Wave Synthetic Aperture Radar Imaging Research Articles

A Texture Enhancement Method for Oceanic Internal Wave Synthetic Aperture Radar Images Based on Non-Local Mean Filtering and Texture Layer Enhancement

Synthetic aperture radar (SAR) is an important tool for observing the oceanic internal wave phenomenon. However, owing to the unstable imaging quality of SAR on oceanic internal waves, the texture details of internal wave images are usually unclear, which is not conducive to the subsequent applications of the images. To cope with this problem, a texture enhancement method for oceanic internal wave SAR images is proposed in this paper, which is based on non-local mean (NLM) filtering and texture layer enhancement (TLE). Since the strong speckle noise commonly present in internal wave images is simultaneously enhanced during texture enhancement, resulting in degraded image quality, NLM filtering is first performed to suppress speckle noise. Then, the denoised image is decomposed into the structure layer and the texture layer, and a texture layer enhancement method oriented to the texture characteristics of oceanic internal waves is proposed and applied. Finally, the enhanced texture layer and the structure layer are combined to reconstruct the final enhanced image. Experiments are conducted based on the Gaofen-3 real SAR data, and the results demonstrate that the proposed method performs well in suppressing speckle noise, maintaining overall image brightness, and enhancing internal wave texture details.

Stripe segmentation of oceanic internal waves in SAR images based on Gabor transform and K-means clustering

Oceanic internal waves are an active ocean phenomenon that can be observed, and their relevant characteristics can be acquired using synthetic aperture radar (SAR). The locations of oceanic internal waves must be determined first to obtain the important parameters of oceanic internal waves from SAR images. An oceanic internal wave segmentation method with integrated light and dark stripes was described in this study. To extract the SAR image characteristics of oceanic internal waves, the Gabor transform was initially used, and then the K-means clustering algorithm was used to separate the light (dark) stripes of oceanic internal waves from the background in the SAR images. The regions of the dark (light) stripes were automatically determined based on the differences between the three classes, that is, the dark stripes, light stripes, and background area. Finally, the locations of the dark (light) stripes were determined by shifting a given distance along the normal direction of the long side with the minimum bounding rectangle of the light (dark) stripes. The best segmentation results were obtained based on the intersection over the union of the images, and the accuracy of segmentation was verified. Furthermore, the effectiveness and practicability of the proposed method in the light and dark stripe segmentation of SAR images of oceanic internal waves were illustrated. The proposed method prepares the foundation for future inversion studies of oceanic internal waves.

A Study on Millimeter Wave SAR Imaging for Non-Destructive Testing of Rebar in Reinforced Concrete.

In this study, we investigate a millimeter wave (mmWave) synthetic aperture radar (SAR) imaging scheme utilizing a low-cost frequency modulated continuous wave (FMCW) radar to take part in non-destructive testing which could be a useful tool for both civilian and military demands. The FMCW radar working in the frequency range from 76 GHz to 81 GHz is equipped with a 2-D moving platform aiming to reconstruct the 2-D image of the shape of the target object. Due to the lab environment containing several devices and furniture, various noise and interference signals from the floor are not avoidable. Therefore, the digital signal processing algorithms are joined to remove the undesired signals as well as improve the target recognition. This study adopts the range migration algorithms (RMAs) on the processed reflected signal data to form the image of the target because of its verified ability in this type of mission. On the other hand, the integration of compressed sensing (CS) algorithms into the SAR imaging system is also researched which helps to improve the performance of the system by reducing the measurement duration while still maintaining the image quality. Three minimization algorithms are used involving the imaging system as the CS solvers reconstruct the radar data before being processed by RMA to form the image. The proposed imaging scheme demonstrates its good ability with high azimuth resolution in the mission of detecting tiny cracks in the rebar of reinforced concrete. In addition, the participation of CS algorithms improves the performance of the scheme as the cracks on the rebar can be located on the images, which are reconstructed from only 30% of the dataset. The comparison of CS solvers shows that ADMM outperforms the other candidates in the reconstruction task.

SAR Imaging Algorithm of Ocean Waves Based on Optimum Subaperture.

Synthetic Aperture Radar (SAR) is widely applied to the field of ocean remote sensing. Clear SAR images are the basis for ocean information acquisitions, such as parameter retrieval of ocean waves and wind field inversion of the ocean surface. However, the SAR ocean images are usually blurred, which seriously affects the acquisition of ocean information. The reasons for the wave blurring in SAR images mainly include the following two aspects. One is that when SAR observes the ocean, the motion of ocean waves will have a greater impact on imaging quality. The other is that the ocean’s surface is seriously decorrelated within the integration time. In order to obtain clear SAR images of ocean waves, a SAR imaging algorithm of ocean waves based on the optimum subaperture is proposed, aiming at the above two aspects. The optimum focus setting of the ocean waves is calculated, drawing support from the azimuth phase velocity of the dominant wave. The optimum subaperture is further calculated according to the proposed new evaluation, namely, F. Finally, according to the optimum focus setting and the optimum subaperture, the dominant wave is refocused, and a clear SAR image of the dominant wave can be obtained. The proposed algorithm was applied to airborne L-band and P-band SAR data. Furthermore, the proposed algorithm was compared with present methods, and the results sufficiently demonstrated the effectiveness and superiority of the proposed algorithm.

Numerical Simulation of SAR Image for Sea Surface

Based on the simulated signal, a numerical simulation method of synthetic aperture radar (SAR) imaging for time-varying sea surfaces is proposed, which is helpful to study the SAR imaging mechanism of time-varying sea surfaces so as to better extract ocean wave parameters from SAR images. Not only are the modulation of ocean waves, speckle noise, and temporal decorrelation of the small-scale waves considered, but the velocity bunching (VB) effect caused by the motion of large-scale waves is also effectively added to the simulation of the SAR echo signal. To verify the reliability of the simulation method, the simulated SAR images using the parameters of the RADARSAT-2 SAR, the corresponding wind wave information measured by an in-situ buoy, and the reanalysis wave spectra have been compared with the actual RADARSAT-2 SAR images. The comparisons demonstrate that the characteristics of simulated SAR images, such as the intensity distribution and the image spectra, are consistent with those of actual RADARSAT-2 SAR images. Based on the numerical simulation method proposed by us, SAR images of ocean waves for different marine environments and radar platform parameters are simulated. The imaging results indicate that the texture feature of the wind waves would be severely damaged due to the VB effect, while the texture of swells in the simulated SAR images may not be damaged or even becomes clearer. From the simulated SAR image spectrum, it can be found that the azimuth wavenumber is cut off when the VB effect is considered in the simulation process, and the azimuth cut-off wavelength increases with the range-to-velocity ratio.

Spaceborne Interrupted Frequency Modulation Continuous Wave SAR Imaging Based on Accumulated Aperture Interpolation Technique

The Intermittent Frequency Modulation Continuous Wave (IFMCW) Synthetic Aperture Radar (SAR) mode solves the problem that the spaceborne Frequency Modulation Continuous Wave (FMCW) SAR must be bistatic by alternately transmitting and receiving signals in different time intervals. However, in this mode, the radar antenna will work intermittently in the transmitting and receiving state, resulting in periodical gaps in the echo data. In order to solve the above problems, a Missing-data Iterative Adaptive imaging processing Approach (MIAA) is proposed, based on Accumulated Aperture Interpolation Technique (AAIT) to recover the data gaps. Experimental results show that the proposed method can effectively recover missing data, thus significantly improving imaging quality and greatly suppressing the artifacts energy caused by the periodical data gaps.

Comparison Between Back Projection Algorithm and Range Migration Algorithm in Terahertz Imaging

Back projection algorithm (BPA) and range migration algorithm (RMA) are two common approaches for image reconstruction in synthetic aperture radar (SAR) imaging. Imaging is implemented in spatial domain and spatial frequency domain, respectively and these two methods are often considered to generate the same results. This is true in normal microwave/millimeter wave SAR imaging systems, since the object of interests is located far away and the applied wavelength is long. In this case, the location of the object is the most important issue and there is no impetus to image the object with very fine details. In case of terahertz (THz) imaging, we have found some differences by using the two algorithms above, including the position of the object and resolution in 2D and 3D imaging. Some insights are given and we believe there should be some guidelines regarding the pros and cons before choosing the exact algorithm, especially when high-performance imaging is pursued.

Air‐borne linear frequency modulation range interrupted continuous‐wave SAR for high‐resolution imaging

To avoid two apertures adopted in air-borne continuous-wave (CW) synthetic aperture radar (SAR) systems, the novel air-borne linear frequency modulation range interrupted continuous wave (LFMRICW) SAR imaging mode is presented here. Different from the conventional air-borne CW imaging mode, it only requires one antenna to transmit radar pulses and receive its echoes. The system design of this mode is given in detail, and its imaging processor based on a linear prediction model (LPM) is proposed according to echo characteristics. Simulation results on distributed targets validate the presented new air-borne imaging scheme and its corresponding imaging processor.

Estimation of Significant Wave Height of Near-Range Traveling Ocean Waves Using Sentinel-1 SAR Images

Synthetic aperture radar (SAR) is a valuable tool to observe many oceanographic parameters of the ocean surface. The significant wave height (H s or SWH), defined as the mean wave height of the highest one-third of waves, can be estimated using indirect relations between SAR-derived and the actual ocean wave spectra. However, multilook SAR imaging of ocean surface waves is highly affected by degraded azimuthal resolution and the random shift of scattered elements as the waves propagate off the SAR range direction. Therefore, the azimuthal displacement is found to be very low when near-range travelling ocean waves with narrow band spectrum are imaged. In this study, an improved algorithm is developed to directly estimate the significant wave height of ocean waves that propagate in the near-range direction using SARSAR imagery. The slope of the NRCS with respect to the radar wave incidence angle is derived from SAR images using an iterative scheme. A total of 69 SAR images from Sentinel-1A and 1B from 2016 to 2017, acquired near Hawaii, and in situ wave data from nearby National Data Buoy Center buoys are used to estimate H s and validate the improved algorithm. Results show that the algorithm performs well in estimating SWH under low to moderate wind forcing conditions (4-10 ms -1 ). The accuracy of the SWH estimation decreases under high-wind-speed and wind-wave-dominant conditions.

Extended wavenumber domain algorithm for equivalent squinted linear frequency modulated continuous wave SAR imaging

Ability to acquire high-resolution, phase-preserved images is an important requirement in modern synthetic aperture radar (SAR) applications. Wavenumber domain algorithms are good choices to achieve this objective without approximation in the wavenumber reversal process. However, when squint angle gets larger, even wavenumber domain algorithms suffer from resolution and computational efficiency degradations. In order to accommodate wavenumber domain algorithms to highly squinted SAR imaging by exploiting squint minimization and two-dimensional interpolation schemes, the proposed extended wavenumber domain algorithm possesses the advantages of maximum spectrum utilization, processing efficiency, and good interpretation of the two-dimensional interpolation. It can also be easily incorporated with motion compensation without complicating the motion analysis. Simulations and real data experiments validate our proposed algorithm.

Airborne SAR Imaging Algorithm for Ocean Waves Based on Optimum Focus Setting

Ocean waves are the richest texture on the sea surface, from which valuable information can be inversed. In general, the Synthetic Aperture Radar (SAR) images of surface waves will inevitably be distorted due to the intricate motion of surface waves. However, commonly used imaging algorithms do not take the motion of surface waves into consideration. Therefore, surface waves on the obtained SAR images are rather blurred. To solve this problem, an airborne SAR imaging algorithm for ocean waves based on optimum focus setting is proposed in this paper. Firstly, in order to obtain the real azimuth phase speed of dominant wave, the geometric and scanning distortion in the blurred SAR image is calibrated. Subsequently, according to the SAR integration time and wavelength of the dominant wave, a proper focus setting variation section is selected. Afterwards, all the focus settings in this variation section are used to refocus the image, which are then compared to decide the optimum focus setting for dominant wave. Finally, by redesigning the azimuth matched filter using this optimum focus setting, a well-focused SAR image for the dominant wave can be obtained. The proposed algorithm is applied to both simulation and field data, and SAR images of surface waves are obtained. Furthermore, the obtained images are compared with those obtained with a zero-focus setting. The comparison shows that the focus of surface waves is significantly improved, which verifies the effectiveness of the proposed algorithm. Finally, how to choose the appropriate focus setting variation section under different parameters and the applicability of the algorithm are analyzed.

APPLICATION OF FACET SCATTERING MODEL IN SAR IMAGING OF SEA SURFACE WAVES WITH KELVIN WAKE

The principal purpose of this work is the simulation of the ship wake in Synthetic Aperture Radar (SAR) imaging based on a facet scattering model. The hydrodynamic model of the surface waves mainly considers the Kelvin wake waves and the wind driven waves. For the prediction of radar returns from the composite surface, the semi-deterministic facet scattering model (SDFSM) is proposed, which is verified to have good performance through a comparison with the experiment by SASS-II. Then, the distributions of backscattering normalized radar cross section (NRCS) of facets are investigated for both VV and HH polarizations and characteristics of the wake pattern are shown with good visibility. On the basis of these, an application of velocity bunching (VB) imaging model is presented in detail for the simulation of SAR imaging of sea surface waves with Kelvin wake. Finally, several numerical results provide states of the effects of ship speed, wind speed and the ship sailing direction on the characteristics of Kelvin wake in SAR images. Thus, this simulation may enable us to provide a theoretical basis to the detection of ship wakes.

Study on the improvements for the high‐resolution frequency modulated continuous wave synthetic aperture radar imaging

This study develops two aspects of improvement, performing the range-dependent secondary range compression (SRC) and correcting the motion errors within the sweep of the transmitted signal, for the high-resolution frequency modulated continuous wave synthetic aperture radar (FMCW SAR). In cases of more complex imaging scenarios such as higher squint angle and larger range swath, the range dependence of SRC should be considered to avoid severe degradation. Moreover, when the trajectory deviations are severe, the motion error within the sweep causes new noticeable residual range cell migration, which should be considered for the motion compensation of FMCW SAR. Experimental results on the simulated and actual Ku-band SAR data proved that, for full swath and high squint mode FMCW SAR, the proposed approaches are valid and greatly helpful to improve the imaging quality.

Internal Wave Parameter Inversion at Malin Shelf Edge Based on the Nonlinear Schrödinger Equation

We established a deep-sea internal wave detection model based on the nonlinear Schrödinger (NLS) equation and Synthetic Aperture Radar (SAR) images, and applied the model to the Malin Shelf edge, located at UK Continental Shelf, west of Scotland, to retrieve internal wave parameters. We selected the SAR images of internal waves at Malin Shelf edge, combined NLS equation with the action spectrum balance equation and Bragg scattering model, retrieved the amplitudes and phase velocities of the internal waves at Malin Shelf edge, and compared these data with those retrieved by the model based on KdV equation and those observed at the same period. The results show that the error between the data retrieved by our model and the measured data is very small, while the difference between the data retrieved by the detection model based on KdV equation and the measured data is significant. In addition, the phase velocities, calculated in our model and the model based on KdV equation, are both close to the measured data. Consequently, our model is valid and more accurate for the parameter inversion of internal waves in deep-sea area.

Depth inversion in coastal water based on SAR image of waves

Wave-number spectrum technique is proposed to retrieve coastal water depths by means of Synthetic Aperture Radar (SAR) image of waves. Based on the general dispersion relation of ocean waves, the wavelength changes of a surface wave over varying water depths can be derived from SAR. Approaching the analysis of SAR images of waves and using the general dispersion relation of ocean waves, this indirect technique of remote sensing bathymetry has been applied to a coastal region of Xiapu in Fujian Province, China. Results show that this technique is suitable for the coastal waters especially for the near-shore regions with variable water depths.

Multi-frequency SAR images of ship-generated internal waves

During the joint U.K./U.S.A. experiment conducted in the Loch Linnhe, Scotland, U.K., in 1989, the Jet Propulsion Laboratory (JPL) multifrequency airborne synthetic aperture radar (SAR) was deployed to investigate the relation between the SAR images and ship-generated internal waves. One of the intriguing results, consistent throughout the experiment, was the striking difference in phase (position) between the images of internal wave wakes in the P-band ( 68cm) wavelength and those in L-band ( 24 cm) and C-band ( 6 cm) wavelengths. An explanation for this difference is found in the sensitivity of different radar wavelengths to oceanic surface waves in different ranges of wavelengths, that are perturbed by varying surface currents by different amounts and at different positions, depending on the wavelength of surface waves.

ERS‐1 and Almaz estimates of directional ocean wave spectra conditioned by simultaneous aircraft SAR and buoy measurements

Abstract The European Space Agency ERS‐1 C‐band V‐V polarization synthetic aperture radar (SAR) and the Russian Almaz S‐band H‐H polarization SAR are compared for their wavenumber response to ocean wave fields existing on 23 November 1991 at the Grand Banks site of the North American ERS‐1 SAR Wave Spectra Validation Experiment. Two‐dimensional wave spectra from two Wavec heave, pitch and roll buoys and a Canadian CV‐580 aircraft C‐band V‐V polarization SAR are used to condition a linear modulation transfer model of wave imaging with SAR. A model of hydrodynamic modulation is included with the velocity bunching and tilt imaging mechanisms to better understand wind and wave interactions. Krogstad's quasi‐linear formulation of Hasselmann's ocean‐SAR integral transform is applied to model SAR velocity bunching and azimuth smearing. Narrow and broad bandwidth components of azimuth wavenumber response for the aircraft SAR are associated with, respectively, non‐linear and incoherent velocity smearing during Doppler resolution of the radar scene. The stationary resolutions of the SAR systems are compared for homogeneous scenes of wind‐roughened, but fetch‐limited, sea surfaces. This comparison is conducted in the Chesapeake Bay of Maryland using ERS‐1 and Almaz satellite imagery collected on 9 May 1992 and 14 May 1991, respectively. The results confirm that SAR imaging of ocean waves can be improved by flying platforms with low R/V (range/velocity) ratios to alleviate the azimuth velocity smear, and near‐nadir incidence angles to increase the effect of tilt modulation.

The effect of range-to-velocity ratio on simulated SAR images of ocean wind waves

Synthetic-aperture-radar (SAR) imaging of locally wind-generated ocean waves is simulated using the subwindowing technique. Several SAR range-to-velocity ratios (R/V) are used. Coherence is maintained throughout the imaging process, so the final image spectra include the noise resulting from phase-interference fading. Maximum spectral signal-to-noise ratio (SNR) is achieved with an R/V that maximizes velocity bunching modulation through imaging nonlinearities. Although the azimuthal shift of the spectral peak can be lessened by utilizing a lower R/V, the maximum wave number at which the signal exceeds the spectral noise does not change significantly, and the resulting decrease in overall S/N would probably make spectral extraction more difficult. >

Synthetic aperture radar imaging of ocean surface waves: multi-look and single-look systems

A single two-dimensional expression is given for the (speckle-averaged) image associated with a model of ocean swell which may be applied to single-look and multi-look synthetic aperture radar (SAR) systems (albeit with different arguments). That expression accommodates real and artificial cross-section modulation mechanisms, shows rescaling effects (i.e. rotation of the image of a wavefield). suggests the use of processor refocusing to maximize image contrast, accounts for scene coherence, and indicates a variation of image contrast with range (assuming homogeneous swell). Most of the above have been observed and discussed previously in the literature. However, in this paper it is shown that all the effects are derived (simultaneously). by a relatively simple, rigorous and self-consistent analysis: it is not always necessary to treat the SAR imaging of ocean waves in a piece-wise manner. The analysis differs from that most frequently found in the literature. A space-time variant point spread function is not presumed; and some of the conclusions, in particular with regard to the optimum image processing strategy, differ with those following the use of the more conventional forms of analysis. Throughout, care is taken to minimize, but also to make explicit, the underlying assumptions in the treatment.

Overview of SAR Chesapeake tower experiment

Synthetic aperture radar (SAR) imaging of the ocean surface promises to be an important tool in ocean remote sensing. The long‐range goal of the work reported here is to understand SAR imaging in sufficient detail that airborne and/or spaceborne SARs become reliable tools for oceanic research and operational use.TOWARD (Tower Ocean Wave and Radar Dependence Experiment) [see Shemdin, 1988, 1990], a predecessor experiment to the SAR and X‐Band Ocean Nonlinearities Experiment at Chesapeake Light Tower (SAXON:CLT), provided a comprehensive data set to test the theoretical concepts advanced on SAR imaging of the ocean surface. A significant achievement of TOWARD is determining that none of the then available theories on SAR imaging of long surface waves could explain all the SAR observations satisfactorily. Improved models immediately followed as a consequence of the TOWARD finding. In spite of the significant insights gained in TOWARD, gaps remain in understanding radar backscatter from the sea surface.