{"title":"用于地形重建的二维相位解包:改进的两阶段编程方法","authors":"Yan Yan;Hanwen Yu;Taoli Yang","doi":"10.1109/JSTARS.2024.3487920","DOIUrl":null,"url":null,"abstract":"The interferometric synthetic aperture radar (InSAR) is able to reconstruct the Earth's surface topography with a meter-level accuracy when two-dimensional phase unwrapping (PU) is properly implemented. The two-stage programming approach (TSPA) can convert the ill-posed PU problem into a well-posed problem by integrating perpendicular baseline diversity in multiple (\n<inline-formula><tex-math>$\\ge$</tex-math></inline-formula>\n2) interferograms, and is currently among the most commonly used multibaseline (MB) PU algorithms. Nevertheless, TSPA still faces two challenges in real-world applications: first, TSPA cannot ensure exceptional performance for any complex topographic scenarios, and second, the PU error of short-baseline interferometric pair tends to propagate into the PU solution of long-baseline interferometric pair, degrading height accuracy. To overcome these issues, a refined TSPA (R-TSPA) MB PU algorithm is proposed in this article. R-TSPA contains two PU procedures under the framework of TSPA, where procedure 1 unwraps the flattened interferograms with TSPA, and procedure 2 re-estimates and reunwraps the erroneous ambiguity number gradients with TSPA. It is demonstrated that R-TSPA outperforms the conventional single-baseline PU algorithms and TSPA with actual InSAR datasets in western Sichuan Province and Tibet Autonomous Region of China, revealing its potentials in accurately mapping topography and broadening application scopes of InSAR.","PeriodicalId":13116,"journal":{"name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","volume":"17 ","pages":"20304-20314"},"PeriodicalIF":4.7000,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10737667","citationCount":"0","resultStr":"{\"title\":\"Two-Dimensional Phase Unwrapping for Topography Reconstruction: A Refined Two-Stage Programming Approach\",\"authors\":\"Yan Yan;Hanwen Yu;Taoli Yang\",\"doi\":\"10.1109/JSTARS.2024.3487920\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The interferometric synthetic aperture radar (InSAR) is able to reconstruct the Earth's surface topography with a meter-level accuracy when two-dimensional phase unwrapping (PU) is properly implemented. The two-stage programming approach (TSPA) can convert the ill-posed PU problem into a well-posed problem by integrating perpendicular baseline diversity in multiple (\\n<inline-formula><tex-math>$\\\\ge$</tex-math></inline-formula>\\n2) interferograms, and is currently among the most commonly used multibaseline (MB) PU algorithms. Nevertheless, TSPA still faces two challenges in real-world applications: first, TSPA cannot ensure exceptional performance for any complex topographic scenarios, and second, the PU error of short-baseline interferometric pair tends to propagate into the PU solution of long-baseline interferometric pair, degrading height accuracy. To overcome these issues, a refined TSPA (R-TSPA) MB PU algorithm is proposed in this article. R-TSPA contains two PU procedures under the framework of TSPA, where procedure 1 unwraps the flattened interferograms with TSPA, and procedure 2 re-estimates and reunwraps the erroneous ambiguity number gradients with TSPA. 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引用次数: 0
摘要
干涉合成孔径雷达(InSAR)在正确实施二维相位解包(PU)的情况下,能够以米级精度重建地球表面地形。两阶段程序设计方法(TSPA)可以通过在多个($\ge$2)干涉图中整合垂直基线分集,将问题不明确的相位解包问题转化为问题明确的相位解包问题,是目前最常用的多基线(MB)相位解包算法之一。然而,TSPA 在实际应用中仍面临两个挑战:首先,TSPA 无法确保在任何复杂地形场景下都能发挥卓越性能;其次,短基线干涉对的 PU 误差往往会传播到长基线干涉对的 PU 解中,从而降低高度精度。为了克服这些问题,本文提出了一种改进的 TSPA(R-TSPA)MB PU 算法。R-TSPA 包含两个 TSPA 框架下的 PU 程序,其中程序 1 利用 TSPA 对扁平化干涉图进行解包,程序 2 利用 TSPA 对错误的模糊数梯度进行重新估计和重新包扎。在四川省西部和中国西藏自治区的实际 InSAR 数据集上,R-TSPA 的性能优于传统的单基线 PU 算法和 TSPA,显示了其在精确绘制地形图和拓宽 InSAR 应用范围方面的潜力。
Two-Dimensional Phase Unwrapping for Topography Reconstruction: A Refined Two-Stage Programming Approach
The interferometric synthetic aperture radar (InSAR) is able to reconstruct the Earth's surface topography with a meter-level accuracy when two-dimensional phase unwrapping (PU) is properly implemented. The two-stage programming approach (TSPA) can convert the ill-posed PU problem into a well-posed problem by integrating perpendicular baseline diversity in multiple (
$\ge$
2) interferograms, and is currently among the most commonly used multibaseline (MB) PU algorithms. Nevertheless, TSPA still faces two challenges in real-world applications: first, TSPA cannot ensure exceptional performance for any complex topographic scenarios, and second, the PU error of short-baseline interferometric pair tends to propagate into the PU solution of long-baseline interferometric pair, degrading height accuracy. To overcome these issues, a refined TSPA (R-TSPA) MB PU algorithm is proposed in this article. R-TSPA contains two PU procedures under the framework of TSPA, where procedure 1 unwraps the flattened interferograms with TSPA, and procedure 2 re-estimates and reunwraps the erroneous ambiguity number gradients with TSPA. It is demonstrated that R-TSPA outperforms the conventional single-baseline PU algorithms and TSPA with actual InSAR datasets in western Sichuan Province and Tibet Autonomous Region of China, revealing its potentials in accurately mapping topography and broadening application scopes of InSAR.
期刊介绍:
The IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing addresses the growing field of applications in Earth observations and remote sensing, and also provides a venue for the rapidly expanding special issues that are being sponsored by the IEEE Geosciences and Remote Sensing Society. The journal draws upon the experience of the highly successful “IEEE Transactions on Geoscience and Remote Sensing” and provide a complementary medium for the wide range of topics in applied earth observations. The ‘Applications’ areas encompasses the societal benefit areas of the Global Earth Observations Systems of Systems (GEOSS) program. Through deliberations over two years, ministers from 50 countries agreed to identify nine areas where Earth observation could positively impact the quality of life and health of their respective countries. Some of these are areas not traditionally addressed in the IEEE context. These include biodiversity, health and climate. Yet it is the skill sets of IEEE members, in areas such as observations, communications, computers, signal processing, standards and ocean engineering, that form the technical underpinnings of GEOSS. Thus, the Journal attracts a broad range of interests that serves both present members in new ways and expands the IEEE visibility into new areas.