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首页> 外文期刊>Journal of Geodesy >Sentinel-1 TOPS co-registration over low-coherence areas and its application to velocity estimation using the all pairs shortest path algorithm
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Sentinel-1 TOPS co-registration over low-coherence areas and its application to velocity estimation using the all pairs shortest path algorithm

机译:Sentinel-1顶部在低相干区域共同登记及其在使用所有对最短路径算法的速度估计的应用

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The C-band Sentinel-1 A/B satellites in TOPS mode provide unprecedented opportunities for continuous radar mapping of the earth with enhanced revisit frequency. The reliability for routine operational services relies on a very stringent azimuth co-registration accuracy. However, while the enhanced spectral diversity (ESD) technique achieves a co-registration accuracy of better than 0.001 pixels, the accuracy might still be degraded over low-coherence areas due to fast decorrelation. When TOPS time series data are available, the abrupt loss of coherence further affects the estimation accuracy of the network ESD. I integrate a double sample over the burst overlap region with an ESD estimator to reduce the ESD phase error and simultaneously mitigate the abrupt loss of coherence in the time series using the all pairs shortest path algorithm. I further use this algorithm to create a spatio-temporal network of co-registered Sentinel-1 SAR stacks for line-of-sight (LOS) velocity estimation over low-coherence areas. I perform InSAR time series analysis and evaluate the effectiveness of the proposed method using data acquired from descending tracks over representative low-coherence regions in south-western China. For those images suffering from significant low coherence, this method can achieve a better co-registration accuracy than those obtained from the previous network ESD method. By cross-validating descending COSMO-SkyMed data, a 39% uncertainty reduction in the estimated LOS velocity can be achieved when applying a co-registered Sentinel-1 stack with high accuracy and spatio-temporal network evolution.
机译:顶部模式中的C波段哨声-1 A / B卫星为地球的连续雷达映射提供了前所未有的机会,具有增强的Revisit频率。例行操作服务的可靠性依赖于非常严格的方位角共同登记精度。然而,虽然增强的频谱分集(ESD)技术实现了优于0.001像素的共同登记精度,但由于快速去相关性,精度可能仍然在低相干区域上劣化。当顶部时间序列数据可用时,突然的相干损失进一步影响了网络ESD的估计精度。我通过ESD估计器将双重样本集成在突发重叠区域上,以减少ESD相位误差,并同时使用所有对最短路径算法在时间序列中的突然损失。我进一步使用该算法创建共同登记的Sentinel-1 SAR堆栈的时空网络,用于低相干区域的视线(LOS)速度估计。我执行Insar时间序列分析,并评估所提出的方法的有效性,所述方法利用从南部西南部代表低相干地区的下降轨道获取的数据获取。对于患有显着低相干性的图像,该方法可以实现比从先前网络ESD方法获得的那些更好的共同登记精度。通过交叉验证降序的宇宙速度数据,在应用具有高精度和时空网络进化的共同登记的哨声-1堆叠时,可以实现估计的LOS速度的39%的不确定性降低。

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