Abstract

This paper proposes a simple and fast method to estimate Atmospheric Phase Screens (APSs) by jointly exploit a stack of Synthetic Aperture Radar (SAR) images and a dataset of GNSS-derived atmospheric product. The output of this processing is conceived to be ingested by Numerical Weather Prediction Models (NWPMs) to improve weather forecasts. In order to provide wide and dense area coverage and to respect requirements in terms of spatial resolution of ingestion products in NWPMs, both Permanent Scatterers (PSs) and Distributed Scatterers (DSs) are jointly exploited. While the formers are by definition stable targets, but unevenly distributed, the latter are ubiquitous but stable only within a certain temporal baseline that can vary depending on the operational frequency of the radar. The proposed method is thus particularly suited for C, L, and P band missions with low temporal baseline between two consecutive acquisitions of the same scene: these conditions, that are both necessary to provide the dense space-time coverage required by meteorologists, allow for a reliable and robust estimation of APSs thanks to the intrinsic limitation of temporal decorrelation. The proposed technique integrates Zenith Total Delay (ZTD) products computed on a very sparse grid from a network of GNSS stations to correct for SAR orbital errors and to provide the missing phase constant from the derived APS map. In this paper, the complete workflow is explained, and a comparison of the derived APSs is performed with phase screens derived from state-of-the-art SAR processing workflow (SqueeSAR®).

Highlights

  • A radar signal is affected by propagation delay when it passes through the atmosphere [1,2,3]

  • It is useful to recognize that, even if the Digital Elevation Model (DEM) used is not very accurate both in horizontal and vertical resolution, the error induced on the phase is negligible since the baseline are usually in the order of a few tens of meters, while the slant range distance R for a space-borne platform is the hundreds of thousands of meters

  • This paper proposes a technique aimed at estimating in a fast, robust, and reliable way atmospheric phase screens from a stack of focused and coregistered Synthetic Aperture Radar (SAR) images, for the ingestion into Numerical Weather Prediction Models (NWPMs)

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Summary

Introduction

A radar signal is affected by propagation delay when it passes through the atmosphere [1,2,3]. The so-called Permanent Scatterers (PSs) are targets showing high stability over long periods and, high accuracy in the estimate of the APS can be reached, but PSs are very often sparse or even not present in the scene (for example in forested or agricultural areas) This sparseness prevents the estimation of dense atmospheric maps and the fulfillment of spatial requirements for NWPM ingestion. Several works have been done in literature in the field of mapping Precipitable Water Vapor (PWV) using SAR acquisitions aimed at the ingestion into NWMPs [14,19,20] These works generally exploit a set of interferograms formed between interferometric couples with short temporal baselines in order to reduce temporal decorrelation and noise in the estimate. Requirements for NWPM Ingestion, SAR Atmospheric Signal Characterization, and Orbit Requirements

Requirements for NWPM Ingestion
Atmospheric Contribution in SAR Images
Orbit Accuracy Requirements
Target Characterization
Topographic Phase Compensation
Phase Estimation via Phase Linking
Phase Linking for APS Estimation
Phase Unwrapping
Orbit Correction
Dataset
May 2017
Variograms and Radially Average Spectra
Findings
Conclusions
Full Text
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