PHASE AUTOFOCUSING ALGORITHM FOR COMPRESSED INVERSE SYNTHETIC APERTURE RADAR IMAGING

As same as the conventional inverse synthetic aperture radar（ISAR）, the compressed ISAR also requires the echo signal based motion compensation, which consists of the range alignment and the phase autofoeusing. A phase autofocusing algorithm for compressed ISAR imaging is presented. In the algorithm, phase autofocusing for the sparse ISAR echoes is accomplished using the eigenvector method. Experimental results validate the effectiveness of the algorithm.

A COMPARISON OF SOME ELECTRONIC COUNTERMEASURES ON INVERSE SYNTHETIC APERTURE RADAR (ISAR)

Inverse Synthetic Aperture Radar (ISAR) is an important means for target classification, recognition, identification and many other military applications. A simulation model of ISAR system is established after analyzing the principle of ISAR imaging, and then several ECM (Electronic Counter Measurement) techniques are studied. Simulation experiments are done on the basis of such research. The experimental result of the research can be used for ECM equipment.

Micro-motion effect in inverse synthetic aperture radar imaging of ballistic mid-course targets

For ballistic mid-course targets,in addition to constant orbital motion,the target or any structure on the target undergoes micro-motion dynamics,such as spin,precession and tumbling.The micro-motion characteristics of the ballistic mid-course targets were discussed.The target motion model and inverse synthetic aperture radar(ISAR) imaging model for this kind of targets were built.Then,the influence of micro-motion on ISAR imaging based on the established imaging model was presented.The computer simulation to get mid-course target echoes from static darkroom electromagnetic scattering data based on the established target motion model was realized.The imaging results of computer simulation show the validity of ISAR imaging analysis for micro-motion targets.

Inverse synthetic aperture radar range profile compensation of plasma-sheath-enveloped reentry object

The scattering points in a plasma sheath characterized with coupled velocities can cause pulse compression mismatching,which results in displacement and energy diffusion in the onedimension range profile.To solve this problem,we deduce the echo model of the plasma-sheathenveloped reentry object.By estimating the coupled velocities,we propose a compensation method to correct the defocus of an inverse synthetic aperture radar(ISAR)image in range dimension to improve the quality of the ISAR images.The simulation results suggest that the echoes from different regions of the surface of the reentry object have various coupling velocities,and the higher the coupled velocity,the more serious the displacement and energy diffusion in the range dimension.Our proposed method can correct the range dimension aberration.Two measurement metrics were used to evaluate the improvement of the compensation method.

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.

Compressive Sensing Inverse Synthetic Aperture Radar Imaging Based on Gini Index Regularization

In compressive sensing(CS) based inverse synthetic aperture radar(ISAR) imaging approaches, the quality of final image significantly depends on the number of measurements and the noise level. In this paper, we propose an improved version of CSbased method for inverse synthetic aperture radar(ISAR) imaging. Different from the traditional l1 norm based CS ISAR imaging method, our method explores the use of Gini index to measure the sparsity of ISAR images to improve the imaging quality. Instead of simultaneous perturbation stochastic approximation(SPSA), we use weighted l1 norm as the surrogate functional and successfully develop an iteratively re-weighted algorithm to reconstruct ISAR images from compressed echo samples. Experimental results show that our approach significantly reduces the number of measurements needed for exact reconstruction and effectively suppresses the noise. Both the peak sidelobe ratio(PSLR) and the reconstruction relative error(RE) indicate that the proposed method outperforms the l1 norm based method.

A new autofocus method for inverse synthetic aperture radar——Local dominant scatterer synthesis

Motion compensation is a key and difficult step in inverse synthetic aperture radar (ISAR) . The calibration of initial phase errors, which is well known as autofocus, requires very high precision, so it determines the quality of the reconstructed image to a great extent. A new autofocus method called the local dominant scatterer synthesis (LDSS) is presented. It has the capability to sufficiently reduce the errors induced by clutter and noise, and the advantage of having wide applications. Experiments of real measured data have shown its effectiveness.

Multi-static InISAR imaging for ships under sparse aperture

This paper concentrates on super-resolution imaging of the ship target under the sparse aperture situation.Firstly,a multi-static configuration is utilized to solve the coherent processing interval(CPI)problem caused by the slow-speed motion of ship targets.Then,we realize signal restoration and image reconstruction with the alternating direction method of multipliers(ADMM).Furthermore,we adopt the interferometric technique to produce the three-dimensional(3D)images of ship targets,namely interferometric inverse synthetic aperture radar(InISAR)imaging.Experiments based on the simulated data are utilized to verify the validity of the proposed method.

Coastal bathymetry inversion using SAR-based altimetric gravity data:A case study over the South Sandwich Island

The global bathymetry models are usually of low accuracy over the coastline of polar areas due to the harsh climatic environment and the complex topography.Satellite altimetric gravity data can be a supplement and plays a key role in bathymetry modeling over these regions.The Synthetic Aperture Radar(SAR)altimeters in the missions like CryoSat-2 and Sentinel-3A/3B can relieve waveform contamination that existed in conventional altimeters and provide data with improved accuracy and spatial resolution.In this study,we investigate the potential application of SAR altimetric gravity data in enhancing coastal bathymetry,where the effects on local bathymetry modeling introduced from SAR altimetry data are quantified and evaluated.Furthermore,we study the effects on bathymetry modeling by using different scale factor calculation approaches,where a partition-wise scheme is implemented.The numerical experiment over the South Sandwich Islands near Antarctica suggests that using SARbased altimetric gravity data improves local coastal bathymetry modeling,compared with the model calculated without SAR altimetry data by a magnitude of 3:55 m within 10 km of offshore areas.Moreover,by using the partition-wise scheme for scale factor calculation,the quality of the coastal bathymetry model is improved by 7.34 m compared with the result derived from the traditional method.These results indicate the superiority of using SAR altimetry data in coastal bathymetry inversion.

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。

基于最大对比度的联合相位误差校正方法

针对高分辨率逆合成孔径雷达(ISAR)成像过程中,因目标转动所引入的转动相位误差无法被忽略,以及由于转动相位误差使得传统平动相位误差校正方法性能严重下降的问题,提出了一种基于最大对比度的联合相位误差校正的方法,可同时校正残余的平动相位误差和转动相位误差,进一步提高成像的质量。首先利用传统的运动补偿方法对回波信号进行处理,其次根据最大对比度准则,将相位误差校正问题转化为最大对比度优化问题,最后利用改进的拟牛顿算法进行求解。该方法能使高分辨率ISAR进行精准成像,且所得图像聚焦效果良好。通过对仿真数据和实测数据的处理,验证了文中方法的有效性。

2023年积石山Ms6.2级地震InSAR同震形变探测与断层滑动分布反演

2023年12月18日,甘肃省临夏回族自治州积石山县发生了Ms6.2级地震,地震灾害损失显著高于同震级地震,查明其同震形变场与断层滑动分布特征,有助于揭示此次地震灾害损失严重的原因。利用Sentinel-1卫星升、降轨雷达影像,采用合成孔径雷达干涉技术获取了本次地震的同震形变场,进而基于Okada弹性位错模型,确定了本次地震的震源参数,并基于分布式滑动模型反演了本次地震断层面上的滑动分布。结果表明,积石山地震为逆冲型地震,升、降轨同震形变场沿视线向最大形变量分别为7.1 cm和7.8 cm,断层最大滑动量为0.31 m,主要集中在地下0~8 km。与2019年6月17日四川长宁Ms 6.0级地震对比发现,长宁地震地表最大形变量为8 cm,断层最大滑动量为0.38 m,均大于积石山地震,推测积石山地震灾害损失严重的主要原因为震区居民房屋相对集中、房屋抗震性能差和黄土区场地地震波放大效应等。

一种联合TDCM和PFA的空间目标大转角ISAR成像方法

空间目标态势感知是当前航天技术领域的研究热点,逆合成孔径雷达(Inverse Synthetic Aperture Radar, ISAR)是空间目标感知的一种有效手段。为了得到利于目标鉴别的高分辨二维ISAR图像,需要通过增大积累转角来提高方位向分辨率。但是,随着转角的增大,平动与转动之间的耦合增大,使得传统的先平动补偿、后利用转动成像的两步式成像方法不再适用。本文提出了一种结合时域信号共轭相乘(Time Domain Conjugate Multiplication, TDCM)处理与极坐标格式算法(Polar Format Algorithm, PFA)的成像算法,首先利用雷达回波的二维相干性,通过TDCM处理进行平动粗补偿,然后借助PFA的插值操作校正大转角引起的散射点越分辨单元走动(Motion Through Resolution Cell, MTRC)并估计目标相对转动参数。通过迭代处理,持续对平动和转动参数进行优化,提升运动补偿效果。仿真验证了所提成像算法的有效性,与传统算法相比,成像聚焦性更好。

吸波材料覆盖直升机强散射源RCS缩减分析

针对武装直升机的宽带隐身问题,提出利用射线追踪和逆合成孔径雷达(Inverse synthetic aperture radar,ISAR)成像确定直升机强散射源位置的方法,形成电磁超构材料和磁性材料一体化设计直升机部分强散射源的隐身设计构想,并计算分析了两款隐身材料加载后对整机隐身效果的影响。首先,分析等效媒质理论、射线追踪与ISAR成像原理。然后,通过射线追踪以及ISAR成像的计算,精确且直观地捕获强散射源部位。最后,给出了两款材料的反射系数并分析加载直升机后单站雷达散射截面(Radar cross section,RCS)变化。计算结果表明,两种不同类型隐身材料覆盖直升机强散射源部位后可以达到局部角域范围内RCS缩减的目的,为隐身材料和直升机蒙皮及旋翼的融合设计提供了参考。

类别数据流和特征空间双分离的类增量学习算法

针对类增量学习(CIL)中的灾难性遗忘问题,该文提出一种不同类的数据流和特征空间双分离的类增量学习算法。双分离(S2)算法在1次增量任务中包含2个阶段。第1个阶段通过分类损失、蒸馏损失和对比损失的综合约束训练网络。根据模块功能对各类的数据流进行分离,以增强新网络对新类别的识别能力。通过对比损失的约束,增大各类数据在特征空间中的距离,避免由于旧类样本的不完备性造成特征空间被新类侵蚀。第2个阶段对不均衡的数据集进行动态均衡采样,利用得到的均衡数据集对新网络进行动态微调。利用实测和仿真数据构建了一个飞机目标高分辨率距离像增量学习数据集,实验结果表明该算法相比其它几种对比算法在保持高可塑性的同时,具有更高的稳定性,综合性能更优。

基于时空注意力-Seq2Seq网络的ISAR包络对齐方法

包络对齐是逆合成孔径雷达(Inverse Synthetic Aperture Radar,ISAR)成像中平动补偿处理的第一步,包络对齐的精度对于方位聚焦和成像质量具有重要影响。针对稀疏孔径和低信噪比条件下传统的包络对齐算法性能显著降低的问题,本文提出一种基于时空注意力-Seq2Seq网络的包络对齐方法。该网络模型以门控循环单元为编码解码单元,针对点目标距离像包络的能量分布特征对空间注意力机制进行改进后,添加时间和空间两维注意力机制形成对ISAR距离像回波包络进行对齐的能力。数据生成方面,基于电磁波仿真参数和目标运动仿真参数进行成像模拟仿真构造了ISAR回波数据集,经过8倍插值后输入网络进行训练,使网络学习到从未对齐回波到对齐回波的映射关系。所提方法以离线训练代替在线相关计算,融合了Seq2Seq模型在处理序列到序列问题上的结构优势、时间注意力机制在捕捉长期依赖关系和空间注意力机制在提取区域特征上的突出能力,实现了稀疏孔径和低信噪比条件下对距离-慢时间域ISAR回波的自动对齐。通过向训练好的时空注意力-Seq2Seq网络输入未对齐的回波序列,网络可以在不改变回波相位结构的前提下自动实现包络对齐。仿真和实测数据对齐结果表明,和传统的包络对齐方法相比,所提方法在稀疏孔径和低信噪比条件下优势明显,在欠采样率为50%、信噪比为0 dB条件下对雅克-42飞机实测回波数据的包络对齐实验中,该方法将循环移位误差由39、26减小至6,将成像结果的图像熵由4.58、4.22减小至1.71,验证了其良好性能。

以全球导航卫星系统为辐射源的前向散射雷达发展综述

前向散射雷达(FSR)可获得高水平雷达截面积(RCS)的特性使其在反隐身中占据重要地位。利用全球导航卫星系统(GNSS)作为辐射源,具有全天时全天候全地域覆盖的优势,通过部署多个接收节点可构建地面/海上/空中目标监视网络。该文针对基于GNSS的FSR发展现状,从目标检测、目标参数估计、阴影逆合成孔径雷达(SISAR)成像及目标分类识别等方面对关键技术和现存问题进行概述,并从组网探测、多目标定位、布站优化和极化信息获取等方面对基于GNSS的FSR发展趋势提出展望。

一种基于时间编码超表面的ISAR干扰方法

时间编码超表面具备对电磁波的调制能力,从而有效改变反射电磁波的特性,达到改变目标特性的目的。基于超表面的调控特性,设计了一种周期时间编码的逆合成孔径雷达(Inverse Synthetic Aperture Radar,ISAR)干扰方法。分析了时间编码超表面的相位调制机理,建立了时间编码序列模型,通过设计优化时间编码序列的相关参数,形成对雷达在距离向上的欺骗干扰。通过理论推导,分析了时间编码调制参数对假目标位置、幅度等的影响。仿真实验结果表明,该方法可以根据信号参数生成数量可控、位置可变的虚假目标,距离向干扰范围扩展至2倍以上,从而实现不同的干扰效果,在电子对抗等方面具有较高的应用价值。

微波光子W波段宽带雷达成像技术研究

W波段逆合成孔径雷达(inverse synthetic aperture radar,ISAR)具有成像分辨率高、成像距离远、体积小、重量轻等特点,适用于机载、弹载、星载等应用领域,是雷达系统中的一个重要的研究方向。微波光子技术由于具有高频、大带宽、低传输损耗等优势,是克服传统雷达面临“电子瓶颈”效应的主要手段。本文提出一种基于微波光子技术实现的W波段调频信号体制ISAR成像系统。在发射端,使用微波光子倍频技术实现了瞬时带宽为8 GHz的W波段线性调频(linearly frequency-modulated,LFM)信号生成。在接收端,基于微波光子去斜技术实现回波信号去斜处理。ISAR成像仿真结果表明,不同姿态下的目标轮廓清晰可辨。

基于迭代自适应的短孔径逆合成孔径雷达成像方法

针对合成孔径时间短、逆合成孔径雷达数据成像质量差的问题,本研究提出一种基于迭代自适应恢复缺失数据(missing-data iterative adaptive processing approach,MIAA)的短孔径数据的逆合成孔径雷达(inverse synthetic aperture radar,ISAR)超分辨率成像方法。该方法利用MIAA对ISAR回波数据的方位向进行扩展,从而增加数据的方位向长度,提高成像质量。仿真和实测均表明该方法能够有效扩展回波数据的方位向长度,提高短孔径条件下的成像质量。