条带模式合成孔径雷达回波数据的聚束成像算法处理

对条带模式SAR和聚束模式SAR的关系进行了研究,给出了一种如何利用聚束成像算法来处理条带模式SAR的原始回波数据的方法,这种方法基于两种模式成像处理器输入数据的不同特点和Dechirp解调原理,同时使用了频谱扩展的方法。在没有聚束模式SAR原始回波数据的情况下,可使用本文的方法利用条带SAR数据来模拟聚束SAR数据,以便研究聚束成像算法。此外在条带 SAR成像过程中,利用文中给出的算法,可以对某一小的目标区域进行精细成像。也可将此方法用于条带SAR的快视成像中。     

基于迁移学习的SAR目标超分辨重建

针对合成孔径雷达(SAR)目标超分辨重建问题,提出了一种基于迁移学习的超分辨方法。在光学图像梯度域中联合训练超完备字典与稀疏编码映射,利用半耦合字典联系SAR图像与光学图像,寻找SAR图像在半耦合字典下的稀疏编码,并在高分辨率字典下完成重建。结合SAR图像的先验信息,使用正则化方法对SAR目标进行特征增强。所提方法在TerraSAR-X数据和MSTAR数据上进行了仿真实验,重建结果表明,相比目前的插值方法和稀疏表示方法,所提方法空间分辨率可提高0.5~1.5个像素。正则化增强结果表明,引入稀疏先验的正则化增强能够进一步提高空间分辨率并抑制杂波比,最后分析了正则化参数的选取对图像质量的影响。     

星载SAR轨道及姿态误差模型分析

平台轨道及姿态误差模型是星载SAR数据模拟及相应的模拟系统的关键组成部分。简要分析了机载SAR和星载SAR的差异,重点对星载SAR的平台轨道及姿态模型进行了分析,最后对星载SAR回波信号仿真方法进行了分析。     

公开SAR图像目标数据集及其在深度学习中的应用综述

由于合成孔径雷达(SAR)图像可读性较差,所以对其进行目标检测与识别处理的难度也较大.近年来,随着深度学习(DL)方法的不断发展,许多学者将其引入SAR图像目标检测与识别研究中.该类方法以数据为驱动.其中,监督学习方法更以已标注的数据为基础.但是,SAR图像目标的标注通常是昂贵且耗时的.鉴于此,本文对已公开的SAR图像...     

AIS和光学遥感图像引导的星载SAR舰船目标识别网络

星载SAR作为全天时、全天候的感知手段广泛应用于海洋目标识别任务中,由于SAR图像分辨率低、难解译、样本不均衡导致现有单一模态目标识别算法识别精度低。提出了一种AIS和光学遥感图像引导的星载SAR舰船目标识别网络,针对不同模态数据特征维度不同导致难度量问题,利用特征迁移模块在保留各自模态独有特征属性前提下将异构特征映射到共同的空间中度量;针对不同模态不同类别数据存在样本不均衡问题,利用异构特征对齐模块充分挖掘不同模态的互补信息,以细粒度的方式进一步对齐不同模态的异构特征,同时将各个模态的判别性特征作为先验信息迁移至SAR图像模态中。实验部分利用AIS历史数据和光学遥感数据集作为辅助信息,在2个公开的SAR图像舰船目标数据集中进行测试,实验结果表明所提算法通过迁移不同模态信息,有效提升了SAR图像舰船目标的识别准确率。     

基于Gibbs-Markov随机场与连通聚类的SAR图像恢复

在传统的马尔可夫随机场(MRF)的图像建模方法基础上利用合成孔径雷达(SAR)图像的固有特性对Gibbs-MRF模型进行改进复原SAR图像,并进一步提出用数字形态学中连通性理论进行图像分割。在SAR图像像素空间的邻域内,估计最大后验概率(MAP)时引用Gamma分布代替传统的瑞利分布恢复数据,同时利用像素强度值相关性的连通模型将目标较好地提取出来。充分利用了SAR图像的数字形态信息和像素强度之间的相关性,得到了更好的分割效果。仿真实验说明本文方法是有效的。     

基于杂波对消-自聚焦的多通道SAR-GMTI

对超高频(UHF)波段多通道合成孔径雷达(SAR)动目标检测技术进行研究,解决了长相干积累时间导致动目标在方位向散焦严重的问题。采用分块自聚焦技术对多通道SAR地面移动目标指示(GMTI)系统自适应杂波抑制后的SAR图像进行处理,改善杂波抑制后的SAR图像中动目标的聚焦情况,增强动目标与周围剩余杂波的对比度,进而提高恒虚警率(CFAR)检测的性能。与传统杂波抑制后直接进行CFAR检测方法相比较,该方法降低了检测虚警概率。实测数据处理结果显示动目标的信杂比明显提高,动目标方位向聚焦成功,证明了该方法的有效性。     

基于星载视频SAR的海上运动目标监视方法

传统SAR处理方法已无法满足日益复杂的战场环境,在监测、跟踪感兴趣区域内的机动目标和场景变化方面存在不足。针对此情况,提出了一种基于星载视频SAR(Video SAR)的海上运动目标监视方法,通过对目标区域持续观测获得全面的目标态势信息。首先,分析了视频SAR工作原理,采用数据重叠复用的方式来保证SAR视频产品的流畅度;结合图像配准,再利用不同帧图像之间动目标主体位置偏差和阴影变化反演动目标速度,同时改进传统后向投影(Back Projection,BP)算法,使其适用于视频SAR的高效性要求;最后,通过计算机仿真验证了该方法的精确性和有效性。     

一种基于MLS的SAR图像点特征提取方法

针对合成孔径雷达图像点特征提取问题,提出了一种基于MLS的SAR图像点特征提取方法.首先利用提出的基于超像素关联分析的SAR图像分割算法得到二值分割图像,再把该二值图像和SAR图像进行点乘运算,获取到含有强度信息的目标区域,然后采用移动最小二乘法(MLS)对目标区域进行曲面拟合,根据设定的点特征判决规则,最后提取出SAR图像的峰值、脊和谷等多种点特征.基于MSTAR数据的实验结果表明了该方法的有效性和准确性.     

遥感影像中电磁特性数据挖掘

从数据挖掘和遥感信息提取的概念出发,提出了遥感影像中电磁特性数据挖掘的思想,从电子信息装备试验对电磁特性数据的需求和SAR影像数据处理的需求出发,重点完成了基于电磁特性的地物分类和面向对象的遥感影像电磁特性数据挖掘,其中面向对象的遥感影像电磁特性数据挖掘包含遥感影像准备与数据预处理、影像分割、对象的层次结构、规则建立、电磁特性数据获取、信息提取等六个部分,最后把理论方法进行了实践,为大批量获取遥感影像中的电磁特性数据提供了方法支持。     

Modified Frequency Scaling Algorithm for FMCW SAR Data Processing

This paper presents a modified frequency scaling algorithm for frequency modulated continuous wave synthetic aperture radar （FMCW SAR） data processing. The relative motion between radar and target in FMCW SAR during reception and between transmission and reception will introduce serious dilation in the received signal. The dilation can cause serious distortions in the reconstructed images using conventional signal processing methods. The received signal is derived and the received signal in range-Doppler domain is given. The relation between the phase resulting from antenna motion and the azimuth frequency is analyzed. The modified frequency scaling algorithm is proposed to process the received signal with serious dilation. The algorithm can effectively eliminate the impact of the dilation. The algorithm performances are shown by the simulation results.     

调频连续波SAR改进的频率尺度变换算法(英文)

本文提出了一种调频连续波SAR改进的频率尺度变换算法。调频连续波SAR在运动过程中持续不断地发射和接收信号,这种运动导致了回波信号的伸缩,对波前重建产生了严重的影响。推导了回波信号模型,给出了信号的距离-多普勒域表达式,分析了由于天线不断运动而导致的相位变化与方位向频率之间的关系。改进的频率尺度变换算法补偿了这种相位变化,实现了目标的精确成像,仿真结果表明了分析的正确性和算法的有效性。     

Moving target imaging algorithm for SAR data

A digital processing algorithm for fine-resolution imaging of synthetic aperture radar (SAR) moving targets is described. The targets may have any translational and rotational motion components relative to the data collection platform. The algorithm requires the presence of up to three prominent points in the image of the target; the signals from these points provide estimates of the unknown target motion parameters. Phase compensation and data formatting based on these estimates eliminate motion-induced phase errors. This algorithm has been implemented on a VAX computer and used to process both simulated and real SAR data of moving targets. Results obtained using the simulated data are presented     

一种提高距离分辨率的FMCW SAR RD成像算法

调频连续波合成孔径雷达（FMCW SAR）是一种新近提出来的成像雷达体制,它结合调频连续波与合成孔径成像技术,具有体积小、重量轻、成本低、分辨率高等一系列优点。从频谱的角度进行分析,FMCW SAR的距离分辨率取决于频率测量分辨率。文章研究了一种FMCW SAR高距离分辨率成像算法——利用FFT得到差频信号谱峰的粗略范围,再对这一范围进行ChirpZ变换,从而实现距离高精度估计,并且避免了大的计算量。仿真结果表明该方法的有效性。     

聚束SAR扩展Chirp Scaling成像算法.

在合成孔径雷达（SAR Synthetic Aperture Radar)的成像算法中，Chrip Scaling成像算法具有计算效率高的优点，因此得到了较为广泛的应用。详细研究了子孔径扩展Chirp Scaling算法在高分辩率聚束模式SAR中的应用，包括子孔径划分和方位向处理问题，针对A.Moreira等1996年所提算法在处理聚束SAR数据时所产生的问题，给出了经过改进的适合于大斜视角处理的整个计算过程的完整表达式。在给出点目标仿真的同时，利用E-SAR实际数据对述方法进行了验证，结果对具体的兼容条带和聚束两种工作模式的SAR处理机设计具有一定的参考价值。     

Advanced high-order nonlinear chirp scaling algorithm for high-resolution wide-swath spaceborne SAR

Spaceborne Synthetic Aperture Radar (SAR) is a well-established and powerful imaging technology that can provide high-resolution images of the Earth’s surface on a global scale. For future SAR systems, one of the key capabilities is to acquire images with both high-resolution and wide-swath. In parallel to the evolution of SAR sensors, more precise range models, and effective imaging algorithms are required. Due to the significant azimuth-variance of the echo signal in High-Resolution Wide-Swath (HRWS) SAR, two challenges have been faced in conventional imaging algorithms. The first challenge is constructing a precise range model of the whole scene and the second one is to develop an effective imaging algorithm since existing ones fail to process high-resolution and wide azimuth swath SAR data effectively. In this paper, an Advanced High-order Nonlinear Chirp Scaling (A-HNLCS) algorithm for HRWS SAR is proposed. First, a novel Second-Order Equivalent Squint Range Model (SOESRM) is developed to describe the range history of the whole scene, by introducing a quadratic curve to fit the deviation of the azimuth FM rate. Second, a corresponding algorithm is derived, where the azimuth-variance of the echo signal is solved by azimuth equalizing processing and accurate focusing is achieved through a high-order nonlinear chirp scaling algorithm. As a result, the whole scene can be accurately focused through one single imaging processing. Simulations are provided to validate the proposed range model and imaging algorithm.     

基于数值计算的机载SAR空变运动补偿算法

针对机载合成孔径雷达(SAR)高分辨率宽测绘带(HRWS)成像问题,在分析结合两步运动误差补偿的距离徙动算法基础上,提出一种基于数值计算的空变运动误差补偿算法。通过对粗聚焦图像进行分块,在子块的两维波数域进行空变运动补偿,补偿的相位包括方位相位误差、距离相位误差以及方位和距离的耦合相位,因此该算法在复杂航迹、高分辨和宽测绘带情况下仍具有较好的鲁棒性。最后对SAR仿真数据和实测数据进行处理,并与结合两步运动误差补偿的距离徙动算法进行比较,处理结果表明该算法能够更好地补偿空变运动误差。     

An extended chirp scaling algorithm for spaceborne sliding spotlight synthetic aperture radar imaging

A system impulse response with low sidelobes is critical in synthetic aperture radar（SAR） images because sidelobes contribute to noise and interfere with nearby scatterers. However,the conventional tricks of sidelobe suppression are unable to be exactly applied to the case of spaceborne sliding spotlight SAR due to great azimuth shifts in both time and frequency domains. In this paper, an extended chirp scaling algorithm is presented for spaceborne sliding spotlight SAR data imaging. The proposed algorithm firstly uses the spectral analysis（SPECAN） technique to avoid the azimuth spectrum folding effect and then employs the chirp scaling（CS） algorithm to achieve data focusing, i.e., the so-called two-step approach. To suppress the sidelobe level, an efficient strategy for the azimuth spectral weighting which only involves matrix multiplications and short fast Fourier transformations（FFTs） is proposed, which is a post-process executed on the focused SAR image and particularly simple to be implemented. The SAR image processed by the proposed extended CS algorithm is very precise and perfectly phase-preserving. In the end, computer simulation results verify the analysis and confirm the validity of the proposed algorithm.     

SAR data focusing using seismic migration techniques

The focusing of synthetic-aperture-radar (SAR) data using migration techniques quite similar to those used in geophysics is treated. The algorithm presented works in the ω-k_x domain. Because time delays can be easily accommodated with phase shifts that increase linearly with ω, range migration poses no problem. The algorithm is described in plane geometry first, where range migration and phase history can be exactly matched. The effects of the sphericity of the Earth, of the Earth's rotation, and of the satellite trajectory curvature are taken into account, showing that the theoretically achievable spatial resolution is well within the requirements of present day and near future SAR missions. Terrestrial swaths as wide as 100 km can be focused simultaneously with no serious degradation. The algorithm has been tested with synthetic data, with Seasat-A data, and with airplane data (NASA-AIR). The experimental results fully support the theoretical analysis     

一种横向机动弹道下SAR成像算法

针对横向机动弹道下SAR成像回波方位向和距离向严重耦合、弹载SAR平台实时性要求高的特点,提出了一种基于频谱分析的扩展SAR成像算法。首先,以初始距离相同的目标作为成像处理对象,建立了横向机动下弹载SAR成像模型,分析了回波相位和瞬时距离的泰勒展开;然后,采用包含水平面速度和偏航加速度参数的相位因子依次进行距离徙动校正、二次相位补偿和多普勒中心频率补偿,实现了SAR图像的精确聚焦。该算法处理流程简单、实时性高,适合横向机动弹道下的中等分辨率的大斜视成像,给出了算法流程,仿真验证了算法有效性。