Modulated-ISRJ rejection using online dictionary learning for synthetic aperture radar imagery

In electromagnetic countermeasures circumstances,synthetic aperture radar(SAR)imagery usually suffers from severe quality degradation from modulated interrupt sampling repeater jamming(MISRJ),which usually owes considerable coherence with the SAR transmission waveform together with periodical modulation patterns.This paper develops an MISRJ suppression algorithm for SAR imagery with online dictionary learning.In the algorithm,the jamming modulation temporal properties are exploited with extracting and sorting MISRJ slices using fast-time autocorrelation.Online dictionary learning is followed to separate real signals from jamming slices.Under the learned representation,time-varying MISRJs are suppressed effectively.Both simulated and real-measured SAR data are also used to confirm advantages in suppressing time-varying MISRJs over traditional methods.

An empirical method for joint inversion of wave and wind parameters based on SAR and wave spectrometer data

Synthetic aperture radar(SAR)and wave spectrometers,crucial in microwave remote sensing,play an essential role in monitoring sea surface wind and wave conditions.However,they face inherent limitations in observing sea surface phenomena.SAR systems,for instance,are hindered by an azimuth cut-off phenomenon in sea surface wind field observation.Wave spectrometers,while unaffected by the azimuth cutoff phenomenon,struggle with low azimuth resolution,impacting the capture of detailed wave and wind field data.This study utilizes SAR and surface wave investigation and monitoring(SWIM)data to initially extract key feature parameters,which are then prioritized using the extreme gradient boosting(XGBoost)algorithm.The research further addresses feature collinearity through a combined analysis of feature importance and correlation,leading to the development of an inversion model for wave and wind parameters based on XGBoost.A comparative analysis of this model with ERA5 reanalysis and buoy data for of significant wave height,mean wave period,wind direction,and wind speed reveals root mean square errors of 0.212 m,0.525 s,27.446°,and 1.092 m/s,compared to 0.314 m,0.888 s,27.698°,and 1.315 m/s from buoy data,respectively.These results demonstrate the model’s effective retrieval of wave and wind parameters.Finally,the model,incorporating altimeter and scatterometer data,is evaluated against SAR/SWIM single and dual payload inversion methods across different wind speeds.This comparison highlights the model’s superior inversion accuracy over other methods.

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 crosspolarization coupled-parameters ocean(C-3 PO) 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.

Modified Omega-K algorithm for processing helicopter-borne frequency modulated continuous waveform rotating synthetic aperture radar data

With appropriate geometry configuration, helicopter- borne rotating synthetic aperture radar （ROSAR） can break through the limitations of monostatic synthetic aperture radar （SAR） on forward-looking imaging. With this capability, ROSAR has extensive potential applications, such as self-navigation and self-landing. Moreover, it has many advantages if combined with the frequency modulated continuous wave （FMCW） technology. A novel geometric configuration and an imaging algorithm for helicopter-borne FMCW-ROSAR are proposed. Firstly, by per- forming the equivalent phase center principle, the separated trans- mitting and receiving antenna system is equalized to the case of system configuration with antenna for both transmitting and receiving signals. Based on this, the accurate two-dimensional spectrum is obtained and the Doppler frequency shift effect in- duced by the continuous motion of the platform during the long pulse duration is compensated. Next, the impacts of the velocity approximation error on the imaging algorithm are analyzed in de- tail, and the system parameters selection and resolution analysis are presented. The well-focused SAR image is then obtained by using the improved Omega-K algorithm incorporating the accurate compensation method for the velocity approximation error. FJnally, correctness of the analysis and effectiveness of the proposed al- gorithm are demonstrated through simulation results.

Speckle suppression in synthetic aperture radar ocean internal solitary wave images with curvelet transform

This paper proposes a speckle-suppression method for ocean internal solitary wave（ISW） synthetic aperture radar（SAR） images by using the curvelet transform.The band-shaped signatures of ocean ISWs in SAR images show obvious scale and directional characteristics.The curvelet transform possesses a very high scale and directional sensitivity.Therefore,the curvelet transform is very efficient in analyzing wave signals in SAR images.A noisy ocean ISW SAR image can be decomposed at different scales,directions,and positions using the curvelet transform.The information of the ISWs is centralized in the curvelet coefficients of certain directions under certain scales,whereas the speckle noise is distributed in every scale and direction.By manipulating the curvelet coefficients,the signals of the ISWs can be extracted from the noisy SAR image.Finally,the speckle noise is suppressed and the ISW feature is enhanced by adding the signals of the ISWs back to the original SAR image.Experiments demonstrate the effectiveness of this method.

Simulation of Raw Signal for Spaceborne Synthetic Aperture Radar(SAR)

The study on simulation of raw signal for spaceborne SAR aims at producing raw signal to test and evaluate the system and imaging algorithm. The model used for simulation includes a distributed target model, a platform and target geometry model, and a mathematical architecture used for generation of raw echo. Two aspects are stressed, one is the effects of earth ellip soid and attitude errors on radar impulse respense, the other is quick generation of range migration in azimuth frequency domain. Prescribed statistical characteristics of the model account for a realistic speckle of actual image. Finally, examples are given to validate the simulation of raw signal for spaceborne SAR.

An Information Theory Approach to the Data Compression and Imaging System for Synthetic Aperture Radar （SAR）

Synthetic aperture radar (SAR) is portrayed as a multiple access channel. An information theory approach is applied to the SAR imaging system, and the information content about a target that can be extracted from its radar image is evaluated by the average mutual information measure. A conditional (transition) probability density function (PDF) of the SAR imaging system is derived by analyzing the system and a closed form of the information content is found. It is shown that the information content obtained by the SAR imaging system from an independent sample of echoes will decrease and the total information content obtained by the SAR imaging system will increase with an increase in the number of looks. Because the total average mutual information is also used to define a measure of radiometric resolution for radar images, it is shown that the radiometric resolution of a radar image of terrain will be improved by spatial averaging. In addition, the imaging process and the data compression process for SAR are each treated as an independent generalized communication channel. The effects of data compression upon radiometric resolution for SAR are studied and some conclusions are obtained.

Carbon stock estimation by dual-polarized synthetic aperture radar (SAR) and forest inventory data in a Mediterranean forest landscape

Forest ecosystems play a crucial role in mitigating global climate change by forming massive carbon sinks. Their carbon stocks and stock changes need to be quantified for carbon budget balancing and international reporting schemes. However, direct sampling and biomass weighing may not always be possible for quantification studies conducted in large forests. In these cases, indirect methods that use forest inventory information combined with remote sensing data can be beneficial. Synthetic aperture radar (SAR) images offer numerous opportunities to researchers as freely distributed remote sensing data. This study aims to estimate the amount of total carbon stock (TCS) in forested lands of the Kizildag Forest Enterprise. To this end, the actual storage capacities of five carbon pools, i.e. above- and below-ground, deadwood, litter, and soil, were calculated using the indirect method based on ground measurements of 264 forest inventory plots. They were then associated with the backscattered values from Sentinel-1 and ALOS-2 PALSAR-2 data in a Geographical Information System (GIS). Finally, TCS was separately modelled and mapped. The best regression model was developed using the HH polarization of ALOS-2 PALSAR-2 with an adjusted R^(2) of 0.78 (p < 0.05). According to the model, the estimated TCS was about 2 Mt for the entire forest, with an average carbon storage of 133 t ha^(−1). The map showed that the distribution of TCS was heterogenic across the study area. Carbon hotspots were mostly composed of pure stands of Anatolian black pine and mixed, over-mature stands of Lebanese cedar and Taurus fir. It was concluded that the total carbon stocks of forest ecosystems could be estimated using appropriate SAR images at acceptable accuracy levels for forestry purposes. The use of additional ancillary data may provide more delicate and reliable estimations in the future. Given the implications of this study, the spatiotemporal dynamics of carbon can be effectively controlled by forest management when coupled with easily accessible space-borne radar data.

A novel synthetic aperture radar scattering model for sea surface with breaking waves

In this study a novel synthetic aperture radar(SAR)scattering model for sea surface with breaking waves is proposed.Compared with existing models,the proposed model considers an empirical relationship between wind speed and wave breaking scattering to present the contribution of wave breaking.Moreover,the scattering weight factor p,and wave breaking rate q,are performed to present the contribution of the quasi-specular scattering term,Bragg scattering term,and wave breaking scattering term to the total scattering from the sea surface.To explore the modeling accuracy of sea-surface scattering,a simulated normalized radar cross-section(NRCS)and measured NRCS are compared.The proposed model generated the simulated NRCS and a matching GF-3 dataset was used for the measured NRCS.It was revealed that the performance of the VV polarization of our model was much better than that of HH polarization,with a correlation of 0.91,bias of-0.14 dB,root mean square error(RMSE)of 1.26 dB,and scattering index(SI)of-0.11.In addition,the novel model is explored and compared with the geophysical model of CMODs and satellite-measured NRCS from GF-3 SAR wave mode imagery.For an incidence angle 40°–41°,the relationship between the NRCS and wind speed,relative wind direction is proposed.As with the SAR-measured NRCS,the performance of VV polarization was much better than HH polarization,with a correlation of 0.99,bias of-0.25 dB,RMSE of 0.64 dB,and SI of-0.04.

IMAGING ANALYSIS OF FREQUENCY MODULATION CONTINUOUS WAVE SYNTHETIC APERTURE RADAR IN NEAR RANGE MODE

Frequency-Modulation Continuous-Wave Synthetic Aperture Radar(FMCW SAR)has shown great potential in the applications of civil and military fields because of its easy deployment and low cost.However,most of these work and analysis are concentrated on airborne FMCW SAR,where the characteristics of the imaging geometry and signal are much similar to that of traditional pulsed-SAR.As a result,a series of test campaigns of automobile-based FMCW SAR were sponsored by Institute of Electronics,Chinese Academy of Sciences(IECAS)in the autumn of 2012.In this paper,we analyze the imaging issues of FMCW SAR in automobile mode(named as near range mode),where a vehicle is used as moving platform and a large looking angle is configured.The imaging geometry and signal properties are analyzed in detail.We emphasize the difference of the near range mode from the traditional airborne SAR mode.Based on the analysis,a focusing approach is proposed in the paper to handle the data focusing in the case.Simulation experiment and real data of automobile FMCW SAR are used to validate the analysis.

CROSS-TRACK THREE APERTURES MILLIMETER WAVE SAR SIDE-LOOKING THREE-DIMENSIONAL IMAGING

The airborne cross-track three apertures MilliMeter Wave (MMW) Synthetic Aperture Radar (SAR) side-looking three-Dimensional (3D) imaging is investigated in this paper. Three apertures are distributed along the cross-track direction, and three virtual phase centers will be obtained through one-input and three-output. These three virtual phase centers form a sparse array which can be used to obtain the cross-track resolution. Because the cross-track array is short, the cross-track resolution is low. When the system works in side-looking mode, the cross-track resolution and height resolution will be coupling, and the low cross-track resolution will partly be transformed into the height uncertainty. The beam pattern of the real aperture is used as a weight to improve the Peak to SideLobe Ratio (PSLR) and Integrated SideLobe Ratio (ISLR) of the cross-track sparse array. In order to suppress the high cross-track sidelobes, a weighting preprocessing method is proposed. The 3D images of a point target and a simulation scene are achieved to verify the feasibility of the proposed method. And the imaging result of the real data obtained by the cross-track three-baseline MMW InSAR prototype is presented as a beneficial attempt.

Ocean wave diffraction in near-shore regions observed by Synthetic Aperture Radar

在近岸的 andnear 岛区域的海浪衍射的观察和分析与合成的孔雷达(SAR ) 数据被执行，用一个优化检索方法命名 parameterized 第一猜测的光谱检索方法。从 ERS-SAR 和 ENVISAT-ASAR 图象检索的结果显示出那，在由陆路掩盖的区域突出，长波的精力被 10%-20% 减少并且长波的繁殖方向由于地形学的效果被改变。在在岛后面的盲区，海浪能宣传海岸而不是对海岸线垂直由 SAR 图象出现。

The efifect of wave breaking on surface wave imaging by Synthetic Aperture Radar

海浪在雷达的 backscatteringcross 节和灯传递函数(MTF ) 上作为 non-Bragg 机制碎的效果基于 Braggresonance 理论和参量的方法被调查。结果证明波浪在 backscattering 剖面图上碎的另外的效果除了小事件角度 ofVV 是不超过 20% 极化电磁(e.m ) 飘动但是为 HH 是重要的极化的 e.m 波浪。Breakingwaves 在 tilt 调整 MTF 的模量导致增加并且越大风速，越 faster 增加。为大事件角度，没有波浪为 VV 极化碎，有波浪碎的 tilt 调整 MTF 的模量为到那的 HH 极化和途径与事件角度快速减少。当考虑波浪碎和增加比为 VV 极化为 HH 极化是更大的时，水动力学 MTF 增加 30%-60% 。

微波视觉与SAR图像智能解译

高分辨率雷达成像技术和人工智能、大数据技术的快速发展,有力促进了雷达图像智能解译技术的进步。由于雷达传感器本身的特殊性和电磁散射成像物理的复杂性,雷达图像的解译缺乏光学图像的直观性,准确迅速识别分类的需求对雷达图像解译提出了迫切的挑战。在借鉴人脑光视觉感知机理和计算机视觉图像处理相关技术基础上,进一步融合电磁散射物理规律及其雷达成像机理,我们提出发展微波域雷达图像解译的“微波视觉”的新交叉领域研究。该文介绍微波视觉的概念与内涵,提出微波视觉认知模型,阐述其基础理论问题与技术路线,最后介绍了作者团队在相关问题上的初步研究进展。

方位向调制干扰对高分宽幅多通道SAR的影响

多通道合成孔径雷达(synthetic aperture radar,SAR)能够利用方位向多通道重构处理去除多普勒模糊,获得高分宽幅SAR图像。针对此特殊的多通道重构处理方式,研究了传统SAR方位向调制干扰对高分宽幅多通道SAR的影响,包括多普勒调制干扰和脉冲延迟转发干扰两种类型的方位向调制干扰方式,为高分宽幅多通道SAR干扰决策提供理论基础。理论分析指出,多普勒调制干扰信号经成像处理后将在方位向生成等间隔分布的虚假目标,并且幅度受与多普勒调制频率相关的正弦函数和匹配滤波损失联合调制;而脉冲延迟转发干扰信号在成像后将只有单个干扰目标出现,且目标的方位位置仅与延迟的脉冲数有关。仿真实验验证了理论分析的正确性。

基于长短路融合及数据平衡的SAR船舶检测算法

针对SAR图像检测船舶任务中的目标小、近岸样本目标检测困难等问题,文章提出一种名为长短路特征融合网络(Long and Short path Feature Fusion Network,LSFF-Net)的船舶检测网络。该网络通过长短路特征融合模块有效协调了大目标与小目标检测,避免小目标特征信息的丢失。网络中应用结构重参数化结构提高了模块学习能力。为了满足多尺度目标检测,加入特征金字塔网络,融合多尺度特征。为了应对近岸样本目标检测,设计数据重分配算法,提高了对近岸样本目标的检测精度。实验结果表明:在公开数据集检测时,算法的平均精度(Average Precision,AP)达到97.50%,优于主流目标检测算法。该方法为提高SAR图像中小目标和近岸样本目标检测精度提供了新的实现方案。

多域特征引导的无监督SAR图像舰船检测方法

如何在合成孔径雷达(SAR)图像标注样本有限的条件下,提升舰船检测性能一直是SAR图像处理中的热点问题。本文提出一种多域特征引导的无监督域适应方法,将知识从有标注的源域(光学图像)转移到未标注的目标域(SAR图像),降低对标记SAR图像数据依赖。同时,设计了频域转换模块、注意力区域增强模块和自适应权重模块来缩小光学、SAR图像域之间的域差距,提高源域与目标域特征对齐效率,增强网络在挑战性样本下的特征迁移能力。在公开发布的数据集上进行了大量实验。结果表明:所提的模块较基础模型AP50提升10%,总体性能优于其他先进的方法。

考虑速度聚束效应的SAR海浪成像仿真方法

针对合成孔径雷达(SAR)海浪成像仿真技术对于速度聚束效应的考虑不充分,仿真数据无法准确反映实际SAR数据的问题,建立一种充分考虑速度聚束效应的SAR海浪成像仿真方法并进行了实验验证。计算了SAR图像强度的概率密度分布的仿真结果与理论结果之间的均方误差(MSE),在风速分别为5、10和15 m/s时,考虑速度聚束效应前、后比对结果的MSE分别为0.1012、0.1576、0.0556与0.0179、0.0314、0.0088。仿真结果表明,所提SAR海浪成像仿真方法有效提高了仿真数据的准确性,对SAR海浪成像的应用具有一定实用价值。

基于遗传算法的无人机载穿墙三维SAR航迹规划方法

传统手持或车载穿墙雷达由于架设高度受限,无法对城市高层建筑内部目标进行透视成像,无人机载穿墙雷达具有灵活机动、高效便捷、无高度限制等优势,可对城市高层楼宇进行大范围三维穿透探测。三维层析合成孔径雷达(SAR)成像广泛采用多基线扫描模式,以获得高度向高分辨能力,但存在高度向空域欠采样导致的栅瓣问题。对此,该文提出一种基于遗传算法的无人机载穿墙三维SAR航迹规划方法,通过非均匀化飞行航迹,削弱周期性的雷达回波能量叠加,从而抑制栅瓣、实现更优的成像质量。该算法结合飞行距离与无人机载穿墙雷达成像质量的内在关系,建立了无人机航迹规划代价函数;利用遗传算法对3种典型的无人机飞行轨迹关键控制点进行基因编码,并进行基因杂交、变异等以优化种群与个体;最终通过最小化代价函数,分别筛选出3种典型飞行模式下的最优飞行航迹。仿真和实测数据的三维成像结果表明:相较于传统等间距多基线飞行模式,所提方法显著抑制了成像目标的栅瓣效应;此外,无人机斜线飞行的航迹长度明显缩短,提高了无人机载穿墙SAR成像效率。

SAR图像飞机目标智能检测识别技术研究进展与展望

合成孔径雷达(SAR)采用相干成像机制,具有全天时、全天候成像的独特优势。飞机目标作为一种典型高价值目标,其检测与识别已成为SAR图像解译领域的研究热点。近年来,深度学习技术的引入,极大提升了SAR图像飞机目标检测与识别的性能。该文结合团队在SAR图像目标特别是飞机目标的检测与识别理论、算法及应用等方面的长期研究积累,对基于深度学习的SAR图像飞机目标检测与识别进行了全面回顾和综述,深入分析了SAR图像飞机目标特性及检测识别难点,总结了最新的研究进展以及不同方法的特点和应用场景,汇总整理了公开数据集及常用性能评估指标,最后,探讨了该领域研究面临的挑战和发展趋势。