This article reports the Phase A study results of the interferometric extension of the high-resolution wide-swath (HRWS) mission with three MirrorSAR satellites. According to the MirrorSAR concept, small, low-cost, transponder-like receive-only satellites without radar signal demodulation, digitization, memory storage, downlink, and synchronization are added to the planned German X-band HRWS mission. The MirrorSAR satellites fly a triple helix orbit in close formation around the HRWS orbit and span multiple single-pass interferometric baselines. A comprehensive system engineering and performance analysis is provided that includes orbit formation, MirrorLink, Doppler steering, antenna pattern and swath design, multi-static echo window timing, SAR performance, height performance, and coverage analysis. The overall interferometric system design analysis of Phase A is presented. The predicted performance of the global digital elevation model (DEM) is improved by one order of magnitude compared to presently available global DEM products such as the TanDEM-X DEM.

In this paper, a dual-frequency and dual-baseline (DFDB) processing framework for the extraction of high-precision terrain information from airborne interferometric synthetic aperture radar (SAR) data is presented. Specifically, we propose the use of two single-pass data sets acquired simultaneously in two different frequency bands and two large-baseline repeat-pass data sets also acquired simultaneously in two frequency bands. The configuration profits from the stability of the single-pass derived elevation maps in relation to spatially correlated artifacts as well as from the increased sensitivity associated with large-baseline acquisitions. Moreover, the dual-frequency nature of the data set enables the tackling of the phase unwrapping issue, promoting the retrieval of unambiguous measurements. Several algorithms for the interferometric processing of the DFDB airborne data set are proposed, including the outline of multichannel phase calibration and unwrapping error correction strategies and approaches to remove spatially correlated artifacts and extract the common underlying topography. Elevation models generated from a DFDB data set acquired with the airborne F-SAR sensor over tidal flats in northern Germany are presented, and comparisons with an airborne laser scanner reference show errors with a standard deviation of around 14 cm and a mean absolute deviation of less than 10 cm.

The combination of SCan-On-REceive with continuous variation of the pulse repetition interval during transmission (staggered operation) is a viable option for the acquisition of high-resolution synthetic aperture radar (SAR) data over wide areas. Since the acquired data are not uniformly sampled and contain gaps within the synthetic aperture mainly due to the interruption of reception during transmission (i.e., due to blockage), proper reconstruction strategies must be considered in order to minimize artifacts. Conventionally, large oversampling rates are required to ensure low ambiguity levels, but this is not always feasible due to data-rate constrains. This article presents a detailed analysis of the blockage recovery in the low-oversampling case. Moreover, we propose a data adaptive strategy to optimally perform this step, ensuring the best performance for point-like targets and avoiding degradation for distributed scatters. This paper also presents simulation results that show the impact of staggered data for interferometric applications.

The NASA-ISRO SAR (NISAR) mission will map the Earth’s surface every 12 days using a reflector-feed system with scan-on-receive (SweepSAR) capability. An alternative for continuous swath coverage is to employ staggered SAR operation, i.e., to vary the pulse repetition intervals over time. In this way, the blocked (missing) samples are spread in range and azimuth and can be interpolated prior to focusing. However, the relatively low azimuth oversampling intended for NISAR in combination with the strong non-uniformity of the staggered data grid forbids the use of conventional interpolation kernels. This paper discusses a processing approach for the NISAR staggered data and validates the strategy with simulated data. Moreover, the impact of the staggered operation for contrast-based and interferometric applications is discussed with examples.

The main goal of the TerraSAR-X Add-On for Digital Elevation Measurements (TanDEM-X) mission is the generation of a global digital elevation model (DEM) of unprecedented accuracy and coverage. The global TanDEM-X DEM product became available in 2016, surpassed all expectations, and became a reference for a wide range of Earth science, commercial, and geospatial applications. In addition, new information products, such as DEM change maps (DCMs), have been developed and are available to the geoscience and remote sensing community. Beyond the operational products, new science applications have been demonstrated and are summarized in this article, along with experimental data acquisitions. This article also aims to provide an overview of science activities with TanDEM-X data and science data acquisitions planned for the coming years.

The global Digital Elevation Model (DEM) resulting from the TanDEM-X mission provides information about the world topography with outstanding precision. In fact, performance analysis carried out with the already available data have shown that the global product is well within the requirements of 10 m absolute vertical accuracy and 2 m relative vertical accuracy for flat to moderate terrain. The mission's science phase took place from October 2014 to December 2015. During this phase, bistatic acquisitions with across-track separation between the two satellites up to 3.6 km at the equator were commanded. Since the relative vertical accuracy of InSAR derived elevation models is, in principle, inversely proportional to the system baseline, the TanDEM-X science phase opened the doors for the generation of elevation models with improved quality with respect to the standard product. However, the interferometric processing of the large-baseline data is troublesome due to the increased volume decorrelation and very high frequency of the phase variations. Hence, in order to fully profit from the increased baseline, sophisticated algorithms for the interferometric processing, and, in particular, for the phase unwrapping have to be considered. This paper proposes a novel dual-baseline region-growing framework for the phase unwrapping of the large-baseline interferograms. Results from two experiments with data from the TanDEM-X science phase are discussed, corroborating the expected increased level of detail of the large-baseline DEMs.