Change Detection within the Processing of the TanDEM-X Change DEM

Over the last years the TanDEM-X mission acquired data for a second global digital elevation model (DEM) the TanDEM-X Change DEM. This new DEM is temporally independent of the former global TanDEM-X DEM and therefore yields the possibility of change detection. In order to decrease the phase noise level the interferometric processing for the Change DEM has been upgraded. This also allows a more accurate change detection. Currently, the processing of the global data is performed operationally. It includes the detection of terrain changes and first examples of detected terrain changes can be presented

The New TanDEM-X Change DEM: Specification and Interferometric Processing

Since 2017, the TanDEM-X mission aims to acquire data globally to generate another (updated) DEM. This new set of acquisitions, which will be complete in 2020, has a clear temporal separation from those used for the TanDEM-X global DEM. It will therefore allow the creation of a temporally independent DEM, the so-called “TanDEM-X Change DEM” enabling the characterization of terrain changes. Since only one global coverage is being acquired, improvements in e.g. the interferometric data processing are necessary. In particular, an edited version of the existing global TanDEM-X DEM is now the "starting point" for the interferometric processing as detailed in this paper

Beyond the 12m TanDEM-X DEM

The standard TanDEM-X product meats HRTI-3 DEM specification and comes with a sample spacing of 12 m.We apply non-local means (NL) interferogram filtering to the TanDEM-X data. In this paper, we present modifications of the original NL filter which render it more appropriate and efficient for massive processing of TanDEM-X data. Further, we investigate the noise reduction properties as well as the resolution and the coherence estimation accuracy of the new NL filter. Simulations and tests with TanDEM-X data hint that the improved DEMs possess a quality close to the HRTI-4 standard. Also future global InSAR missions like Tandem-L will greatly benefit from this type of filters

TerraSAR-X SAR Data Processing

The TerraSAR-X Mission started operational provision of SAR image products to the scientific and commercial user community in January 2008. An essential prerequisite for the excellent quality of the SAR products was the successful execution of a comprehensive commissioning phase (CP) in 2007. Here, the complete SAR system which comprises instrument commanding, instrument SAR data acquisition as well as SAR processing has been characterized, calibrated and verified. Finally SAR image product verification ensured that the product performance parameters are within the specification. Besides the versatile high-resolution X-Band SAR instrument in space, featuring Stripmap, ScanSAR and Spotlight imaging modes in different polarizations, the TerraSAR Multi-Mode SAR Processor (TMSP) is the central part of the ground segment. Most instrument and SAR calibration parameters have been derived on basis of SAR image products generated by the TMSP. Therefore, already in the beginning of the CP the products had to be relatively radiometric calibrated and geometrical undistorted. An indispensable prerequisite for this was the imaging mode independent normalization of the processor gain as well as the incorporation of external information, i.e. a digital elevation model for the projection of the elevation gain antenna pattern onto the terrain surface and a model of the atmosphere accounting for additional propagation delays. During the CP the TMSP has been adjusted to the in-orbit characteristics of the SAR data and instrument internal calibration. This includes adaptations of calibration pulse processing to a modified internal calibration strategy, accounting for duty cycle dependent pulse energy and temperature dependent gain levels as well as a fine tuning of the signal and geometry based Doppler centroid estimation algorithm. Furthermore, the determination of the reference function for range focusing has been optimized. Finally, the spectral weighting of the SAR data has been adjusted in order to obtain well balanced impulse response function properties in terms of resolution, side lobe ratios and azimuth ambiguities. The presentation reviews the essential features of the TMSP, summarizes the TMSP adjustments and presents results of the SAR product verification

TanDEM-X DEM 2020: What is new?

In the last years, the TanDEM-X mission systematically acquired data to create another global DEM, the so-called 'TanDEM-X DEM 2020', mainly between September 2017 and mid-2020. This contribution describes the status of the generation of this second global TanDEM-X DEM with special focus on procedural and algorithmic modifications compared to the first global TanDEM-X DEM

Minimum Cost Flow phase unwrapping supported by multibaseline unwrapped gradient

The objective of the TanDEM-X Mission is the generation of a global high resolution Digital Elevation Model (DEM). To carry out this goal, two interferograms with different baselines will be acquired. We propose a novel two-stage multibaseline phase unwrapping method. Maximum Likelihood Estimation (MLE) is used to reduce the ambiguity and errors in gradient estimation on a pixel-by-pixel basis. Based on these estimates, Minimum Cost Flow (MCF) is used to unwrap the phase accounting for the overall conservative condition of the gradient. Hence the advantages of both techniques are efficiently integrated. Results on simlated data using TerraSAR-X parameters are reported

Multibaseline Gradient Ambiguity Resolution To Support Minimum Cost Flow Phase Unwrapping

The TanDEM-X Mission has as primary objective to generate a high resolution global Digital Elevation Model. This paper proposes a new method for multibaseline Phase Unwrapping which is the critical point of this generation. We propose to combine both Minimum Cost Flow (MCF) and Maximum a Posteriori (MAP) estimation. The latter is used to solve phase gradient ambiguities. The problem is posed as an energy minimization one and solved using Belief Propagation (BP) which is an iterative process. Nevertheless, although very good results are obtained on loopy graphs, it is not guaranteed to converge. Thus, phase unwrapping of the most accurate interferogram is finally performed with the MCF algorithm and takes as input the unwrapped gradients

Phase Unwrapping of Multi-Channel Synthetic Aperture Radar: Application to the TanDEM-X Mission

The contribution of this thesis is the design and development of a new method which combines bistatic high-resolution interferometric data in order to perform a correct and accurate phase unwrapping on a huge amount of data. This is especially dedicated to the TanDEM-X Mission. The Dual-Baseline Phase Unwrapping Correction (DB-PUC) framework addresses this challenge by correcting errors that occurred during the single-baseline PU procedure. It benefits from the additional information available through the differential interferogram and the stereo-radargrammetric phase. The former is used to correct the ambiguity bands of the misestimated unwrapped phases. The latter enables the assessment of the differential unwrapped phase and the correction of its potential errors region-wise. The region-wise correction of the integer number of cycles allows it to be less sensitive to noise and possible temporal changes. The DB-PUC framework is used during the operational processing (or re-processing) of the TanDEM-X acquisitions, which are used for the generation of the final global DEM. The second global coverage has been unwrapped with the proposed approach with a success rate of 96.5%

The dual-baseline interferometric processing chain for the TanDEM-X mission

During the second operational year of the TanDEM-X mission, a second coverage of the whole land mass is acquired in order to produce a high accurate and high resolution DEM from a combination of both data sets. This paper presents the dual-baseline interferometric processing chain. Its main steps consist of coregistering the different interferograms (having different baselines), of unwrapping the phases and of comparing them to eliminate the possible unwrapping errors