Performance improvement in multi-ship imaging for ScanSAR based on sparse representation

There is always a compromise between unambiguous wide-swath imaging and high cross-range resolution owing to the constraint of minimum antenna area for conventional single-channel spaceborne synthetic aperture radar(SAR)imaging.To overcome the inherent systemic limitation,multi-channel SAR imaging has been developed.Nevertheless,this still suffers from various problems such as high system complexity.To simplify the system structure,a novel algorithm for high resolution multi-ship ScanSAR imaging based on sparse representation is proposed in this paper,where the SAR imaging model is established via maximum a posterior estimation by utilizing the sparsity prior of multi-ship targets.In the scheme,a wide swath is generated in the ScanSAR mode by continuously switching the radar footprint between subswaths.Meanwhile,high crossrange resolution is realized from sparse subapertures by exploiting the sparsity feature of multi-ship imaging.In particular,the SAR observation operator is constructed approximately as the inverse of conventional SAR imaging and then high resolution SAR imaging including range cell migration compensation is achieved by solving the optimization.Compared with multi-channel SAR imaging,the system complexity is effectively reduced in the ScanSAR mode.In addition,enhancement of the cross-range resolution is realized by incorporating the sparsity prior with sparse subapertures.As a result,the amount of data is effectively reduced.Experiments based on measured data have been carried out to confirm the effectiveness and validity of the proposed algorithm.     

Suitability of SAR imagery for automatic flood mapping in the Lower Mekong Basin

Flood detection and inundation mapping are amongst the most important applications for remote-sensing data. Space-borne radar systems, synthetic aperture radar (SAR) in particular, and its application for waterbody mapping have recently been subject to research in many publications. Although very good results have been achieved with such data, in some cases automatic waterbody classification based on SAR data is not feasible. Factors influencing the applicability are, e.g., local environmental conditions, roughening of water surfaces due to wind, or the satellite observation geometry. In this study, a measure for the usability of SAR imagery for flood mapping was investigated. Additionally, a method for permanent waterbody mapping was introduced. The study is based on Envisat ASAR wide swath mode (150 m spatial resolution) data of the Mekong River Basin. For the usability measure, the concept of ‘high-contrast tiles’ was established, which allows an a priori estimation of the expected accuracy of a waterbody classifier. The SAR-based permanent waterbody map was used for the validation of the approach. It was found that, for the test site, the new SAR usability measure allows the identification of unsuitable scenes with a certainty of more than 90%. The method is expected to be very useful for near-real-time flood mapping applications where human interaction is neither desired nor feasible when large regions and large data volumes are considered.     

Texture image prior for SAR image super resolution based on total variation regularization using split Bregman iteration

In this article, we propose a total variation (TV) regularization approach for the reconstruction of super-resolution synthetic aperture radar (SAR) image based on gradient profile prior or other texture image prior in the maximum a posteriori framework. We also design a novel super-resolution reconstruction algorithm via split Bregman iteration with the known degradation matrix, thereby enhancing the resolution of the SAR image. The parameter adaptation of the TV regularization is performed based on the high-resolution (HR) SAR image at each step. Several evaluation indices are tested on SAR images for objective assessment of the performance of SAR image super-resolution reconstruction. This computationally efficient algorithm is robust to noise in SAR scenes in HR image estimation. Experimental results show that the proposed split Bregman super-resolution approach can effectively avoid the speckle noise generated due to some strange textures and has good effect of noise suppression, while effectively maintaining the SAR image content, the structure of the SAR image is more apparent. Additionally, the experimental results on real SAR scenes also demonstrate the effectiveness of the proposed algorithm and demonstrate its superiority to other super-resolution algorithms.     

Design and performance analysis of orthogonal coding signal in MIMO-SAR

Multi-input multi-output (MIMO) radar which has evident advantages in many applications is a new radar system.Applying the MIMO technique to the earth observing synthetic aperture radar (SAR) system offers effective ways for the improvement of high resolution and wide swath imaging and ground moving target indication (GMTI) systems.Designing the optimal orthogonal waveform is a crucial problem in the research on MIMO radar.First,the index definition of synthetic integrated side-lobe level ratio (ISLR) is pr...     

多发多收SAR编码正交信号设计及性能分析

多发多收(MIMO)雷达是一种新的雷达体制,具有许多突出的优点.将MIMO技术应用于对地观测的SAR系统,将为高性能地完成高分辨率、宽测绘带成像和GMTI等功能提供有效途径.正交波形优化设计是MIMO雷达研究中的基础性关键问题.首先针对SAR应用的特点,考虑同频编码正交信号之间互相关能量影响,提出了综合积分旁瓣比指标定义.然后通过理论分析和一维数值仿真论证了同频编码正交信号综合积分旁瓣比性能无法满足SAR成像的要求;再通过数值仿真验证了失配滤波处理仍然无法改善同频编码正交信号的综合积分旁瓣比性能.最后优化设计了一组相位编码正交信号作为MIMO-SAR发射信号,通过MIMO-SAR成像和InSAR仿真试验,进一步验证了分析结论的有效性.     

海洋监视监测SAR卫星任务初步分析

以海浪、船舶、溢油、内波和海冰等海洋现象为主要的观测目标,海洋监视监测卫星利用多极化SAR的高分辨率模式进行精细成像,识别目标细节特征,利用宽观测带扫描模式进行快速覆盖观测,获取全球海洋遥感信息。针对各观测目标要素,借鉴ERS和RADARSAT-1的观测结果,结合理论分析与仿真,初步分析了海洋监视监测SAR卫星轨道参数和有效载荷工作模式等卫星任务。     

基于DBF技术的星载SAR宽测绘带实现方法

在研究距离向使用数字波束形成(Digital Beanforming,DBF)实现星载SAR宽测绘带原理的基础上,分析了星载DBF-SAR距离模糊与传统星载SAR距离模糊的不同,并利用阵列天线零点指向技术实现宽零陷的原理,展宽模糊点所对应位置零陷宽度,从而在提高星载SAR宽测绘带基础上有效地减小距离模糊,提高成像质量.通过仿真和比较分析,表明使用具有宽零陷指向特性的DBF技术实现星载SAR宽测绘带模式的可行性.     

An approach to evaluate and monitor RISAT-1 SAR from level-0 raw data

Data quality evaluation of synthetic aperture radar (SAR) products is essential with respect to mission performance and reliability of the data products for users. The generation of any value-added SAR product starts with a level-0 raw data product, so it is vital firstly to analyse and monitor the raw data. In other words, any inconsistency or error occur because of data, the SAR processor requires to ‘quality evaluate’ the raw data first to ensure that the higher level of data products meets the user specifications. Many parameters can be evaluated from the raw data per se before SAR processing. Here, an independent approach is formulated to evaluate the long-term stability and performance of the SAR system from raw data. Quality parameters such as echo data statistics in terms of bias in the mean of Inphase (I) and Quadrature in phase (Q), power imbalance, phase imbalance, antenna pattern in elevation for the qualified swath, Doppler centroid estimation, and chirp phase and amplitude stability were evaluated and monitored for various scenes of an orbit and characterized in detail for different beams covering the near to far range. In the Radar Imaging Satellite (RISAT-1), the SAR beam is formed by a number of transmit/receive modules (TRMs) (total number of active TRMs depends on the look angle), and the consolidated effect of TRMs can be observed from the raw data instead of individual TRMs, which enables examination of the overall behaviour of beams, from near to far range in different orbits, for temporal stability. In this article, for the first time, a novel approach is taken to observe and evaluate the antenna pattern for the 3 dB qualified swath from range-uncompressed raw data and to relatively monitor the different beams from level-0 raw data for the qualified swath, for both extended homogeneous and non-homogeneous targets. Furthermore, the approach is justified in that it is not necessary to perform range compression, and also one can use scenes with heterogeneous targets to estimate and monitor the beamwidth parameter of the antenna pattern. This article focuses on the results obtained from RISAT-1 level-0 raw data from various beams covered in strip-map mode. The methodology to evaluate the RISAT-1 SAR system from raw data is discussed. Analysis is carried out with respect to different beams (60 beam data of different orbits either side, covering near to far nadir swath coverage) of fine resolution strip-map-1 (FRS-1) mode in circularly transmitted and linearly received polarization, with a defined swath of 25 km with 3 m × 2 m (azimuth × range) resolution. The results of evaluation and monitoring analysis show consistency in the identified parameters observed over time for different beams, and they are within specifications.     

Symbolic target detection in SAR imagery via rotationally invariant-weighted feature extraction

This article introduces the application of a physics-based symbolic image partitioning method to detect targets in synthetic aperture radar (SAR) imagery. ‘Targets’ in this case refer to vehicular objects which produce a distinct radar return pattern, and have spatial characteristics that are known a priori. The proposed Rotationally Invariant Symbolic Histogram (RISH) detection method co-analyses both target and speckle statistics, and significantly reduces computational requirements by partitioning the data into a discrete number of state representations. RISH requires only one pass for robust detection, unlike other SAR detection methods which rely on difference metrics calculated using multiple passes. To improve performance in high-resolution data, RISH uses a weighted feature extraction algorithm to avoid the common requirement of processing each pixel of the image equally. The weighted structure extracts geometrically undefined and rotationally invariant target features. This article details the analysis of 24 experimentally obtained very high-frequency (VHF)-band SAR magnitude images using this novel approach to SAR target detection. In localizing small (~8.4 m²) foliage-concealed targets, without the aid of pre-processing, this method results in high performance characteristics (90% true positive) with a low Type-II error rate of 6.4 false alarms per 1 × 10⁶ m². With the addition of change detection, RISH lowers the error rate by 85%.     

Ship detection performance using simulated dual-polarization RADARSAT constellation mission data

The RADARSAT Constellation Mission (RCM) planned to be launched in 2018 is designed to support maritime surveillance requirements in which ice, wind, oil pollution, and ships are to be monitored by providing wide swath beam modes. In this article, we introduce the first analysis of ship detection performance using simulated RCM data. We report ship detection performance using a likelihood ratio test (LRT) for three wide swath RCM imaging modes: Ship Detection (25 m), Low Resolution (100 m), and Medium Resolution (50 m). These beam modes were assessed for a number of dual-polarimetric (dual-pol) systems, including the standard linear polarizations as well as compact polarimetry (CP). These data were simulated from RADARSAT-2 Fine Quad (FQ) mode in the three RCM modes. Furthermore, the detection performance of the pseudo-quad data reconstructed from the simulated circular transmit, linear receive data is also investigated and compared to the other systems’ performance for the three RCM modes. The receiver operating characteristic curves are used in this study as the basic measure of detection performance for all beam modes and all detectors. We found that the compact polarimetric SAR detectors outperform the conventional linear dual-pol detectors at the three RCM modes for ship detection for medium to high incidence angles. At steep angles, the performance of the two polarization configurations was comparable. Our study confirmed that detection performance improved as incidence angle and spatial resolution increased. We also investigated the impact of the ship orientation with respect to the radar beam and found that detection performance was generally higher when ship was oriented perpendicular to the radar beam.     

带距离徙动校正的压缩感知PFA成像方法

目的 极坐标格式算法（PFA）是合成孔径雷达（SAR）聚束模式下的一种高分辨率成像算法,方位向增加孔径长度带来了数据存储和传输的负担,利用压缩感知进行合成孔径雷达成像可以减小采样率,以前的研究往往认为图像是2维可分离的而忽略距离徙动的影响,造成了图像质量的下降。提出一种在方位向利用压缩感知处理的PFA成像算法,可以校正距离徙动,保证压缩感知成像的图像分辨率。方法 在方位向进行压缩感知处理的过程时,采用了随距离空间频率变化的傅里叶基。结果 该方法可以有效代替PFA处理过程中的方位向插值,消除距离徙动的影响,保证距离向和方位向的分辨率。结论 仿真和实测数据的处理结果证明了该方法的有效性。     

合成孔径与实孔径雷达谱域成像算法对比分析

讨论了合成孔径雷达(Synthetic aperture radar,SAR)和实孔径雷达(Real aperture radar,RAR)一维扫描方式下的谱域成像实现问题.文中从SAR和RAR扫描下的波数域波散关系入手,分析了这两种扫描方式下的谱域填充区域和成像分辨率,指出了二者的异同,导出了相应的成像算法.单目标和组合目标的雷达成像仿真实验验证了两种扫描方式下成像算法的有效性和理论分析结果.     

混沌信号雷达SAR成像的新方法

针对现有的合成孔径雷达(SAR)成像方法,介绍了隐抽样平均算法的基本原理及时延确定的方法;进一步,将隐抽样平均算法用于SAR成像中,提出了基于隐抽样平均的SAR成像算法;该成像算法利用二元混沌信号作为雷达发射信号,通过产生一个特征波形来指示目标的时延;与传统的SAR相关成像算法相比,该成像算法不仅简单易行,运算量小,成像时间短,成像效率高,而且重构图像具有较高的图像分辨率;仿真结果表明,图像中的目标轮廓清晰,图像品质较高。     

基于稀疏贝叶斯学习的雷达目标成像技术

利用傅立叶变换进行雷达目标成像,分辨率受瑞利准则的限制;超分辨成像技术能最著改善雷达图像的分辨率,但算法的复杂性急剧增加并且正则化参数不易选取.以稀疏贝叶斯学习为基础,针对雷达成像系统的结构特点,提出了一种基于快速傅立叶变换(FFT)和分块托普里兹(Toeplitz)系统的快速超分辨成像算法.算法无需存储系数矩阵,极大地降低了存储量和运算量.进一步,通过寻找拟合误差曲线和稀疏性度量函数曲线的交点实现了正则化参数的方便选择.仿真结果表明,算法对雷达目标图像具有良好的分辨率增强能力.     

匀速运动目标的聚束SAR成像特征分析

运动目标的合成孔径雷达(SAR)成像特征是SAR/GMTI系统中进行运动目标检测和成像的基础.以往研究都是在两维可分离条带SAR成像算法条件下讨论目标运动对成像的影响,而很少考虑高分辨聚束SAR成像算法处理后运动目标的成像特征.本文推导了两种典型高分辨聚束SAR成像算法(RMA和PFA)处理后的动目标误差谱表达式,并在此基础上从目标几何定位误差、残留距离徙动和散焦等方面给出了完整的聚束SAR运动目标响应特征分析.最后通过仿真数据处理验证了分析结果.     

A novel spaceborne SAR wide-swath imaging approach based on Poisson disk-like nonuniform sampling and compressive sensing

Since the range swath width in the conventional single channel spaceborne synthetic aperture radar(SAR)is restricted by the system parameters,there is a trade-off between the azimuth resolution and the swath width in order to satisfy the Nyquist sampling criterion.In this paper,we propose a novel spaceborne SAR wide-swath imaging scheme based on compressive sensing(CS)for the sparse scene.The proposed method designs a Poisson disk-like nonuniform sampling pattern in the azimuth direction,which meets the demand of wider swath by restricting the smallest time interval between any two azimuth samples,with the conventional sampling pattern preserved in the range direction.By a similar way to the processing procedure of spectral analysis(SPECAN)algorithm,the linear range migration correction(RMC)is realized while carrying out range compression,which can meet the demand for focusing with middle level resolution.To reduce the computation load of CS reconstruction,we propose a novel fast reconstruction algorithm based on nonuniform fast Fourier transform(NUFFT),which greatly reduces the computation complexity from O(2M N)to O(4N log N).Experiment results validate the effectiveness of the proposed methods via the point target simulation and the Radarsat-1 raw data processing in F2 mode.     

Using sentinel-1A SAR wind retrievals for enhancing scatterometer and radiometer regional wind analyses

Scatterometer surface wind speed and direction observations in combination with radiometer wind speeds allow to generate surface wind analyses with high space and time resolutions over global as well as at regional scales. Regarding scatterometer sampling schemes and physics, the resulting surface wind analyses suffer from lack of accuracy in areas near coasts. The use of the synthetic aperture radar (SAR) onboard the Sentinel-1A satellite attempts to address the enhancement of surface wind analyses issues. In this study, SAR wind speeds and directions retrieved from backscatter coefficients acquired in interferometric wide (IW) swath mode are used. Their accuracy is determined through comprehensive comparisons with moored buoy wind measurements. SAR and buoy winds agree well at offshore and nearshore locations. The statistics characterizing the comparison of SAR and buoy wind speeds and directions are of the same order as those obtained from scatterometer (Advanced SCATterometer (ASCAT) and RapidScat) and buoy wind comparisons. The main discrepancy between SAR and buoy data are found for high wind speeds. SAR wind speeds exceeding 10 m s^–1 tend to be underestimated. A similar conclusion is drawn from SAR and scatterometer wind speed comparisons. It is based on the underestimation of SAR backscatter coefficient (σ°) with respect to σ° estimated from scatterometer winds and the geophysical model function (GMF) named CMOD-IFR2 (Ifremer C band MODel). New SAR wind speeds are retrieved using CMOD-IFR2. The corrected SAR retrievals allow better determination of the spatial characteristics of surface wind speeds and of the related wind components in near-coast areas. They are used for enhancing the determination of the spatial structure function required for the estimation of wind fields gridded in space and time at the regional scale. The resulting wind fields are only determined from scatterometer wind observations in combination with radiometer retrievals. Their qualities are determined through comparisons with SAR wind speeds and directions, and through their application for determination of wind power off Brittany coasts.     

Fuzzy classification of earth terrain covers using complex polarimetric SAR data

The conventional approach of terrain image classification that assigns a specific class for each pixel is inadequate, because the area covered by each pixel may embrace more than a single class. Fuzzy set theory which has been developed to deal with imprecise information can be incorporate in the analysis for a more appropriate solution to this problem. In the current state of imaging radar technology, polarimetric synthetic aperture radar (SAR) is unique in providing complete polarization information of ground covers for more effective classification than a single polarization radar. In this paper, we use the fuzzy c-means clustering algorithm for unsupervised segmentation of multi-look polarimetric SAR images. A statistical distance measure adopted in this algorithm is derived from the complex Wishart distribution of the complex covariance matrix. In classifying polarimetric SAR imagery, each terrain class is characterized by its own feature covariance matrix. The algorithm searches for cluster centres for each class and generates a fuzzy partition for the whole image. Membership grades obtained for each pixel provide detailed information about spatial terrain variations. Classification of the image is achieved by choosing a defuzzification criterion. When the back-scattering characteristics of two or more classes are not well distinguished from each other, a divisive hierarchical clustering procedure is adopted to locate their respective feature covariance matrices. NASA/JPL AIRSAR data is used to substantiate this fuzzy classification algorithm.     

Applicability of SAR-based wave retrieval for wind–wave interaction analysis in the fetch-limited Baltic

In this article, a method for the detection of wave field parameters from synthetic aperture radar (SAR) imagery in the fetch-limited Baltic Sea is presented. Over the Baltic Sea region, common southwest (SW) and west (W) winds induce steep waves with shorter wavelengths compared with ocean waves. Thus, with the use of previous SAR sensors (e.g. ENVISAT/ASAR), it was not possible to detect individual waves and retrieve image wave number spectra. Since the year 2007, when TerraSAR-X (TS-X) reached its orbit, high spatial resolution data is available for measuring the sea-state parameters: the individual waves up to 30 m wavelength and their refraction can be distinguished. The main objective of this work was to demonstrate the capability of detecting wave field parameter from (TS-X) imagery in the Baltic Sea. The wave field parameters obtained from the SAR imagery were compared with in situ measurements and the Simulating WAves Nearshore (SWAN) wave model. The comparison of SAR-based wave field information with buoy measurements showed high agreement in case of wave propagation direction (r = 0.95) and wavelength (r = 0.83). A significant correlation is also seen between SWAN- and SAR-derived wave propagation direction (r = 0.87) and wavelengths (r = 0.91). With the case studies, it is shown that SAR data enables one to detect land shadow effects and small-scale wave field variations in the coastal zone. It was shown that SAR data is also valuable for improving and interpreting the wave model results. In consequence of common slanting fetch cases over the Baltic Sea region, it was demonstrated that the peak wave directions differ from the mean wind directions up to 43°.