An L-band geophysical model function for SAR wind retrieval using JERS-1 SAR

An L-band geophysical model function is developed using Japanese Earth Resources Satellite-1 (JERS-1) synthetic aperture radar (SAR) data. First, we estimate the SAR system noise, which has been a serious problem peculiar to the JERS-1 SAR. It is found that the system noise has a feature common in all the SAR images and that the azimuth-averaged profile of noise can be expressed as a parabolic function of range. By subtracting the estimated noise from the SAR images, we can extract the relatively calibrated ocean signals. Second, using the noise-removed SAR data and wind vector data from the NASA Scatterometer and buoys operated by the Japan Meteorological Agency, we generate a match-up dataset, which consists of the SAR sigma-0, the incidence angle, the surface wind speed, and wind direction. Third, we investigate the sigma-0 dependence on incidence angle, wind speed, and wind direction. While the incidence angle dependence is negligible in the present results, we can derive distinct sigma-0 dependence on wind speed and direction. For wind speeds below 8 m/s, the wind direction dependence is not significant. However, for higher wind speeds, the upwind-downwind asymmetry becomes very large. Finally, taking into account these characteristics, a new L-band-HH geophysical model function is produced for the SAR wind retrieval using a third-order harmonics formula. Resultant estimates of SAR-derived wind speed have an rms error of 2.09 m/s with a negligible bias against the truth wind speed. This result enables us to convert JERS-1 SAR images into the reliable wind-speed maps.     

JERS-1 SAR image quality and interferometric potential

As part of the JERS-1 investigation program, the authors evaluate the duality of images from the Japanese radar and validate its interferometric capabilities. JERS-1 interferometry has the potential to derive digital terrain models and measure ground displacements     

星载合成孔径雷达海面风速反演技术研究

CMOD系列地球物理模式函数作为业务化应用的风速反演模式,已由CMOD4（1997）发展到CMOD5.N（2010）,且该系列模式函数还在不多的发展完善。     

Wave and wind retrieval from sar images of the ocean

Over the past few years, recognition of the importance of the coastal zone has led to the establishment of international programmes for monitoring the coastal zone environment and its change. The European programme marsais is part of this effort. One important component of such actions aims to better predict the sea surface wind and wave dynamics in these vulnerable regions where most economic marine activity is taking place. Indeed, ocean surface wind and wave observations serves both oceanographic and meteorological communities and have direct applications for driving ocean circulation models, numerical predictions and short term forecasts, but also for advancing in the physical understanding of the complex interactions that take place at the ocean-atmosphere interface. As now well recognised, satellite data and particularly the weather independent radar remote sensing data present potential advantages and applications to achieve these requirements. Nowadays, sea surface remote sensing techniques are rapidly developing throughout the world and need some kind of assessment. Altimetry and scatterometry are well proven techniques, which result in recognised operational applications. Synthetic Aperture Radar (sar) missions have not enjoyed such successes. However numerous space borne radar images of the ocean surface have revealed a wealth of information on different dynamical processes and sar images of the ocean surface very often reveal a remarkable range of signatures on the uppermost layers of the sea. These data have resulted in numerous quantitative scientific findings and theoretical advances in upper-layer and lower atmosphere dynamics. In this review, the main different techniques developed to retrieve surface wave and wind information are recalled. Illustrations are given for envisat wave mode products.     

A continental-scale mosaic of the Amazon basin using JERS-1 SAR

A methodology, example and accuracy assessment are given for a continental-scale mosaic of the Amazon River basin at 100 m resolution using the JERS-1 satellite. This unprecedented resource of L-band SAR data collected by JERS-1 during the low-flood season of the river amounts to a collection of 57 orbits of the satellite and a total of some 1500 1 k/spl times/1 kB images. Interscene overlap both in the along-track and cross-track directions allows common reference points to be used to correct individual scene geolocation inaccuracies that have been derived from the satellite ephemeris. The set of common reference points is assembled into a matrix formulation that is used to solve for individual scene geometric offsets. By correcting for these offsets, each scene is placed within a global coordinate system, which can then be used as the basis for creating a final, visually seamless mosaic. The methodology employed in this approach allows for a mathematical foundation to be applied to the mosaicking process as well as providing a unique, traceable solution for correctly geolocating satellite imagery.     

基于SAR图像的点状目标检测方法研究

分析了SAR图像目标检测中常用的方差法、恒虚警算法,讨论了对纹理和灰度都敏感的扩展分形法,然后针对弱目标的检测,提出了基于小波多分辨率能级分析的检测方法,最后对四种算法的性能作了比较,并指出了下一步的研究方向.     

Directional analysis of SAR images aiming at wind direction

Currently, the retrieval of wind fields from synthetic aperture radar (SAR) images suffers from inadequate knowledge of the wind direction. State-of-the-art spectral analysis works fine on open seas, but is limited in spatial resolution. The method described here is based on the local gradients computed with standard image processing algorithms. It handles image features not caused by wind and can be applied to irregularly shaped regions. The new method has already been applied to many images from the European Remote sensing Satellite SARs and RADARSAT-1 ScanSAR, usually supplying reasonable wind fields. The spatial sampling most frequently used was 20 /spl times/ 20 and 10/spl times/10 km/sup 2/. In some cases, samplings down to 1/spl times/1 km/sup 2/ were tested. This paper describes the local gradients method including the filtering of nonwind generated image features and gives some application examples.     

Validating a scatterometer wind algorithm for ERS-1 SAR

The ocean surface wind field is observed from space operationally using scatterometry. The European Space Agency's (ESAs) ERS-1 satellite scatterometer routinely produces a wind product that is assimilated into forecast models. Scatterometry cannot give accurate wind estimates close to land, however, because the field of view of a spaceborne scatterometer is on the order of 50 km. Side lobe contamination, due to the large contrast in backscatter between land and water, compounds the problem. Synthetic aperture radar (SAR) can provide wind speed and direction estimates on a finer scale, so that high-resolution wind fields can be constructed near shore. An algorithm has been developed that uses the spectral expression of wind in SAR imagery to estimate wind direction and calibrated backscatter to estimate wind strength. Three versions, based on C-band scatterometer algorithms, are evaluated for accuracy in potential operational use. Algorithm estimates are compared with wind measurements from buoys in the Gulf of Alaska, Bering Strait, and off the Pacific Northwest coast by using a data set of 61 near-coincident buoy and ERS-1 SAR observations. Representative figures for the accuracy of the algorithm are ±2 m/s for wind speed and ±37° for wind direction at a 25-km spatial resolution     

基于DBSCAN技术的SAR图像感兴趣区域鉴别

使用一种新奇的聚类方法从粗略检测后的SAR图像中提取感兴趣区域(ROI),再通过多特征提取和综合鉴别,去除虚警保留目标,为进一步的目标识别做准备。自动目标聚类是基于SAR图像的自动目标识别系统的难点之一,带有噪声的基于密度的聚类方法 (DBSCAN)可以发现任意形状的聚类目标,只依赖于两个不敏感的系统参数,通过区域判断缩减计算时间减少计算内存,很好地适应了自动目标识别的系统需要。多特征目标鉴别方案基于聚类结果,研究聚类得到的感兴趣区域,通过提取多种特征综合判断,有效去除了虚警。所述方法已应用于某SAR-ATR系统,得到了很好的应用体验。     

Analyzing lead information from SAR images

Leads are relatively linear features in the sea ice cover, which are composed of open water or new, thin ice. Because of their composition, leads impact the ocean/air heat exchange. Automated analysis of leads from sea ice imagery may provide a means of gathering important information about the sea ice cover and its climatic influence. This paper describes: (1) a method for extracting and analyzing leads from ERS-1 synthetic aperture radar (SAR) images classified by ice type and (2) the results of using this method on images of the Beaufort Sea. The methodology consists of identifying potential lead features in the image and measuring their characteristics both before and after using a thinning or skeletonization technique on the features. The measurements obtained using this method include lead area, average width, number of leads in an area, amount of branching, and linearity of the lead. These measurements were analyzed with respect to the time of year and the latitude of the images. Results indicate that the measurements produced by the methodology are consistent with lead measurement distributions that others have found. The results of the study suggest that the methodology is appropriate to study lead characteristics on a large scale     

ERS-1 SAR images of atmospheric gravity waves

ERS-1 synthetic aperture radar (SAR) images of atmospheric gravity waves over the ocean are discussed. Several case studies are presented in detail. It is shown that the well-organized long wavelength (1 to 10 km) wave phenomena which often are seen in SAR images over the ocean may be atmospheric gravity waves. The waves appear in the SAR images because they modulate the surface wind speed which in turn modulates the surface roughness and the radar cross section. The wavelength may be measured directly from the SAR image, and the mean wind speed and wind speed modulation near the ocean surface may be estimated from the observed radar cross section modulation using a wind retrieval model. The atmospheric gravity waves usually were generated by the approach or passing of a meteorological front. Atmospheric soundings and a two-layer model for the lower troposphere indicate that, in general, the observed atmospheric wave phenomena could have been supported by accompanying temperature inversion layers and wind shears     

Forest height retrieval from commercial X-band SAR products

This paper assesses the accuracy and reliability of tree height retrieval over coniferous plantations using X-band interferometry. Factors such as crown shape, density, tree height, incidence angle, and slope have been assessed and quantified using a simple polarimetric radar interferometry simulator to determine their impact on height retrieval. Results from model simulation show that the most important factors are: crown shape, plantation density, and tree height. Variation in viewing angle and small slopes (<30/spl deg/) appear to have only small effects. These results appear to be in reasonably good agreement with the retrieved tree height from airborne X-band Intermap data over coniferous plantations in the U.K.     

Three-dimensional surface reconstruction from multistatic SAR images

This paper discusses reconstruction of three-dimensional surfaces from multiple bistatic synthetic aperture radar (SAR) images. Techniques for surface reconstruction from multiple monostatic SAR images already exist, including interferometric processing and stereo SAR. We generalize these methods to obtain algorithms for bistatic interferometric SAR and bistatic stereo SAR. We also propose a framework for predicting the performance of our multistatic stereo SAR algorithm, and, from this framework, we suggest a metric for use in planning strategic deployment of multistatic assets.     

Unconstrained inversion of waveheight spectra from SAR images

A procedure for inverting the nonlinear relationship between the waveheight spectrum and the SAR image spectrum is presented, and this procedure is evaluated using simulated data as well as actual ERS SAR data collected near Duck, NC. Results of this nonlinear inversion are compared with those obtained from a quasi-linear estimation procedure using simulated data, in order to illustrate the effects of nonlinearities in the imaging process. These effects include the well-known azimuth falloff effect as well as the generation of harmonics which appear in the background region of the spectrum. The nonlinear inversion technique is able to reproduce the input image spectrum to high accuracy, although the wave spectrum obtained by this procedure is not necessarily the same as the input wave spectrum. In general, the estimated wave spectrum is quite similar to the portion of the input wave spectrum within the SAR passband region, but none of the energy outside the passband is recovered. The background signals due to nonlinear effects can cause large errors in the quasi-linear estimation procedure because these signals appear in regions of the spectrum where the SAR modulation transfer function (mtf) is small. Results using actual SAR data also indicate that energy within the passband is recovered fairly accurately, although energy outside the passband is clearly lost     

基于Nonsubsampled Contourlet变换的SAR图像形状特征检索

Nonsubsampled Contourlet变换是一种非抽取得具有平移不变性的多尺度多方向的变换。将Canny算子和Nonsubsampled Contourlet变换(NSCT)[1]相结合,对图像运用Canny算子[2]提取边缘特征,再进行Nonsubsampled Contourlet变换,引入了三阶中心矩作为特征向量提取形状特征的算法。实现了基于Nonsubsampled Contourlet变换的图像形状特征检索,并将结果与基于2-D小波变换和基于Contourlet变换的图像形状特征检索作了比较,实验结果证明该方法的图像形状特征检索效率有较大的提高。     

Sea ice monitoring by L-band SAR: an assessment based on literature and comparisons of JERS-1 and ERS-1 imagery

Spaceborne single-polarization C-band synthetic aperture radar (SAR) imagery is widely used to gather information about the state of the sea ice cover in the polar regions. C-band is regarded as a reasonable choice for all-season monitoring capabilities. For specific mapping tasks, however, other frequency bands can be more suitable. In the first part of this paper, the summary of a literature study dealing with the utilization of L-band SAR imagery for sea ice monitoring is presented. Investigations reveal that if deformation features such as ice ridges, rubble fields, and brash ice are to be mapped, L-band radar is superior in a number of cases. The second part of this paper addresses the comparison of JERS-1 and ERS-1 SAR images that were acquired over sea ice east of Svalbard and along the east coast of Greenland. The effects of the different frequencies, polarizations, and incidence angles of the two SAR systems are discussed. It is demonstrated that the images of both sensors complement one another in the analysis of ice conditions, resulting in a more detailed view of the sea ice cover state.     

基于中心点回归的大场景SAR图像舰船检测方法

合成孔径雷达(synthetic aperture radar,SAR)图像舰船目标检测在军事和民用领域有着重要的应用.然而随着SAR图像成像能力的提升,SAR成像场景越来越大,舰船目标检测存在两个难点:一是舰船目标在整幅图像中所占比例极小,很难与周围背景分开;二是靠岸舰船目标通常密集排列,目标之间难以区分.目前常用基...     

Similarity retrieval of trademark images

The Artisan system retrieves abstract trademark images by shape similarity. It analyzes each image to characterize key shape components, grouping image regions into families that potentially mirror human image perception, and then derives characteristic indexing features from these families and from the image as a whole. We have evaluated the retrieval effectiveness of our prototype system on more than 10,000 images from the UK Trade Marks Registry     

Filtering of multichannel SAR images

An explicit form of the linear multichannel synthetic aperture radar (SAR) intensity filter, which preserves radiometry while optimally reducing speckle is derived, together with a compact expression for the theoretical gain in equivalent numbers of looks (ENLs). The filter can be applied to mixed data types, which is demonstrated using a combination of ERS and JERS satellite data, and confirms the filter performance predicted by the theory. Tests indicate that a simplified form of the filter, which neglects correlation between images, gives an ENL only slightly less than optimal, while being much easier to implement. Exact analysis of the effect of estimating filter weights shows that the linear increase in ENL with the number of images predicted for the ideal filter does not occur. In practice, the ENL is affected by the window size used to estimate the weights and saturates as the number of images increases. An efficient recursive form of the filter is described, which is most naturally applied to multitemporal data for the practically important case where the current image is uncorrelated with previous images in a data sequence