Open Radar Datasets.zip，这是一份不错的文件

Numerous books have been written on Radar Systems and Radar Applications. A limited set of these books provides companion software. There is need for a comprehensive reference book that can provide the reader with hands-on-like experience. The ideal radar book, in my opinion, should serve as a conclusive, detailed, and useful reference for working engineers as well as a textbook for students learning radar systems analysis and design. This book must assume few prerequisites and must stand on its own as a complete presentation of the subject. Examples and exercise problems must be included. User friendly software that demonstrates the theory needs to be included. This software should be reconfigurable to allow different users to vary the inputs in order to better analyze their relevant and unique requirements, and enhance understanding of the subject.

ofdm与ocdm雷达通信一体化模糊函数比较（Integrated radar and communication OFDM s

对雷达信号处理中的恒虚警检测和动目标显示进行了仿真，对需要理解恒虚警检测的同学很有帮助

雷达波形设计matlab代码雷达生成检测 在MATLAB中实现RADAR目标生成和检测 雷达项目 1.FMCW波形设计 R = 110 ; % initial distance of the target v = - 20 ; % speed of the target fc = 77e9 ; % Frequency of operation R_max = 200 ; % Max Range resolution = 1 ; % Range Resolution c = 3e8 ; % Speed of Light v_max = 100 ; % Max Velocity %% FMCW Waveform Generation % Design the FMCW waveform by giving the specs of each of its parameters. % Calculate the Bandwidth (B), Chirp Time (Tchirp) and slope (slope) of the FMCW % chirp using the requirem

MIMO Radar Signal Processing

Principles of Modern Radar Advanced Techniques IEEE

雷达系统用于通过在自由空间中传输电磁波来检测物体。 它们在期望的回波信号极有可能干扰其他来源的信号的环境中运行。 这些信号包括杂波和干扰信号。 干扰器是一种在雷达环境中连续发射宽带无线电信号，从而使接收器充满噪声或虚假信息的设备。 因此，总的接收信号具有三个分量，即来自目标，杂波和干扰的回波相结合，即它是三维信号。 常规信号处理技术的使用是不可取的，因为它们无法将所需的回声信号与其他分量分开，因为不知道接收信号中存在的这些分量的统计信息。 在机载监视雷达中，必须解决此问题，因为它们必须在多个干扰环境中识别和定位目标。 空时自适应技术（STAP）是空间和时间滤波的组合，可以消除干扰信号并识别慢速移动的目标。 这些技术在角域和多普勒域中对信号进行滤波，以抑制不需要的信号。 本文对时空自适应编码技术进行了理论研究，并介绍了STAP算法的MATLAB实现。 SMI，DPCA和ADPCA，以抑制接收脉冲中的杂波和干扰干扰。

径向 极坐标中的RADAR和LIDAR数据的NetCDF CF约定。 概述 [概述文档]（./docs/CfRadialOverview.20170201.pdf） [AGU海报2016]（./presentations/AGU_2016.poster_IN23A-1761.cfradial.pdf） [Earthcube研讨会]（./reports/Workshop.20160525.md）| 时间轴-CfRadial版本1-经典模型 日期 活动 2016/08/01 [版本1.4]（./current_docs/CfRadialDoc.v1.4.20160801.pdf） 2013/07/01 [版本1.3]（./old_docs/CfRadialDoc.v1.3.20130701.pdf） 2011/06/07 [版本1.2]（./old_docs/CfRadialDo

The paper presents an improved method for the deinterleaving of radar signals, based on a time of arrival analysis and the use of the sequential difference histogram (SDIF) for determining the pulse repetition interval (PRI). The optimal detection threshold in the SDIF histogram is derived, which greatly contributes to the efficiency of the algorithm. The algorithm is applied to classic, frequency-agile and staggered PRI radar signals. It is shown that the new method is very successful in high-pulse-density radar environments and for complex signal types. Special attention is given to an application of this method to the multiple-parameter deinterleaving algorithm.