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sar-signalprocessing's Introduction

SAR-SignalProcessing

合成孔径雷达算法与实现

Catalogue

  • Chapter_Two

    • Figure2.2 包含数据扭曲和旋转的傅里叶变换对

    • Figure2.3 矩形和sinc函数的傅里叶便函

    • Figure2.7 以两个不同采样率对300Hz的正弦波采样来说明混叠现象

    • Figure2.8 采样引起的频谱平移(实信号)

    • Figure2.9 采样引起的频谱平移(复信号)

    • Figure2.11 不同$\beta$值的Kaiser窗形状

    • Figure2.12 不同Kaiser窗的展宽和峰值旁瓣比

    • Figure2.14 使用sinc函数插值的图

    • FIgure2.15 Kaiser窗加权后的sinc函数,$\beta=2.5$

  • Chapter_Three

    • Figure3.1 线性调频脉冲的相位和频率

    • Figure3.2 线性调频脉的复频谱

    • Figure3.3 不同TBP值的离散傅里叶变换频谱变化

    • Figure3.4 过采样率$\alpha_{os}$在频谱中引起的能量间隙

    • Figure3.5 匹配滤波器输出的3dB分辨率的测量

    • Figure3.6 基带线性调频信号的匹配滤波

    • Figure3.7 存在噪声时基带线性调频信号的匹配滤波

    • Figure3.8 非基带线性调频信号的匹配滤波

    • Figure3.9 匹配滤波后的信号频谱

    • Figure3.10 Kaiser窗在时域和频域中的实现形式

    • Figure3.11 方式2生成的频域匹配滤波器

    • Figure3.12 方式3生成的频域匹配滤波器

    • Figure3.13 通过压缩目标的位置来说明基带信号的弃置区和TA值

    • Figure3.14 当$\beta=2.5$时的IRW、PSLR、ISLR与QPE之间的关系(结果并不吻合)

    • Figure3.15 旁瓣位置不同,而脉冲响应相似时的情况

  • Chapter_Four

  • Chapter_Five

    • Figure5.3 离散脉冲对方位信号的采样造成的方位混叠

    • Figure5.4 由方位chirp信号混叠造成的方位模糊

    • Figure5.5 斜视角为零和非零时的多普勒中心

    • Figure5.12 距离徙动的线性分量和二次分量

    • Figure5.13 目标轨迹在方位时域和方位频域的变化趋势

    • Figure5.16 零斜视角下单个点目标的时域性质

    • Figure5.17 零斜视角并且为正扫频下单个点目标的方位频谱

    • Figure5.18 非零斜视角下单个点目标的时域性质

    • Figure5.19 非零斜视角并且为正扫频下单个点目标的方位频谱

Notes:

  • .mlx实时脚本文件为练习时使用!

  • arrow.m是一个非常牛逼的画箭头函数!

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