论文原文《A Tomographic Formulation of Spotlight-Mode Synthetic Aperture Radar》，BP算法的出处

目标中结构的微运动可能会在反向合成Kong径雷达（ISAR）成像中引入微多普勒（mD）效应，这会污染经典测距多普勒算法（RDA）的主体图像。 本文提出了一种新的微运动目标成像方法，该方法在范围轮廓中的元素之前分配了一个分层的贝叶斯方法，目的是促进稀疏性并在缓慢的时间维度上保持连续性模式。为克服后验分布的棘手性，Gibbs利用采样器实现贝叶斯推断。然后，可以根据条件后验分布的期望估计距离分布，然后在交叉压缩后获得清晰的ISAR图像。实验结果验证了该方法的性能。

主要是讲他的 Braitenberg 小车，千辛万苦才搞到的，淘宝也没有卖的，感谢舍友。只设置一积分 下载，如果后续变多，那是xxdn系统的问题。

Synthetic Chinese Data数据集百度云盘

matlab自己编写的polar format algorithm for synthetic aperture radar

A static-mode synthetic aperture imaging ladar (SAIL) in which the target and carrying platform are kept still during the collection process is proposed and demonstrated. A target point of 0.5 mm \times 0.5 mm and a two-dimensional (2D) object are reconstructed in the experiments, in which an optical collimator with a focal length of 10 m is used to simulate the far-field condition. The achieved imaging resolution is in agreement with the theoretical design. The static-mode down-looking SAIL has

SynthPop SynthPop使用高斯系脉生成表格综合数据。 动机 我们想对{ X ， y }的联合分布建模，以便可以绘制更多样本。 从统计上相同的分布中获取更多样本可以（a）减少过度拟合或（b）保留隐私（通过创建具有相同统计属性的数据集而不会揭示底线）。 例子 您可以从以下分布中获得一些样本。 借助SynthPop，您可以通过（a）将高斯连接数拟合到这些观测值，以及（b）从该多元高斯中抽取样本来从该分布中生成更多样本。 from SynthPop import Copula data = np . load ( "data.npy" ) # ground truth of 100 samples Generator = Copula () Generator . fit ( data ) # fit a Guassian so it has a similar distr

Matlab编写的地震合成记录，学习使用

《Spotlight Synthetic Aperture Radar Signal Processing Algorithms》原始文件超过60M，没有办法上传，故分为两部分，这是第二部分。 这本书是1995年的经典书，虽然标题是聚束SAR信号处理算法，但是里面讲述的经典内容不仅仅适用于聚束SAR，而是对更广阔的SAR也是通用的。 这本书讲述了：合成孔径雷达基础；聚束SAR和极化格式算法；数字极化格式处理；相位误差；自聚焦技术；处理设计例程；SAR系统性能；聚束SAR处理应用；RMA算法；CS算法等内容。

Principles of Synthetic Aperture Radar Imaging: A System Simulation Approach demonstrates the use of image simulation for SAR. It covers the various applications of SAR (including feature extraction, target classification, and change detection), provides a complete understanding of SAR principles, and illustrates the complete chain of a SAR operation. The book places special emphasis on a ground-based SAR, but also explains space and air-borne systems. It contains chapters on signal speckle, radar-signal models, sensor-trajectory models, SAR-image focusing, platform-motion compensation, and microwave-scattering from random media. While discussing SAR image focusing and motion compensation, it presents processing algorithms and applications that feature extraction, target classification, and change detection. It also provides samples of simulation on various scenarios, and includes simulation flowcharts and results that are detailed throughout the book.