Sentinel-1 Imaging Performance Verification with TerraSAR-X

This paper presents dedicated analyses of TerraSAR-X data with respect to the Sentinel-1 TOPS imaging mode. First, the analysis of Doppler centroid behaviour for high azimuth steering angles, as occurs in TOPS imaging, is investigated followed by the analysis and compensation of residual scalloping. Finally, the Flexible-Dynamic BAQ (FD-BAQ) raw data compression algorithm is investigated for the first time with real TerraSAR-X data and its performance is compared to state-of-the-art BAQ algorithms. The presented analyses demonstrate the improvements of the new TOPS imaging mode as well as the new FD-BAQ data compression algorithm for SAR image quality in general and in particular for Sentinel-1

Advanced Multi-Channel SAR Imaging - Measured Data Demonstration

Synthetic Aperture Radar (SAR) is a well-established technique for remote sensing of the Earth. However, conventional SAR systems relying on only a single transmit and receive aperture are not capable of imaging a wide swath with high spatial resolution. Multi-channel SAR concepts, such as systems based on multiple receive apertures in azimuth, promise to overcome these restrictions, thus enabling high-resolution wide-swath imaging. Analysis revealed that these systems imperatively require sophisticated digital processing of the received signals in order to guarantee full performance independently of the spatial sample distribution imposed by the applied pulse repetition frequency (PRF). A suitable algorithm to cope with these challenges of multi-channel data is given by the “multi-channel reconstruction algorithm”, which demonstrated in comprehensive analysis and system design examples its potential for high perform-ance SAR imaging. In this context, various optimization strategies were investigated and aspects of operating multi-channel systems in burst modes such as ScanSAR or TOPS were discussed. Furthermore, a first proof-of-principle showed the algorithm’s applicability to measured multi-channel X-band data gathered by the German Aerospace Cen-ter’s (DLR) airborne F-SAR system. As a next step in the framework of multi-channel azimuth processing, this paper builds on the results recalled above and continues two paths. Firstly, focus is turned to further optimization of the proc-essing algorithm by investigating the classical Space-Time Adaptive Processing (STAP) applied to SAR. Secondly, attention is turned to the analysis of the measured multi-channel data by elaborating the impact and compensation of channel mismatch and by verifying the derived theory

A Network-Based Enhanced Spectral Diversity Approach for TOPS Time-Series Analysis

For multitemporal analysis of synthetic aperture radar (SAR) images acquired with a terrain observation by progressive scan (TOPS) mode, all acquisitions from a given satellite track must be coregistered to a reference coordinate system with accuracies better than 0.001 of a pixel (assuming full SAR resolution) in the azimuth direction. Such a high accuracy can be achieved through geometric coregistration, using precise satellite orbits and a digital elevation model, followed by a refinement step using a time-series analysis of coregistration errors. These errors represent the misregistration between all TOPS acquisitions relative to the reference coordinate system. We develop a workflow to estimate the time series of azimuth misregistration using a network-based enhanced spectral diversity (NESD) approach, in order to reduce the impact of temporal decorrelation on coregistration. Example time series of misregistration inferred for five tracks of Sentinel-1 TOPS acquisitions indicates a maximum relative azimuth misregistration of less than 0.01 of the full azimuth resolution between the TOPS acquisitions in the studied areas. Standard deviation of the estimated misregistration time series for different stacks varies from 1.1e-3 to 2e-3 of the azimuth resolution, equivalent to 1.6-2.8 cm orbital uncertainty in the azimuth direction. These values fall within the 1-sigma orbital uncertainty of the Sentinel-1 orbits and imply that orbital uncertainty is most likely the main source of the constant azimuth misregistration between different TOPS acquisitions. We propagate the uncertainty of individual misregistration estimated with ESD to the misregistration time series estimated with NESD and investigate the different challenges for operationalizing NESD

Ground Processing of Cassini RADAR Imagery of Titan

The Cassini RADAR instrument onboard the Cassini Orbiter is currently collecting SAR Imagery of the surface of Saturn's largest moon, Titan. This paper describes the ground processing of Cassini SAR data. We focus upon the unusual features of the data and how these features impact the processing. We exhibit a data dependent mechanism we have implemented for eliminating artifacts due to attitude and ephemeris knowledge error. Finally we describe how we trade-off SAR performance vs. area of coverage when we design our spacecraft pointing profiles

Interferometric SAR signal analysis in the presence of squint

This paper develops an analysis of the SAR impulse response function from the interferometric point of view, with the intention of studying its phase behavior in the presence of high squint angle values. It will be pointed out that in this case, a phase ramp is present in the range direction, which, in combination with a certain degree of misregistration between the two images induces an offset in the generated interferometric phase. This behavior, if not compensated, imposes strong limits on the performance of the interferometric techniques in a squinted case, especially for airborne SAR systems. The article proposes two new techniques, which are appropriate to correct the phase bias coming from this source. The first one is based on a modification of the azimuth compression filter, which cancels the phase ramp of the range impulse response function for one specific squint value. In case the SAR processing is performed with variable squint over range, the authors propose a second method oriented to estimating the expected misregistration and thus, the phase bias by means of an iterative approach. Simulated data as well as real corner reflector responses are used to show that the correct topography can be recovered precisely even in the presence of phase bias coming from the squinted geometry.Peer Reviewe

Processing of Sliding Spotlight and TOPS SAR Data Using Baseband Azimuth Scaling

This paper presents an efficient phase preserving processor for the focusing of data acquired in sliding spotlight and TOPS (Terrain Observation by Progressive Scans) imaging modes. They share in common a linear variation of the Doppler centroid along the azimuth dimension, which is due to a steering of the antenna (either mechanically or electronically) throughout the data take. Existing approaches for the azimuth processing can become inefficient due to the additional processing to overcome the folding in the focused domain. In this paper a new azimuth scaling approach is presented to perform the azimuth processing, whose kernel is exactly the same for sliding spotlight and TOPS modes. The possibility to use the proposed approach to process ScanSAR data, as well as a discussion concerning staring spotlight, are also included. Simulations with point-targets and real data acquired by TerraSAR-X in sliding spotlight and TOPS modes are used to validate the developed algorithm

Extension of Wavenumber Domain Focusing for spotlight COSMO-SkyMed SAR Data

In this work we describe a method to handle curved orbits in wavenumber domain focusing algorithm for high-resolution SAR data acquired by Low Earth Orbit satellites using spotlight mode. The stand..

Moving Target Azimuth Velocity Estimation for the MASA Mode Based on Sequential SAR Images

A novel azimuth velocity estimation method is proposed based on the multiple azimuth squint angles (MASA) imaging mode, acquiring sequential synthetic aperture radar images with different squint angles and time lags. The MASA mode acquisition geometry is given first, and the effect of target motion on azimuth offset and slant range offset is discussed in detail. Then, the azimuth velocity estimation accuracy is analyzed, considering the errors caused by registration, defocusing, and range velocity. Moreover, the interaction between target azimuth velocity and range velocity is studied for a better understanding of the azimuth velocity estimation error caused by the range velocity. With the proposed error compensation step, the new method can achieve a very high accuracy in azimuth velocity estimation, as verified by experimental results based on both simulated data and the TerraSAR-X data

A High-Order Imaging Algorithm for High-Resolution Space-Borne SAR Based on a Modified Equivalent Squint Range Model

Two challenges have been faced in signal processing of ultrahigh-resolution spaceborne synthetic aperture radar (SAR). The first challenge is constructing a precise range model, and the second one is to develop an efficient imaging algorithm since traditional algorithms fail to process ultrahigh-resolution spaceborne SAR data effectively. In this paper, a novel high-order imaging algorithm for high-resolution spaceborne SAR is presented. First, a modified equivalent squint range model (MESRM) is developed by introducing equivalent radar acceleration into the equivalent squint range model, and it is more suitable for high-resolution spaceborne SAR. The signal model based on the MESRM is also presented. Second, a novel high-order imaging algorithm is derived. The insufficient pulse-repetition frequency problem is solved by an improved subaperture method, and accurate focusing is achieved through an extended hybrid correlation algorithm. Simulations are performed to validate the presented algorithm