Current Measurements in Rivers by Spaceborne Along-Track InSAR

Romeiser, Roland; Runge, Hartmut; Suchandt, Steffen; Sprenger, Johanna; Weilbeer, Holger; Sohrmann, A.; Stammer, Detlef

doi:10.1109/tgrs.2007.904837

Cited by 58 publications

(40 citation statements)

References 23 publications

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“…D (x) and umaxv(x) are the water depth and the maximum velocity sampled along the vertical [10], respectively. Parameter hu is the depth below the water surface where umax occurs (hu = 0 if umax occurs at the surface).…”

Section: Entropy Methodsmentioning

confidence: 99%

“…InSAR techniques allow sensing river surface velocity in the direction orthogonal to the sensor track, called radial velocity. This feature was already tested on the tidal extent of the Elbe river using TerraSAR-X satellite [10,11] with an average accuracy of 0.1 m/s while the hydrological community is waiting for the data of the current airborne mission AirSWOT [12]. This mission will test, calibrate and validate the instrument of the next satellite mission SWOT.…”

Section: Introductionmentioning

confidence: 99%

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Conventional Point-Velocity Records and Surface Velocity Observations for Estimating High Flow Discharge

Corato¹,

Ammari

Moramarco

2014

Entropy

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Flow velocity measurements using point-velocity meters are normally obtained by sampling one, two or three velocity points per vertical profile. During high floods their use is inhibited due to the difficulty of sampling in lower portions of the flow area. Nevertheless, the application of standard methods allows estimation of a parameter, α, which depends on the energy slope and the Manning roughness coefficient. During high floods, monitoring of velocity can be accomplished by sampling the maximum velocity, umax, only, which can be used to estimate the mean flow velocity, um, by applying the linear entropy relationship depending on the parameter, M, estimated on the basis of historical observed pairs (um, umax). In this context, this work attempts to analyze if a correlation between α and M holds, so that the monitoring for high flows can be addressed by exploiting information from standard methods. A methodology is proposed to estimate M from α, by coupling the "historical" information derived by standard methods, and "new" information from the measurement of umax surmised at later times. Results from four gauged river sites of different hydraulic and geometric characteristics have shown the robust estimation of M based on α.

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Section: Entropy Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Conventional Point-Velocity Records and Surface Velocity Observations for Estimating High Flow Discharge

Corato¹,

Ammari

Moramarco

2014

Entropy

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“…Since then, the feasibility of current measurements by this technique has been demonstrated in a number of further experiments, using interferometric SAR (InSAR) systems on aircraft (e.g. [2][3][4][5]), on a space shuttle [6,7], and on the first ATI-capable satellite, the German TerraSAR-X [8]. Furthermore, some theoretical studies have been performed to understand the ATI imaging mechanism of current and wave fields and to find out how the ATI data quality depends on radar frequency, incidence angle, alongtrack (AT) baseline, etc., and what parameter combinations are most promising for accurate highresolution current measurements (e.g.…”

Section: Introductionmentioning

confidence: 99%

“…Unfortunately, the Shuttle Radar Topography Mission setup (used in [6,7]) and the divided-antenna modes of TerraSAR-X (explained in [10][11][12] and used in [8]) have offered effective AT baselines of only 3.5 m and approx. 1 m, respectively, resulting in a clearly suboptimal sensitivity to target velocities and the requirement to average the interferograms over thousands of full-resolution pixels to reduce phase noise.…”

Section: Introductionmentioning

confidence: 99%

Quality Assessment of Surface Current Fields From TerraSAR-X and TanDEM-X Along-Track Interferometry and Doppler Centroid Analysis

Romeiser

Runge

Suchandt

et al. 2014

IEEE Trans. Geosci. Remote Sensing

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All existing examples of current measurements by spaceborne synthetic aperture radar (SAR) along-track interferometry (ATI) have suffered from short baselines and corresponding low sensitivities. Theoretically, the best data quality at X band is expected at effective baselines on the order of 30 m, i.e. 30 times as long as the baselines of the divided-antenna modes of TerraSAR-X. In early 2012, we had a first opportunity to obtain data at near-optimum baselines from the TanDEM-X satellite formation. In this paper we analyze two TanDEM good agreement in all three cases. The DCA-based currents are found to be less accurate than the ATIbased ones, but close to short-baseline ATI results in quality. We conclude that DCA is a considerable alternative to divided-antenna mode ATI, while our TanDEM-X results demonstrate the true potential of the ATI technique at near-optimum baselines.

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“…The ATI SAR was initially proposed for detecting ground moving targets [8][9][10], which uses two antennas to detect targets by providing essentially two identical views of the illuminated scene but at slightly different time. Several interferometry SAR (InSAR)-based moving targets detection algorithms have been proposed previously [11][12][13][14]. However, the stationary clutter unavoidably corrupts the interferometric phase of the targets depending on its signal-to-clutter environment.…”

Section: Introductionmentioning

confidence: 99%

Moving Target Indication via Three-Antenna SAR with Simplified Fractional Fourier Transform

Wang

2011

EURASIP J. Adv. Signal Process.

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Ground moving target indiction (GMTI) is of great important for surveillance and reconnaissance, but it is not an easy job. One technique is the along-track interferometry (ATI) synthetic aperture radar (SAR), which was initially proposed for estimating the radial velocity of ground moving targets. However, the measured differential phase may be contaminated by overlapping stationary clutter, leading to errors in velocity and position estimates. As effective clutter suppression can be achieved by multiple aperture or phase center antennas, this article presents a simplified fractional Fourier transform (SFrFT) for three-antenna-based SAR GMTI applications. This approach cancels clutter with three-antenna-based methods and forms two-channel signals through which moving targets are detected and imaged. Next, the Doppler parameters of the moving targets are estimated with the SFrFT-based estimation algorithm. In this way, both target location and target velocity are acquired. Next, the moving targets are focused with one uniform imaging algorithm. The feasibility is validated by theory analysis and simulation results.

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Current Measurements in Rivers by Spaceborne Along-Track InSAR

Cited by 58 publications

References 23 publications

Conventional Point-Velocity Records and Surface Velocity Observations for Estimating High Flow Discharge

Conventional Point-Velocity Records and Surface Velocity Observations for Estimating High Flow Discharge

Quality Assessment of Surface Current Fields From TerraSAR-X and TanDEM-X Along-Track Interferometry and Doppler Centroid Analysis

Moving Target Indication via Three-Antenna SAR with Simplified Fractional Fourier Transform

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