3D Target Localization Based on FrFT from Spaceborne Curve SAR

Synthetic aperture radar(SAR)three-dimensional(3D)imaging technology can reconstruct the complete structure of observed targets and has been a hot topic.Compared with tomographic SAR,array interferometric SAR,and circular SAR,curve SAR can use less data to achieve 3D positioning of targets.Most existing algorithms for estimating Doppler frequency modulation(FM)rate are based on sub aperture partitioning,resulting in low computational efficiency.To address this,this article establishes a target height estimation model,which reflects the relation-ship between the height and the residual Doppler FM rate for spaceborne curve SAR.Then,a fast SAR 3D localization processing flow based on fractional Fourier transform(FrFT)is proposed.Experimental verification demonstrates that this method can estimate the Doppler FM of the target column by column,and the 3D position error for non-overlapping targets is controlled within 1 m.For overlapping points with an intensity ratio greater than 1.5,the root mean square error(RMSE)of the estimation results is around 5 m.If the separation between overlapping points is greater than 35 m,the RMSE decreases to approximately 2 m.

Airborne sparse flight array SAR 3D imaging based on compressed sensing in frequency domain

In airborne array synthetic aperture radar(SAR), the three-dimensional(3D) imaging performance and cross-track resolution depends on the length of the equivalent array. In this paper, Barker sequence criterion is used for sparse flight sampling of airborne array SAR, in order to obtain high cross-track resolution in as few times of flights as possible. Under each flight, the imaging algorithm of back projection(BP) and the data extraction method based on modified uniformly redundant arrays(MURAs) are utilized to obtain complex 3D image pairs. To solve the side-lobe noise in images, the interferometry between each image pair is implemented, and compressed sensing(CS) reconstruction is adopted in the frequency domain. Furthermore, to restore the geometrical relationship between each flight, the phase information corresponding to negative MURA is compensated on each single-pass image reconstructed by CS. Finally,by coherent accumulation of each complex image, the high resolution in cross-track direction is obtained. Simulations and experiments in X-band verify the availability.

Precise Three-Dimensional Deformation Retrieval in Large and Complex Deformation Areas via Integration of Offset-Based Unwrapping and Improved Multiple-Aperture SAR Interferometry:Application to the 2016 Kumamoto Earthquake

Conventional synthetic aperture radar(SAR)interferometry(InSAR)has been successfully used to precisely measure surface deformation in the line-of-sight(LOS)direction,while multiple-aperture SAR interferometry(MAI)has provided precise surface deformation in the along-track(AT)direction.Integration of the InSAR and MAI methods enables precise measurement of the two-dimensional(2D)deformation from an interferometric pair;recently,the integration of ascending and descending pairs has allowed the observation of precise three-dimensional(3D)deformation.Precise 3D deformation measurement has been applied to better understand geological events such as earthquakes and volcanic eruptions.The surface deformation related to the 2016 Kumamoto earthquake was large and complex near the fault line;hence,precise 3D deformation retrieval had not yet been attempted.The objectives of this study were to①perform a feasibility test of precise 3D deformation retrieval in large and complex deformation areas through the integration of offset-based unwrapped and improved multiple-aperture SAR interferograms and②observe the 3D deformation field related to the 2016 Kumamoto earthquake,even near the fault lines.Two ascending pairs and one descending the Advanced Land Observing Satellite-2(ALOS-2)Phased Array-type L-band Synthetic Aperture Radar-2(PALSAR-2)pair were used for the 3D deformation retrieval.Eleven in situ Global Positioning System(GPS)measurements were used to validate the 3D deformation measurement accuracy.The achieved accuracy was approximately 2.96,3.75,and 2.86 cm in the east,north,and up directions,respectively.The results show the feasibility of precise 3D deformation measured through the integration of the improved methods,even in a case of large and complex deformation.

机载SAR影像时空模型重构因子及3D特征提取

时空模型有助于人们获取类似于真实世界的时间及空间信息 ,对于城市工程设计、灾害预防决策及军事应用具有重要意义。本文探讨了机载SAR影像重构时空模型的潜力及方法 ,研究了时空模型重构因子、基于机载SAR影像的建筑物、植被的三维提取 。

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.

结合三维电磁散射模型和深度学习的SAR目标识别框架设计

不断提高合成孔径雷达(SAR)图像目标识别能力对于全天时、全天候战场情报侦察具有重要意义。近年来,深度学习模型在SAR目标识别领域得到了广泛应用和验证,但由于SAR图像样本往往十分有限,模型的适应性受到一定制约。提出结合三维电磁散射模型和深度学习的SAR目标识别框架,充分运用三维电磁散射模型在目标SAR数据生成以及物理属性描述方面的优势,提升深度学习模型的分类可靠性和适应性。

DOWNWARD LOOKING SPARSE LINEAR ARRAY 3D SAR IMAGING ALGORITHM BASED ON BACK-PROJECTION AND CONVEX OPTIMIZATION

Downward Looking Sparse Linear Array Three Dimensional SAR(DLSLA 3D SAR) is an important form of 3D SAR imaging, which has a widespread application field. Since its practical equivalent phase centers are usually distributed sparsely and nonuniformly, traditional 3D SAR algorithms suffer from low resolution and high sidelobes in cross-track dimension. To deal with this problem, this paper introduces a method based on back-projection and convex optimization to achieve 3D high accuracy imaging reconstruction. Compared with traditional SAR algorithms, the proposed method sufficiently utilizes the sparsity of the 3D SAR imaging scene and can achieve lower sidelobes and higher resolution in cross-track dimension. In the simulated experiments, the reconstructed results of both simple and complex imaging scene verify that the proposed method outperforms 3D back-projection algorithm and shows satisfying cross-track dimensional resolution and good robustness to noise.

纳尔科3D TRASAR技术赢得美国总统绿色化学挑战奖

本刊讯（胡晓红报道）日前，纳尔科公司所开发的3DTRASAR冷却水技术赢得了2008年美国总统绿色化学挑战奖。颁奖仪式干6月24日在华盛顿国家科学院举行，纳尔科在“绿色反应条件”奖中胜出。

A Downsampled SAR-BM3D Despeckling Approach for Single-Look SAR Images in High Resolution

SAR-BM3D is one of the state of the art despeckling algorithms for SAR images. However, when tackling with high resolution SAR images, it often has an unsatisfying despeckling performance in the homogeneous smooth regions, together with a high time complexity. In this paper, a novel downsampled SAR-BM3D despeckling approach combined with edge compensation is proposed. The proposed algorithm consists of two steps. First, despeckle the image which is a downsampled version of original image with SAR-BM3D. Then, compensate edges in each level when upsampling. This approach not only utilizes the good ability of feature preservation, but also improves performance of smoothing homogenous regions. When it comes to high resolution SAR images, the efficiency can be raised by six to seven times, compared to original SAR-BM3D. Experiments on simulated and real SAR images show that the proposed method reaches a high level in terms of visual quality and act more efficiently.

3D TRASAR~技术在循环水冷却系统中的应用

介绍了Gulf Coast石化厂采用纳尔科3D Trasar循环冷却水管理技术,成功解决其循环水冷却系统关键换热器的腐蚀与结垢控制问题,提高了设备及工厂运行的可靠性。

3D-TRASAR技术在硝酸循环水处理系统的应用

循环水处理系统有时会偏离正常轨道而进入苛刻的运行状态。在苛刻运行状态下，循环水处理系统的任务就是在于减少系统结垢、腐蚀和生物黏泥等危害，使系统正常运行。循环水处理系统一旦发生问题，采取必要的措施后，

纳尔科3D TRASAR技术赢得美国总统绿色化学挑战奖

纳尔科公司（纽约证交所代码：NLC）3D TRASAR冷却水技术赢得了2008年美国总统绿色化学挑战奖。颁奖仪式已于6月24日在华盛顿国家科学院举行，纳尔科在“绿色反应条件”奖中胜出。

纳尔科3D TRASAR技术赢得美国总统绿色化学挑战奖

美国伊利诺伊州内珀维尔纳尔科公司所开发的3DTRASAR冷却水技术赢得了2008年美国总统绿色化学挑战奖。颁奖仪式于6月24日在华盛顿国家科学院举行，纳尔科在“绿色反应条件”奖中胜出。

改善制冷机运行状况纳尔科3D TRASAR技术可为药厂降低能耗并提高运行效率

药品生产厂家会将制冷机用于冷却生产工艺．满足暖通空调负荷、维持GMP生产车间的湿度和环境温度。冷冻水流量和温度是确保生产稳定和工厂运行的关键因素。制冷机是主要的耗能设备，其运行效率是影响制药厂能耗的重点。本文将以某药厂的制冷机系统改造为例阐述纳尔科3D TRASAR技术的优势。

一种基于深度学习的SAR城市建筑区域叠掩精确检测方法

建筑物叠掩检测在城市三维合成孔径雷达(3D SAR)成像流程中是至关重要的步骤,其不仅影响成像效率,还直接影响最终成像的质量。目前,用于建筑物叠掩检测的算法往往难以提取远距离全局空间特征,也未能充分挖掘多通道SAR数据中关于叠掩的丰富特征信息,导致现有叠掩检测算法的精确度无法满足城市3D SAR成像的要求。为此,该文结合Vision Transformer (ViT)模型和卷积神经网络(CNN)的优点,提出了一种基于深度学习的SAR城市建筑区域叠掩精确检测方法。ViT模型能够通过自注意力机制有效提取全局特征和远距离特征,同时CNN有着很强的局部特征提取能力。此外,该文所提方法还基于专家知识增加了用于挖掘通道间叠掩特征和干涉相位叠掩特征的模块,提高算法的准确率与鲁棒性,同时也能够有效地减轻模型在小样本数据集上的训练压力。最后在该文构建的机载阵列SAR数据集上测试,实验结果表明,该文所提算法检测准确率达到94%以上,显著高于其他叠掩检测算法。

EFFICIENT STRIP-MODE SAR RAW SIGNAL SIMULATION OF MIXED TARGETS BASED ON ACCURATE 2-D SPECTRUM

An accurate and efficient Synthetic Aperture Radar(SAR)raw data generator is of considerable value for testing system parameters and verifying imaging algorithms.Nevertheless,the existing simulator cannot exactly handle the case of the fast moving targets in high squint geometry.As for the issue,the analytical expression for the two Dimensional(2-D)signal spectrum of moving targets is derived and a fast raw echo simulation method is proposed in this study.The proposed simulator can accommodate the moving targets in the high squint geometry,whose processing steps of the simulation are given in detail and its computational complexity is analyzed.The simulation data for static and moving targets are processed and analyzed,and the results are given to validate the effectiveness of the proposed approach.

新体制SAR三维成像技术研究进展

常规SAR成像,平台沿直线飞行,形成直线型合成孔径,仅能获取2维图像,即3维空间中的观测场景在斜距-方位平面的2维投影,图像具有叠掩、透视缩短、阴影等畸变现象。SAR 3维成像突破了斜距-方位2维频率信息获取,能够获取第3维频率信息,实现3维分辨,可获得观测场景的散射中心在3维空间中的分布,从而解决叠掩问题,消除透视缩短、顶底倒置等几何形变现象,更直观地描述客观场景,已成为国际研究热点。该文介绍SAR 3维成像的概念和主要观测模式,分析该领域国内外研究现状和进展,重点阐述作者所在研究团队的SAR3维成像研究进展,最后对SAR 3维成像技术进行总结和展望。

地球同步轨道圆迹SAR研究

该文介绍了地球同步轨道圆迹合成孔径雷达(Geosynchronous Circular SAR,Geo-CSAR)的概念,通过设计同步轨道的轨道参数,可以形成近圆的卫星相对地球轨迹,使SAR载荷的凝视成像模式成为可能,实现对地的大面积定点连续观测以及真3维信息获取;研究分析了Geo-CSAR的成像能力,指出其在瞬时覆盖度、连续观测范围及3维精确定位方面,具有现有低轨星载SAR无法比拟的优势,是实现全球不间断覆盖的有效途径之一,在军事侦察、灾害监测方面具有重要的应用前景。

基于压缩感知的下视三维SAR成像新方法

下视3维合成孔径雷达(Synthetic Aperture Radar,SAR)可对平台正下方目标进行3维重构,具有广阔的应用前景。为有效减少线阵天线所需阵元数,该文提出了一种基于稀疏阵列的下视3维SAR成像方法。为了抑制稀疏阵列导致的栅瓣效应,该方法结合压缩感知(Compressed Sensing,CS)理论,实现对下方3维目标的成像。分析了稀疏阵列配置对稀疏信号处理的影响以及3维成像采用稀疏信号处理的可行性。最后通过仿真实验验证了该文分析的正确性及算法的有效性。

单幅高分辨率SAR图像建筑物三维模型重构

提出了一种利用高分辨率SAR图像进行建筑物提取和三维重构的方法.首先,分析了高分辨率SAR图像建筑物产生的电磁散射的类型,给出了不同类型散射区域的后向散射计算方法,并在此基础上给出了一种利用建筑物三维CAD模型进行SAR建筑物特征区域图像仿真的方法;其次,给出了利用建筑物的二次散射结构确定建筑物底部轮廓位置和方向的方法,并提出了一种基于分布密度函数差异的仿真图像迭代匹配方法,进行建筑物高度的反演.仿真SAR图像后向散射系数用来划分建筑物不同的散射区域,通过计算特征区域之间的分布密度函数差异,以取得最大匹配度值的仿真图像对应的检验高度作为建筑物的反演高度;最后,选用了两幅不同屋顶类型的实际机载高分辨率SAR图像进行建筑物提取和三维重构实验,试验结果较为理想,验证了所提方法的可行性和有效性.