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基于鲁棒M估计协方差矩阵相位优化的DSInSAR矿区形变监测研究
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作者 曾祥凯 孙凤娜 +2 位作者 陈东兴 段文再 滕文龙 《中国矿业》 北大核心 2024年第3期142-151,共10页
针对时序干涉合成孔径雷达(Interferometric Synthetic Aperture Radar,InSAR)技术在矿区所处区域内耕地、裸地等自然地表地物上无法识别有效监测点信息,致使矿区地表形变信息不足及形变解译困难等问题,提出一种基于鲁棒M估计协方差矩... 针对时序干涉合成孔径雷达(Interferometric Synthetic Aperture Radar,InSAR)技术在矿区所处区域内耕地、裸地等自然地表地物上无法识别有效监测点信息,致使矿区地表形变信息不足及形变解译困难等问题,提出一种基于鲁棒M估计协方差矩阵特征值分解相位优化的DSInSAR技术,并基于34景Sentinel-1A影像获取了霄云煤矿2022年的地表时序形变。推导基于鲁棒M估计协方差矩阵估计公式,提高对样本异常值及异质像素的鲁棒性,开展基于鲁棒M估计协方差矩阵特征值分解的相位优化处理,分析了上述优化模型与通用相位优化模型的相似性,最终通过对优化估计相位开展相位信息解译处理来获取最终的形变信息。实验结果表明:基于鲁棒M估计协方差矩阵特征值分解相位优化的DSInSAR技术较常规SBAS技术及基于最大似然估计协方差矩阵的DSInSAR技术在监测点密度上分别提高了约11.4倍、0.2倍,且与水准数据对比具有最小的均方根误差,约22 mm;此外,霄云煤矿共包含三个主要形变场,其地表沉降的时序变化呈现出较显著的非线性趋势,煤矿内地表的视线向最大沉降量约418 mm。研究成果为矿区地表形变规律反演及矿区灾害防控提供重要数据支撑。 展开更多
关键词 dsinsar技术 鲁棒协方差矩阵 特征值分解 相位优化 矿区形变监测
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先验信息驱动的DSInSAR自适应相位优化算法
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作者 李世金 卞正富 +5 位作者 高延东 张书毕 郑南山 张秋昭 张艳锁 田雨 《中国矿业大学学报》 EI CAS CSCD 北大核心 2024年第2期409-420,共12页
相位优化是分布式散射体干涉合成孔径雷达(Distributed Scatterers Interferometric Synthetic Aperture Radar,DSInSAR)技术中提升相位信噪比的关键步骤.为了改善现有相位优化算法在矿区大梯度形变对应密集条纹处的相位信息严重损失问... 相位优化是分布式散射体干涉合成孔径雷达(Distributed Scatterers Interferometric Synthetic Aperture Radar,DSInSAR)技术中提升相位信噪比的关键步骤.为了改善现有相位优化算法在矿区大梯度形变对应密集条纹处的相位信息严重损失问题,提出一种基于先验信息驱动的DSInSAR自适应相位优化算法.算法首先采用常规小基线集技术反演初始时序形变相位,通过时序相位预处理获取先验形变相位信息;然后将其从原始单视复数(Single Look Complex,SLC)相位中去除,获取SLC残余相位,结合相干性次幂加权策略构建残余相位优化模型,通过先验形变相位补偿,估计最终优化相位.试验结果表明:提出算法可有效兼顾大梯度形变场对应条纹密集区域的相位信息保护及噪声抑制,且有效提升了大梯度形变区域的监测点密度及监测精度,较常规优化算法具有更好的自适应效果及优化性能. 展开更多
关键词 dsinsar 相位优化 先验信息 矿区形变监测
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The monitoring and analysis of the coastal lowland subsidence in the southern Hangzhou Bay with an advanced time-series InSAR method 被引量:6
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作者 HAN Peng YANG Xiaoxia +1 位作者 BAI Lin SUN Qishi 《Acta Oceanologica Sinica》 SCIE CAS CSCD 2017年第7期110-118,共9页
Time-series InSAR analysis(e.g., permanent scatterers(PSInSAR)) has been proven as an effective technology in monitoring ground deformation over urban areas. However, it is a big challenge to apply this technology... Time-series InSAR analysis(e.g., permanent scatterers(PSInSAR)) has been proven as an effective technology in monitoring ground deformation over urban areas. However, it is a big challenge to apply this technology in coastal regions due to the lack of man-made targets. An distributed scatterers interferometric synthetic aperture radar(DSInSAR) is developed to solve the problem of insufficient samples and low reliability in monitoring coastal lowland subsidence, by applying a spatially adaptive filter and an eigendecomposition algorithm to estimating the optimal phase of statistically homogeneous distributed scatterers(DSs). Twenty-four scenes of COSMO-Sky Med images acquired between 2013 and 2015 are used to retrieve the land subsidence over the Shangyu District on south coast of the Hangzhou Bay, Zhejiang Province, China. The spatial pattern of the land subsidence obtained by the PS-InSAR and the DSInSAR coincides with each other, but the density of the DSs is three point five times higher than the permanent scatterers(PSs). Validated by precise levelling data over the same period, the DSInSAR method achieves an accuracy of ±5.0 mm/a which is superior to the PS-InSAR with±5.5 mm/a. The land subsidence in the Shangyu District is mainly distributed in the urban areas, industrial towns and land reclamation zones, with a maximum subsidence rate -30.2 mm/a. The analysis of geological data, field investigation and historical reclamation data indicates that human activities and natural compaction of reclamation material are major causes of the detected land subsidence. The results demonstrate that the DSInSAR method has a great potential in monitoring the coastal lowland subsidence and can be used to further investigate subsidence-related environmental issues in coastal regions. 展开更多
关键词 coastal areas land subsidence dsinsar PSInSAR leveling observation Hangzhou Bay in China
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