow (MCF) optimization model to obtain the PU result. TSPA can be regarded as a framework for solving MB PU problems. In this paper, we studied how to transplant the infinity-norm ($L^{\\infty}$-norm) optimization model into TSPA framework. Under the TSPA MB PU framework, a $L^{\\infty}$-norm based MB PU method (referred to as Inf-TSPA) is proposed to solve the problem of low PU accuracy of the $L^{\\infty}$-norm SB PU method. The experimental results on the simulated and the realistic MB InSAR data sets verify that the performance of Inf-TSPA is significantly improved compared to the $L^{\\infty}$-norm SB PU method.","PeriodicalId":444267,"journal":{"name":"IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium","volume":"17 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An Infinity-Norm-Based Phase Unwrapping Method with TSPA Framework for Multi-Baseline SAR Interferograms\",\"authors\":\"Yang Lan, Hanwen Yu, M. Xing, Jixiang Fu\",\"doi\":\"10.1109/IGARSS39084.2020.9323551\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Phase unwrapping (PU) is a key step for the synthetic aperture radar (SAR) interferometry (InSAR). Single-baseline (SB) PU and multi-baseline (MB) PU are two independently developed technologies, each of which has its own advantages and disadvantages. A two-stage programming-based MB PU method (TSPA) proposed by Yu [1] establishes a connection between the MB and SB PU methods. TSPA breaks the limitation of the phase continuity assumption by using the Chinese remainder theorem (CRT), and uses the minimum-cost flow (MCF) optimization model to obtain the PU result. TSPA can be regarded as a framework for solving MB PU problems. In this paper, we studied how to transplant the infinity-norm ($L^{\\\\infty}$-norm) optimization model into TSPA framework. Under the TSPA MB PU framework, a $L^{\\\\infty}$-norm based MB PU method (referred to as Inf-TSPA) is proposed to solve the problem of low PU accuracy of the $L^{\\\\infty}$-norm SB PU method. The experimental results on the simulated and the realistic MB InSAR data sets verify that the performance of Inf-TSPA is significantly improved compared to the $L^{\\\\infty}$-norm SB PU method.\",\"PeriodicalId\":444267,\"journal\":{\"name\":\"IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium\",\"volume\":\"17 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-09-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IGARSS39084.2020.9323551\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IGARSS39084.2020.9323551","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Infinity-Norm-Based Phase Unwrapping Method with TSPA Framework for Multi-Baseline SAR Interferograms
Phase unwrapping (PU) is a key step for the synthetic aperture radar (SAR) interferometry (InSAR). Single-baseline (SB) PU and multi-baseline (MB) PU are two independently developed technologies, each of which has its own advantages and disadvantages. A two-stage programming-based MB PU method (TSPA) proposed by Yu [1] establishes a connection between the MB and SB PU methods. TSPA breaks the limitation of the phase continuity assumption by using the Chinese remainder theorem (CRT), and uses the minimum-cost flow (MCF) optimization model to obtain the PU result. TSPA can be regarded as a framework for solving MB PU problems. In this paper, we studied how to transplant the infinity-norm ($L^{\infty}$-norm) optimization model into TSPA framework. Under the TSPA MB PU framework, a $L^{\infty}$-norm based MB PU method (referred to as Inf-TSPA) is proposed to solve the problem of low PU accuracy of the $L^{\infty}$-norm SB PU method. The experimental results on the simulated and the realistic MB InSAR data sets verify that the performance of Inf-TSPA is significantly improved compared to the $L^{\infty}$-norm SB PU method.