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。

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。

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。

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。

天基逆合成孔径雷达脉内脉间运动补偿及高分辨成像

近年来,太空态势感知在军用和民用领域都得到了越来越多的关注。天基逆合成孔径雷达(SBISAR)能够实现对空间目标的高分辨成像,支撑部件提取、姿态估计、类型识别等后续任务,是太空态势感知的重要工具。然而,在SBISAR成像场景下,平台与空间机动目标间存在复杂的相对高速运动,传统距离-多普勒成像方法不再适用,必须进行运动补偿。本文针对高速径向速度下传统“停—走—停”模型失效、长相干积累时间内目标转速不一致的两个典型误差来源,分别设计了脉内运动及脉间运动补偿算法。首先,建立SBISAR成像的信号模型。然后,基于最小熵准则构建参数估计代价函数,通过估计目标对应回波信号的调频率,构造补偿项进而实现脉内补偿。同时,建立图像熵代价函数,在估计转动参数后,完成对目标转动的空变相位补偿。所提算法有效解决了天基高速机动背景下传统距离-多普勒成像方法的距离像展宽、方位散焦问题,实现了SBISAR对空间目标的高分辨成像。通过基于仿真数据的实验分析,验证了所提算法的有效性。

星载InSAR方位向逐行的顺轨有效基线计算方法

本文开展了星载干涉合成孔径雷达(Interferometric synthetic aperture radar,InSAR)顺轨有效基线计算方法的改进研究。首先利用多项式拟合卫星轨道方程,使用相干系数法计算待配准图像对的像元偏移量,通过建立顺轨有效基线与方位向行号的函数关系式获得逐行有效基线,解决了在整幅图像使用固定有效基线带来的误差问题。通过TanDEM-X/TerraSAR-X实测干涉数据对本文的改进方法进行了应用和检验,同时针对所使用干涉图像对的特殊线性关系建立了快捷实用的线性方程。通过在整幅图像上精细化使用顺轨有效基线会对诸如海流反演方面有效提高反演精度。

空间目标ISAR图像三维基元表示方法

空间卫星目标的逆合成孔径雷达(ISAR)图像由离散的散射点构成,具有弱纹理、高动态、非连续的特性,造成传统算法对空间目标ISAR图像进行三维重建时,得到的点云结果稀疏,无法覆盖目标整体外形轮廓,进而导致难以精确提取目标结构、姿态参数。针对上述问题,并考虑到空间目标通常由特定模块化部件组成的特点,该文提出一种从空间目标ISAR图像中抽取参数化基元来表示其三维结构的方法。首先利用能量累积算法从ISAR图像中得到目标的稀疏点云,进而利用参数化基元对点云进行拟合,最后将基元投影至ISAR成像平面,并最大化与目标图像的相似度来优化基元参数,得到最优的目标三维基元表示。相比于传统点云三维重建,该方法能够获得对目标三维结构更完整的描述,且所得到的基元参数即代表目标的姿态及结构,可直接支撑后续的目标识别、分析研判等任务。仿真实验证明该方法能够根据ISAR序列图像,有效实现对空间目标的三维表示。

高频地波雷达编队目标分辨方法

由于方位分辨性能受限和多普勒模糊问题,高频地波雷达(HFSWR)难以分辨编队内的子目标。该文将逆合成孔径原理应用于HFSWR,提出横向距离成像方法。该方法首先在运动补偿处理中消除径向运动分量、保留旋转运动,实现聚焦的多普勒谱,并分辨多个子目标。然后,横向距离定标处理将频率坐标转化为横向距离,进而估计子目标间的间距。其中,由最小熵准则来估计径向速度和径向加速度,由分段数字波束形成来估计旋转角度。为了在有限积累时间条件下提升分辨效果,采用基于数据复用方式的重叠相干积累来增加扫频周期数。仿真实验表明,所提方法的理论分辨率在几百米至几千米范围内,运动补偿和横向距离定标实现了单纵队的分辨及其间距估计,重叠积累具有缩窄主峰和降低旁瓣水平的效果。

结合最近邻图模型的稀疏ISAR成像方法

逆合成孔径雷达(Inverse Synthetic Aperture Radar,ISAR)稀疏成像方法可提供图像对比度高、旁瓣干扰少的成像结果 .稀疏成像以场景或目标散射率分布具有稀疏性为前提,待成像目标场景的稀疏特性决定了最终成像质量. ISAR目标场景的自然稀疏特性着重刻画点状特征,变换域稀疏表示可增强目标图像的纹理等通用特征.通过学习获得的稀疏变换字典,可自适应于待成像的ISAR目标场景,找到面向ISAR目标图像块的特有稀疏表示.但是,图像块的特有稀疏表示中忽略了待成像目标场景中目标的几何特征信息.最近邻图模型可建立给定数据的几何特征描述算子,刻画出给定数据的几何特征信息.本文利用最近邻图模型来刻画待成像目标场景中目标的几何特征信息,并映射到待成像目标场景的特有稀疏表示中;提出结合最近邻图模型的ISAR稀疏成像方法,用于不同类别实测ISAR数据成像.相比已有的ISAR稀疏成像方法,所提成像方法可获得目标轮廓更清晰的成像结果,成像所需时间平均减少10.4%.