TanDEM-X (TerraSAR-X add-on for Digital Elevation Measurements) is an innovative formation flying radar mission that opens a new era in spaceborne radar remote sensing. The primary objective is the acquisition of a global Digital Elevation Model (DEM) with unprecedented accuracy (12 m horizontal and 2 m vertical resolution). This goal is achieved by extending the TerraSAR-X synthetic aperture radar (SAR) mission by a second, TerraSAR-X like satellite (TDX) flying in close formation with TerraSAR-X (TSX). Both satellites form together a large singlepass SAR interferometer with the opportunity for flexible baseline selection. This enables the acquisition of highly accurate cross-track interferograms without the inherent accuracy limitations imposed by repeat-pass interferometry due to temporal decorrelation and atmospheric disturbances. Besides the primary goal of the mission, several secondary mission objectives based on along-track interferometry as well as new bistatic and multistatic SAR techniques have been defined, representing an important and innovative asset of the TanDEM-X mission. TanDEM-X is implemented in the framework of a public-private partnership between the German Aerospace Center (DLR) and EADS Astrium GmbH. The TanDEM-X mission was successfully launched in June 2010 and started operational data acquisition in December 2010. This paper provides an overview of the TanDEM-X mission and summarizes its actual status and performance. Furthermore, results from several scientific radar experiments will be presented that show the great potential of future formation flying interferometric SAR missions to serve novel remote sensing applications.
Capon's minimum-variance method (MVM) and Amplitude and Phase Estimation (APES) spectral estimation algorithms can be applied to SAR processing to improve the resolution and suppress sidelobe levels. In this paper, we use Capon/APES based SAR reprocessing algorithms to increase the Persistent Scatterer (PS) density in Persistent Scatterer Interferometry (PSI). We propose a Persistent Scatterer Candidate (PSC) selection algorithm applicable to the super-resolution reprocessed images and the corresponding processing chain. The performance of the proposed algorithm is evaluated by a number of simulations and a stack of TerraSAR-X data. The results show that the Capon algorithm outperforms others in PSC selection. We present a full PSI time-series analysis on the PSCs extracted from the Capon reprocessed stacks. The results show that the PS density is increased between 50% and 60%, while their interferometric quality is maintained.
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