Detection and analysis of oceanic internal waves by JERS-1 SAR
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The paper discusses K. Hasselmann's closed form nonlinear transform for the velocity bunching and applies the transform to data from the NORCSEX experiment carried out in 1988. It is concluded that the transform captures most features of observed SAR spectra and provides a significant step towards a complete theory for SAR observations of directional ocean wave fields.
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Simulation of polarization synthetic aperture radar(SAR) imaging of sea wave has great significance on sea surface scattering.According to the theory of random ocean wave,rough ocean surface is modeled in this paper.Random rough ocean surface which contains swell is constructed using the two-scale-model.This treatment takes both the large scale and small scale surface into account.By using the Bragg scattering model and the geometry optical approximation method,polarization SAR images of the modeled ocean surface at different wind speeds are simulated.The effects of the parameters of ocean waves and the parameters of SAR system are analyzed.Finally,some useful conclusions are drawn,which are helpful for extracting the information of ocean surface.
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Rough surface
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Abstract. With the advent of the new generation of synthetic aperture radar (SAR) satellites, it has become possible to resolve fine-scale features on the sea surface on the scale of meters. The proper identification of sea surface signatures in SAR imagery can be challenging, since some features may be due to atmospheric distortions (gravity waves, squall lines) or anthropogenic influences (slicks), and may not be related to dynamic processes in the upper ocean. In order to improve our understanding of the nature of fine-scale features on the sea surface and their signature in SAR, we have conducted high-resolution numerical simulations combining a three-dimensional non-hydrostatic computational fluid dynamics model with a radar imaging model. The surface velocity field from the hydrodynamic model is used as input to the radar imaging model. The combined approach reproduces the sea surface signatures in SAR of ship wakes, low-density plumes, and internal waves in a stratified environment. The numerical results are consistent with observations reported in a companion paper on in situ measurements during SAR satellite overpasses. Ocean surface and internal waves are also known to produce a measurable signal in the ocean magnetic field. This paper explores the use of computational fluid dynamics to investigate the magnetic signatures of oceanic processes. This potentially provides a link between SAR signatures of transient ocean dynamics and magnetic field fluctuations in the ocean. We suggest that combining SAR imagery with data from ocean magnetometers may be useful as an additional maritime sensing method. The new approach presented in this work can be extended to other dynamic processes in the upper ocean, including fronts and eddies, and can be a valuable tool for the interpretation of SAR images of the ocean surface.
Racing slick
Ocean surface topography
Ocean dynamics
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The major goals of the variable SARs were applications in ocean wave research and wave forecasting. Two-dimensional ocean wave spectra can be derived from SIR-C/X-SAR images by inversion of the SAR imaging mechanism. But for a composite sea surface, i.e., there exist local wind-generated waves, long wave (or swell) from far fetch, internal waves and/or wave breakers, to separate very certain wave information or wave spectrum is difficult in practice. Inversion of a 2D spectrum of internal wave surface of South-China Sea is computed from SIR-C/X-SAR image data. A new inversion method is presented which estimates two dimensional wave spectra. The scheme uses prior information from ocean wave models to add missing information and to account for the fact that the SAR ocean wave imaging mechanism model is not a one to one imaging process. The scheme takes the shape of different ocean wave components as information and uses the SAR information to adjust the mean wavelengths, propagation directions and waveheights of the prior spectrum. The scheme is based on stochastic models for both the measurement error and the prior distribution. The method can separate internal wave from wind-generated waves efficiently.
Wind wave model
Swell
Fetch
Wave shoaling
Significant wave height
Wave radar
Electromagnetic spectrum
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Numerical models
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Aim To study the SAR imaging of ocean surface wave and the surface wave modulation of radar cross section. Methods Simulation is done by using velocity bunching model,for various SAR parameters and ocean states. Results Because of the wave orbital velocity, the process of imaging ocean surface by SAR becomes nonlinear. The SAR image has a shift and becomes smeared in azimuthal direction. Conclusions This simulation method is an effective way in the study of ocean surface wave imaging by SAR.
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Research over the past several years has produced a number of different mathematical models which all claim to explain the physical mechanism by which ocean waves are imaged by synthetic aperture radar (SAR). Identifying the correct and incorrect features in these models is important in two ways: first as basic research which leads to quantitative understanding of meteorological and oceanographic features in SAR images and second as a step in making, otherwise unobtainable, synoptic scale ocean wave measurements. Key issues connected with the differences between these models are the role of surface motion, degradation of SAR resolution by surface motion, relative importance of quasi-specular, Bragg-resonance and other scattering mechanisms and validity of two-scale models. Experimental results taken from SEASAT SAR images and buoy measurements of ocean waves are compared with hypotheses drawn from the three models. We conclude that for large scale, low amplitude surface waves, wave phase velocity is not a dominant factor in the SAR imaging process. Further, quasi-specular scattering can be important for SEASAT SAR imaging of ocean waves.
Buoy
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We have developed SAR image simulation in time domain for observations of moving sea surface. The simulation aims to obtain SAR images of ocean waves and ocean winds with regard to velocity bunching and Bragg scattering. In order to discuss whether the simulation is based on Bragg scattering, incident angle dependence is simulated from wind waves in the range direction. The simulated SAR signals are good agreement with features of Bragg scattering. Furthermore, velocity bunching modulation due to orbital motions of ocean waves is confirmed in the case of ocean waves with different wave directions. The simulated SAR images show that nonlinearity is strong when ocean waves are travelling to the azimuth direction. It is consistent to the theory of velocity bunching. These simulation results turn out that the time domain simulation can be applied for generating numerical SAR images of ocean waves and ocean winds.
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A theory of internal wave synthetic aperture radar (SAR) imaging has been improved by applying Korteweg-de Vries (KdV) equation, Bragg back scatter model, and replacing surface wave action equation with high frequency ocean wave spectrum balance equation. An analytical expression for an ocean internal wave SAR image will be obtained. Based on the new theory, the effects of wind on internal waves SAR images are studied with theoretical and scale analysis. The results indicate that the effects of wind are comparable with the hydrodynamic parameters, and the signature of internal waves can be imaged on the SAR only when oceanic state is low. The results agree well with some observations.
Wave radar
Aperture (computer memory)
Sea state
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