A Satellite Selection Algorithm for GNSS-R InSAR Elevation Deformation Retrieval

Jingyan Yu;Yunlong Zhu;Zhixin Deng;Yanling Zhao
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Abstract

The global navigation satellite system (GNSS) reflectometry synthetic aperture radar (SAR) interferometry (GNSS-R InSAR) system enables elevation deformation retrieval using a single satellite. However, variations in bistatic configurations and the generally low accuracy of most satellites necessitate a refined satellite selection method. Thus, this letter proposes a satellite selection algorithm for GNSS-R InSAR, aiming to optimize satellite selection and data acquisition time to improve the precision of elevation deformation monitoring. First, the interferometric phase model based on the repeat-pass concept was established using GPS L5 signals. Second, a satellite selection algorithm was proposed that incorporates constraints on resolution cells, spatial baseline, and phase sensitivity for elevation deformation, derived from an analysis of the repeat-pass spatial baseline of GNSS satellites, interferometric phase sensitivity, and the maximum deformation range. Third, 24 sets of repeat-pass data were collected, and the experimental results validate the effectiveness of this single-satellite selection approach.
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GNSS-R InSAR高程变形检索的卫星选择算法
全球导航卫星系统(GNSS)反射测量合成孔径雷达(SAR)干涉测量(GNSS- r InSAR)系统能够使用单个卫星进行高程变形检索。然而,由于双基地配置的变化和大多数卫星的普遍低精度,需要一种改进的卫星选择方法。为此,本文提出了一种GNSS-R InSAR卫星选择算法,旨在优化卫星选择和数据采集时间,提高高程变形监测精度。首先,利用GPS L5信号建立了基于重复通概念的干涉相位模型;其次,通过对GNSS卫星重复通道空间基线、干涉相位灵敏度和最大变形范围的分析,提出了一种结合分辨率单元、空间基线和高程变形相位灵敏度约束的卫星选择算法。再次,采集了24组重复卫星数据,实验结果验证了该方法的有效性。
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