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分布式散射体(Distributed Scatters, DS)相位优化是DS-InSAR技术关键,本文提出一种新的基于奇异值分解的DS相位优化方法。采用模拟数据和33景覆盖郑州东部白沙镇Sentinel-1A数据对提出方法的可靠性与有效性进行验证和分析。结果表明,与对比DS相位优化方法相比,提出方法对干涉图DS相位优化效果更好,特别是在一些低相干区域仍然可获得较好DS相位优化结果；提出方法在降低DS相位噪声同时可较好地保持地物细节信息。此外,相较于常规PS技术形变监测结果,本文方法高质量监测点密度提高了4.3倍,较对比方法高质量监测点密度提升更显著。模拟与真实数据结果证实了本文提出DS优化方法的有效性,该方法可服务于基于DS-InSAR技术的地表形变监测。
Distributed Scatters (DS) phase optimization is the core of DS-InSAR technology. Taking DS phase optimization as the research object, this paper proposes a new principal component analysis DS phase optimization method based on singular value decomposition. Simulation data and 33 scene coverage of Sentinel-1A data in Baisha Town, eastern Zhengzhou are used to verify the reliability and validity of the proposed method. The results show that, compared with the contrast DS phase optimization method, the proposed method has a better effect on the interferogram DS phase optimization, especially in some areas with poor coherence; In addition, the proposed method can better maintain the detailed information of the ground features while reducing the DS phase noise. Compared with the conventional PS technology deformation monitoring results, the density of high-quality measurement points in this method is increased by 4.3 times, which is more significant than that of the comparative method. The experimental results of simulation and real data confirm the effectiveness of the DS optimization method proposed in this paper, which can be used in the DS-InSAR technology for surface deformation monitoring.