Synthetic Aperture Radar Spectra Research Articles

Wave parameters retrieval for dual-polarization C-band synthetic aperture radar using a theoretical-based algorithm under cyclonic conditions

Theoretical-based ocean wave retrieval algorithms are applied by inverting a synthetic aperture radar (SAR) intensity spectrum into a wave spectrum, that has been developed based on a SAR wave mapping mechanism. In our previous studies, it was shown that the wave retrieval algorithm, named the parameterized first-guess spectrum method (PFSM), works for C-band and X-band SAR at low to moderate sea states. In this work, we investigate the performance of the PFSM algorithm when it is applied for dual-polarization c-band sentinel-1 (S-1) SAR acquired in extra wide-swath (EW) and interferometric wide-swath (IW) mode under cyclonic conditions. Strong winds are retrieved from six vertical-horizontal (VH) polarization S-1 SAR images using the c-band cross-polarization coupled-parameters ocean (C-3PO) model and then wave parameters are obtained from the image at the vertical-vertical (VV) polarization channel. significant wave height (SWH) and mean wave period (MWP) are compared with simulations from the WAVEWATCH-III (WW3) model. The validation shows a 0.69 m root mean square error (RMSE) of SWH with a −0.01 m bias and a 0.62 s RMSE of MWP with a −0.17 s bias. Although the PFSM algorithm relies on a good quality SAR spectrum, this study confirms the applicability for wave retrieval from an S-1 SAR image. Moreover, it is found that the retrieved results have less accuracy on the right sector of cyclone eyes where swell directly affects strong wind-sea, while the PFSM algorithm works well on the left and rear sectors of cyclone eyes where the interaction of wind-sea and swell is relatively poor.

Empirical Algorithm for Significant Wave Height Retrieval from Wave Mode Data Provided by the Chinese Satellite Gaofen-3

Gaofen-3 (GF-3), the first Chinese civil C-band synthetic aperture radar (SAR), was successfully launched by the China Academy of Space Technology on 10 August 2016. Among its 12 imaging modes, wave mode is designed to monitor the ocean surface waves over the open ocean. An empirical retrieval algorithm of significant wave height (SWH), termed Quad-Polarized C-band WAVE algorithm for GF-3 wave mode (QPCWAVE_GF3), is developed for quad-polarized SAR measurements from GF-3 in wave mode. QPCWAVE_GF3 model is built using six SAR image and spectrum related parameters. Based on a total of 2576 WaveWatch III (WW3) and GF-3 wave mode match-ups, 12 empirical coefficients of the model are determined for 6 incidence angle modes. The validation of the QPCWAVE_GF3 model is performed through comparisons against independent WW3 modelling hindcasts, and observations from altimeters and buoys from January to October in 2017. The assessment shows a good agreement with root mean square error from 0.5 m to 0.6 m, and scatter index around 20%. In particular, applications of the QPCWAVE_GF3 model in SWH estimation for two storm cases from GF-3 data in wave mode and Quad-Polarization Strip I mode are presented respectively. Results indicate that the proposed algorithm is suitable for SWH estimation from GF-3 wave mode and is promising for other similar data.

Focusing Bistatic FMCW SAR Signal by Range Migration Algorithm Based on Fresnel Approximation.

Frequency modulated continuous wave (FMCW) technique has recently been employed by synthetic aperture radar (SAR) to decrease the radar cost and volume. However, the operation range is limited by the direct energy leakage from the transmitting channel to receiving channel due to the operation principle of FMCW technique. Bistatic configuration is an efficient way to increase the isolation between the transmitter and receiver, which could significantly increase the radar standoff range. A bistatic FMCW SAR spectrum model is proposed by using the Fresnel approximation in this paper. This model is similar to that of a monostatic FMCW SAR spectrum, which allows the existing imaging algorithms to be used on bistatic image processing. Based on the new model and the characteristics of FMCW signal, a modified range migration algorithm (RMA) for FMCW SAR is proposed to focus the image, which requires less memory and computational load than the traditional RMA. Point-target simulation is used to verify the proposed spectral model and real data processing verified the effectiveness of the proposed RMA.

Synergistic measurements of ocean winds and waves from SAR

AbstractIn this study we present a synergistic method to retrieve both ocean surface wave and wind fields from spaceborne quad‐polarization (QP) synthetic aperture radar (SAR) imaging mode data. This algorithm integrates QP‐SAR wind vector retrieval model and the wave retrieval model, with consideration to the nonlinear mapping relationship between ocean wave spectra and SAR image spectra, in order to synergistically retrieve wind fields and wave directional spectra. The method does not require a priori information on the sea state. It combines the observed VV‐polarized SAR image spectra with the retrieved wind vectors from the VH‐polarized SAR image, to estimate the wind‐generated wave directional spectra. The differences between the observed SAR spectra and optimal SAR image spectra associated with the wind waves are interpreted as the contributions from the swell waves. The retrieved ocean wave spectra are used to estimate the integrated spectral wave parameters such as significant wave heights, wavelengths, wave directions and wave periods. The wind and wave parameters retrieved by QP‐SAR are validated against those measured by the National Data Buoy Center (NDBC) directional wave buoys under different sea states. The validation results show that the QP‐SAR SAR has potential to simultaneously measure the ocean surface waves and wind fields from space.

Fuzzy Logic Applied to Track Generation Areas of Swell Systems Observed by SAR

Recently, with the availability of a great number of synthetic aperture radar (SAR) wave mode spectra, it has been possible to derive a set of great circle lines of swell propagation whose intersection points indicate the position of the storm generating the observed swell field. However, due to the inherent limitations of SAR spectra, the locus of convergence of great circle of swell propagation can be sometimes diffuse or contain multiple convergence regions. In this letter, we adapted the fuzzy cluster logic method to identify the regions of convergence of SAR wave field rays. The analysis of the results of the fuzzy algorithm clearly indicates the ability of this statistical method to identify the cluster center region of swell fields observed in SAR wave mode images. The measure of success of the method was how well the generation center of the swell could be traced back to an existing strong storm system.

Retrieval of surface wave parameters from sar images and their validation in the coastal seas around Japan

We have developed a scheme to retrieve surface wave parameters (wave height and wave propagation direction) from European Remote-Sensing Satellite (ERS) Synthetic Aperture Radar (SAR) image mode data in coastal seas around Japanese coastlines. SAR spectra are converted to surface wave spectra of swell-dominated or wind-wave dominated cases. The SAR spectrum and SAR-derived wind speed are used to derive the surface wave spectrum. The wind-wave dominated case and swell-dominated case are differentiated by a wind speed of 6 m/s, and processed in different ways because of their different degree of nonlinearity. It is indicated that the cutoff wavelength for retrieval of the wind-wave dominated spectrum is proportional to the root of significant wave height, which is consistent with the results of previous studies. We generated 66 match-ups using the SAR sub-images and the in-situ surface wave parameters, which were measured by wave gauges installed in near-shore seas. Among them, there are 57 swell-dominated cases, and 9 wind-wave dominated cases. The significant wave heights derived from SAR and from in-situ observation agree with the bias of 0.09 m, the standard deviation of 0.61 m and the correlation coefficient of 0.78. The averaged absolute deviation of wave propagation directions is 18.4°, and the trend of the agreement does not depend on the wave height. These results demonstrate that the SAR surface wave spectrum retrieved by the present system can be used to observe the surface wave field in the coastal seas around Japan.

Modification of SAR spectra associated with surface wind fields in the sea off the Kii Peninsula: A case study

Using surface wave parameters and a high-resolution surface wind field derived from Synthetic Aperture Radar (SAR) image mode data, we have investigated the spatial modification of SAR spectra. We found a surface wind front, formed by sheltering effect of the Kii Mountains, separating high and low wind-speed regions in a sea area of an European Remote-Sensing Satellite (ERS) SAR image off the Kii Peninsula. A swell system propagating westward dominates in the whole sea area covered by the SAR image. The wavelength retrieved from the SAR spectra in the sheltered (non-sheltered) region is longer (shorter). Since the distributions of surface wave parameters and surface wind speed are so well correlated, it can be considered that the SAR spectra are modified differently by the sheltered/non-sheltered surface winds. In order to examine the phenomena observed on the SAR image we have estimated the wind-wave SAR spectrum using the SAR surface winds, a wind-wave spectrum model and a SAR wave imaging model. We assume that the SAR spectrum related to the swell is homogeneous in the area imaged by SAR, and that the SAR spectrum of the wind-wave components causes the observed SAR spectra modification. Differences between the observed SAR spectra and the estimated SAR spectra in the sheltered and non-sheltered regions agree well with each other. In the present case, it can be concluded that the observed SAR spectra can be regarded as a linear combination of the wind-wave SAR spectra and the swell SAR spectra.

Surface Wave Parameters Retrieval in Coastal Seas from Spaceborne SAR Image Mode Data

We have developed a retrieval scheme of surface wave parameters (wave height and wave propagation direction) from ERS Synthetic Aperture Radar (SAR) image mode data in coastal seas around Japan. In this study, we investigated the energy of simulated SAR spectrum at difierent wind speed using nonlinear wave-SAR imaging mechanism, derived the criteria to difierentiate swell from wind waves, and accordingly processed SAR images containing swell and wind waves in difierent way respectively. SAR spectra are converted to surface wave spectra of swell-dominated or wind-wave dominated cases. The SAR spectrum and SAR-derived wind speed are used for the derivation of surface wave spectrum. The wind-wave dominated case and swell- dominated case are difierentiated by the wind speed of 6m/s, and processed in difierent ways because of their difierent nonlinear degree. It is indicated that the cutofi wavelength for retrieval of the wind-wave dominated spectrum is proportional to the root of signiflcant wave height, which is consistent with the results of previous studies. We generated 66 match-ups coupling the SAR sub-images and the in-situ surface wave parameters, which were measured by the wave gauges installed in near-shore seas. Among them, the number of swell-dominated case is 57, and the number of wind-wave dominated case is 9. The SAR-derived and in-situ signiflcant wave heights agree well with the bias of 0.24m, the RMS error 0.92m and the correlation coe-cient of 0.66. The averaged absolute deviation of wave propagation directions is 18:4§, and the agreement tendency does not depend on the wave height. It is proven through the comprehensive validation that the developed SAR surface wave spectrum has high accuracy in the Japanese coastal seas.

Analysis of the SAR imaging process of the ocean surface using Volterra models

The synthetic aperture radar (SAR) process of the ocean surface mapping is studied using a decomposition based on a Volterra model. By a mathematical expansion of the complex exponential of the complete SAR transform, these models decompose the nonlinear distortion mechanisms of the SAR spectrum over different spectra of polynomial interactions. Thus, they offer an alternative modeling (to the exact SAR transform) giving a theoretical separation between the SAR Fourier components linearly derived from the sea surface elevation and the artifacts created by nonlinearities of the SAR mapping of the ocean surface. The paper gives a systematic assessment of such an approximation of the ocean surface SAR imaging process. Higher order statistics (HOS) of the SAR transform and their calculus and implementation are presented. In fact, nonlinearity detection, location (in the Fourier domain) and quantification can only be performed by HOS, reduced to a second-order Volterra model. The Volterra expansion of the SAR imaging process opens new theoretical inversion schemes since under certain conditions on the linear part, Volterra models are easily invertible. Our method is first tested on simulated SAR images in order to validate the HOS tools. We then show results of this nonlinearity analysis performed on images from the ERS-1 satellite and we present cases of nonlinearity detection.

Ocean wave extraction from RADARSAT synthetic aperture radar inter-look image cross-spectra

This study is concerned with the extraction of directional ocean wave spectra from synthetic aperture radar (SAR) image spectra. The statistical estimation problem underlying the wave-SAR inverse problem is examined in detail in order to properly quantify the wave information content of SAR. As a concrete focus, a data set is considered comprising six RADARSAT SAR images co-located with a directional wave buoy off the east coast of Canada. These SAR data are transformed into inter-look image cross-spectra based on two looks at the same ocean scene separated by 0.4 s. The general problem of wave extraction from SAR is cast in terms of a statistical estimation problem that includes the observed SAR spectra, the wave-SAR transform, and prior spectral wave information. The central role of the weighting functions (inverse of the error covariances) is demonstrated, as well as the consequence of approximate (based on the quasilinear wave-SAR transform) versus exact linearizations on the convergence properties of the algorithm. Error estimates are derived and discussed. This statistical framework is applied to the extraction of spectral wave information from observed RADARSAT SAR image cross-spectra. A modified wave-SAR transform is used to account for case-specific geophysical and imaging effects. Analysis of the residual error of simulated and observed SAR spectra motivates a canonical form for the SAR observation error covariance. Wave estimates are then extracted from the SAR spectra, including wavenumber dependent error estimates and explicit identification of spectral null spaces where the SAR contains no wave information. Band-limited SAR wave information is also combined with prior (buoy) spectral wave estimates through parameterization of the wave spectral shape and use of regularization.

A semiparametric algorithm to retrieve ocean wave spectra from synthetic aperture radar

A new wave retrieval method for the ERS synthetic aperture radar(SAR) wave mode is presented. The new algorithm, named semiparametric retrieval algorithm (SPRA), uses the full nonlinear mapping relations as proposed by Hasselmann and Hasselmann [1991]. It differs from previous retrieval algorithms in that it does not require a priori information on the sea state. Instead, it combines the observed SAR spectrum with the collocated wind vector from the ERS scatterometer to make an estimate of the wind sea spectrum. The residual signal in the SAR spectrum is interpreted as swell. The method has been validated by collocating over 5 years of SAR wave mode observations with spectral buoy measurements at 11 locations on the open ocean. For wave components longer than 225 m, the standard deviation between the retrieved spectra and buoy observations is 0.41 m, which corresponds to a relative RMS error of 29%. About 10% of the observed SAR spectra were rejected, in particular in light wind conditions when nonwave features such as those caused by slicks dominated the imagette. The bias and scatter in the results obtained under light wind conditions could be reduced by introducing a wind‐dependent tilt modulation. This wind‐dependent tilt formulation is derived from the empirical CMOD4 relation between the wind vector, the incidence angle, and the radar backscatter for the ERS scatterometer.

Directional spectrum analysis and statistics obtained from ERS-1 SAR wave images

This work examines ERS-1 (the first European Remote Sensing Satellite) SAR (Synthetic Aperture Radar) water surface wave images over Hualien of Taiwan, indicating that the variation of SAR signals in space domain is similar to in situ wave data's in time domain. Some statistical properties of SAR data are investigated. The Rayleigh distribution function closely corresponds with the histogram of wave heights, but the Gaussian one cannot for water surface displacements. Evidence reveals that SAR wave signals do not respond well to actual ocean waves effectively. As wave spectral analysis of available SAR data reveals, the appropriate sample size of SAR wave image, sampling average, and moving average should be taken carefully to accurately confirm directional power spectra. Moreover, SAR spectra are compared with in situ ones, confirming that peak frequencies correlate well and wave directions approximately agree with each other. Some differences between both spectral shapes remain somewhat unclear and require further study. Nevertheless, in this study, ERS-1 SAR power spectra verified the feasibility of deriving an appropriate dominant wave direction and peak frequency.

Dominant wave directions and significant wave heights from synthetic aperture radar imagery of the ocean

We show that quasi‐linear theory accounts for dominant wave directions observed in synthetic aperture radar (SAR) imagery of the ocean for range‐to‐velocity (R/V) ratios up to 70 s. We also show that when used in combination with Alpers and Hasselmann's [1982] model of signal‐to‐noise ratios in SAR imagery, this theory yields significant wave heights in good agreement with those actually observed. We have found that the apparent dominant wave direction in SAR imagery taken at a 45° incidence angle can differ from the true wave direction by as much as 40° under certain conditions. To understand such differences, we simulated SAR image spectra using quasi‐linear theory, a surface wave spectrum measured by a buoy but with a variable angular spread, coherence times calculated from line‐of‐sight velocity spreads, and modulation transfer functions based on a functional form developed from Bragg scattering theory and data obtained during the SAR X Band Ocean Nonlinearities‐Forschungsplatform Nordsee (SAXON‐FPN) experiment. We carried out these simulations for a 45° incidence angle, L, C, and X bands, both horizontal/horizontal (HH) and vertical/vertical (VV) polarization, three different flight altitudes, and a variety of flight directions to compare the predicted apparent wave directions with those observed in the SAR imagery collected during SAXON‐FPN. The difference between the SAR‐derived dominant wave direction and the one measured by the buoy could be predicted well as a function of the true wave direction relative to the flight direction. The parameters of the quasi‐linear theory that produced the best fit to the directional data differed somewhat from those measured by tower‐based radars during SAXON‐FPN, however. Significant wave heights obtained using the parameters that best fit the directional data were in good agreement with those measured by the buoy. The SAR‐derived wave heights were consistently higher than the measured ones, however, unless the full system bandwidth was used in determining the clutter level, that is, unless bandwidth reductions due to azimuthal presumming and multilook averaging were removed. Finally, the prediction and observation of spectral splitting in SAR spectra of azimuthally traveling waves are also reported.

An improved algorithm for the retrieval of ocean wave spectra from synthetic aperture radar image spectra

An earlier algorithm for retrieving two‐dimensional wave spectra from synthetic aperture radar (SAR) image spectra is improved by using a modified cost function and introducing an additional iteration loop in which the first‐guess input spectrum is systematically updated. For this purpose a spectral partitioning scheme is applied in which the spectrum is decomposed into a finite number of distinct wave systems. At each iteration step, the individual wave systems of the partitioned nth‐guess wave spectrum are adjusted to agree in mean energy, frequency, and direction with the corresponding mean values of the associated wave systems of the SAR‐inverted wave spectrum. The algorithm retrieves smooth wave spectra, avoiding the discontinuities which tended to arise in the previous algorithm in the transition region near the azimuthal wavenumber cutoff of the SAR image spectrum. The azimuthal cutoff of the SAR spectrum is also reproduced more accurately. The greatest improvement of the new retrieval algorithm is obtained when the discrepancies between the initial first‐guess wave spectrum and the observed SAR spectrum are large. In this case the additional updating loop for the input spectrum enables the retrieved spectrum to adjust such that the simulated SAR spectrum matches more closely the observed SAR spectrum. The overall correlation of a large set of simulated SAR spectra with the measured SAR spectra is found to be significantly higher than with the previous algorithm, indicating that the algorithm not only overcomes isolated shortcomings of the earlier algorithm but also yields retrieved wave spectra which are generally more consistent with the input SAR data. An additional practical advantage of the new algorithm is that it returns spectral partioning parameters which can be used in SAR wave data assimilation schemes.

Ocean‐ice interaction in the marginal ice zone using synthetic aperture radar imagery

Ocean‐ice interaction processes in the marginal ice zone (MIZ) by wind, waves, and mesoscale features, such as up/downwelling and eddies are studied using ERS 1 synthetic aperture radar (SAR) images and an ocean‐ice interaction model. A sequence of seven SAR images of the MIZ in the Chukchi Sea with 3 or 6 days interval are investigated for ice edge advance/retreat. Simultaneous current measurements from the northeast Chukchi Sea, as well as the Barrow wind record, are used to interpret the MIZ dynamics. SAR spectra of waves in ice and ocean waves in the Bering and Chukchi Sea are compared for the study of wave propagation and dominant SAR imaging mechanism. By using the SAR‐observed ice edge configuration and wind and wave field in the Chukchi Sea as inputs, a numerical simulation has been performed with the ocean‐ice interaction model. After 3 days of wind and wave forcing the resulting ice edge configuration, eddy formation, and flow velocity field are shown to be consistent with SAR observations.

Airborne and spaceborne synthetic aperture radar observations of ocean waves

Abstract The Grand Banks ERS‐1 synthetic aperture radar (SAR) wave spectra validation experiment took place over a study site in which intensive in situ wind and wave measurements were being taken. The unique aspect of the program was the nearly simultaneous acquisition (in space and time) of spaceborne (ESA ERS‐1) and airborne (CCRS CV‐580) SAR imagery of the same ocean wave field. Although both SARs were operating at C‐band with W polarization, the geometry of acquisition was quite different. For example, the range‐to‐velocity ratio parameter was large for ERS‐1 (R/V ∼ 115 s) and relatively small for the CV‐580 (R/V < 50 s). Thus, the SAR image spectra derived from ERS‐1 are significantly more susceptible to velocity bunching non‐linearity and azimuth spectral cut‐off, which are well‐known limitations of SAR in accurately measuring azimuth‐travelling ocean waves. Airborne and spaceborne SAR measurements of ocean waves are presented and compared with directional wave buoy measurements. A technique is developed to estimate the azimuth spectral width based upon a quasi‐linear ocean‐to‐SAR transform, and is applied to all of the SAR spectra. This quasi‐linear transform is qualitatively assessed by forward‐mapping directional wave buoy spectra into SAR image spectra. The width measurements are correlated with observed values for the significant wave height or the azimuth shift and the local wind speed. This allows definition of a quasi‐linear transform that includes both velocity bunching decorrelation effects and wind speed‐dependent coherence time effects. Finally, a new SAR spectral inversion scheme, based upon the quasi‐linear transform, is demonstrated. Wave model spectra are used as the starting point and validation is against directional wave buoy spectra.

Comparison of aircraft synthetic aperture radar and buoy spectra during the Norwegian Continental Shelf Experiment of 1988

Aircraft synthetic aperture radar (SAR) measurements from seven flight paths at two different altitudes were acquired over a trimodal ocean wave system off the coast of Norway on March 11, 1988. These three wave systems traveling in different directions were also measured by a directional buoy with the buoy spectra rotated into the radar coordinates for comparison with SAR spectra. Fifteen subspectra were averaged to obtain the measured SAR spectra, and sixteen spectral bands were averaged to obtain the measured buoy spectra. The seven flight paths in conjunction with the three wave systems resulted in a nearly uniform distribution of azimuth peak directions varying from 0° to 83° and R/V varying from 28 to 110. The comparison of the SAR‐ and buoy‐derived peak wavelength and direction shows some scatter. We consider the scatter to be due primarily to the statistical uncertainty in the spectral estimates, the wave number resolution, and differences in the temporal and spatial averaging. Scanning distortion is shown to cause significant bias in the SAR and buoy comparison for slow‐flying aircraft imaging ocean wave swell. Correction of the SAR spectra for this special radar‐ocean condition gives significant improvement in the SAR‐buoy comparison. We investigate the relative importance of the motion‐related mechanisms (velocity bunching, velocity smearing, and scanning distortion), and the tilt contributions using four nondimensional imaging parameters.

Aircraft synthetic aperture radar and buoy ocean wave measurements off the coast of Norway

Abstract Aircraft synthetic aperture radar (SAR) measurements from seven flight paths at two different altitudes were acquired over a tri-modal ocean wave system off the coast of Norway on 11 March 1988. These three-wave systems travelling in different directions were also measured by a directional buoy with the buoy spectra rotated into the radar coordinates for comparison with SAR spectra. Fifteen subspectra were averaged to obtain the measured SAR spectra and sixteen spectral bands were averaged to obtain the measured buoy spectra. The seven flight paths in conjunction with the three wave systems resulted in a nearly uniform distribution, of azimuth peak directions varying from 0° to 83° and R/Vvarying from 28 to 110 s. The SAR spectra derived and buoy peak wavelength and direction comparison show the expected variation, however some scatter and bias are present. The r.m.s. scatter was about 10 per cent or less for the peak wavelength and 10° or less for the peak direction. We consider the scatter as p...

Estimating aircraft SAR response characteristics and ocean wave spectra in the Labrador Sea Extreme waves Experiment

The Labrador Extreme Waves Experiment (LEWEX) was an international effort to assess methods of measuring and modeling the directional aspects of wind-generated ocean waves, especially their evolution in the presence of rapidly turning winds. The author describes data-processing methods that have been developed to derive estimates of two-dimensional wave height-variance spectra from the ocean imagery obtained in LEWEX by a C-band synthetic aperture radar (SAR) system aboard a Canadian CV-580 aircraft. SAR spectra at altitudes of 20000 and 12000 ft are compared for both large ( approximately 50 degrees ) and small ( approximately 25 degrees ) radar look angles. Independence spectral estimates from both a surface contour radar and a radar ocean wave spectrometer aboard a NASA aircraft are used to verify the surface wave spectrum.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Ocean-wave imaging by synthetic-aperture radar: results from the SIR-B experiment in the N.E. Atlantic

Waveheight spectra were extracted from synthetic-aperture radar (SAR) images close to a number of wave-measuring buoys, and the results of radar and in situ measurements were compared as a test of wave-imaging theory. SAR and buoy spectra of waves traveling close to the radar range direction were in good quantitative agreement, with any discrepancies probably attributable to the processing technique. However, SAR estimates of the amplitude of azimuth-traveling waves were very much lower than buoy-derived values. This cannot be accounted for by appealing to nonlinear imaging by the velocity-bunching mechanism, or by velocity smearing, calculating the scene coherence time from the available buoy data. Rather, the scene coherent time must be reduced by a factor of about two, to within the range 0.022-0.027 s. This result highlights a lack of knowledge of scatterer motions and lifetimes on the sea surface.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>