登录
首页 » matlab » 雷达信号处理

雷达信号处理

于 2021-01-27 发布
0 258
下载积分: 1 下载次数: 10

代码说明:

说明:  包含雷达信号处理的基本流程与操作规范的matlab代码示例,内容选摘如下: 一、脉冲压缩 窄带(或某些中等带宽)的匹配滤波: 相关处理,用FFT数字化执行,即快速卷积处理,可以在基带实现(脉冲压缩) 快速卷积,频域的匹配滤波 脉宽越小,带宽越宽,距离分辨率越高; 脉宽越大,带宽越窄,雷达能量越小,探测距离越近;(Matlab code examples including the basic flow and operation specifications of radar signal processing are as follows:)

文件列表:

雷达信号处理基本操作规范.doc, 43008 , 2021-01-27
雷达信号处理基本流程.doc, 336430 , 2021-01-27

下载说明:请别用迅雷下载,失败请重下,重下不扣分!

发表评论

0 个回复

  • mile5.m
    2012美国建模大赛B题代码,M奖队伍代码(2012 U.S. modeling contest code of Problem B, the M-Prize team code)
    2012-06-02 10:32:56下载
    积分:1
  • coaxial
    Coaxial-Mesh generation-Finite element method-elctromagnetic-KNTU-
    2013-07-12 04:26:03下载
    积分:1
  • IMM
    1.IMM.m 主要功能: (1)IMM算法的实现; (2)画出目标轨迹与利用IMM算法跟踪目标的轨迹; (3)画出位置误差与速度误差; (4)画出模型混合概率图。 2.Target_track.m 主要功能: 实现目标轨迹的产生。 3.Model_mix.m 主要功能: 实现IMM算法下,各模型的估计融合。 4.Kalman.m 主要功能: 实现模型的条件滤波,以及似然函数的输出。(1.IMM.m main functions: (1) IMM algorithm implementation (2) Draw the locus and utilization of IMM target tracking algorithm goals (3) shows the position error and speed error Mixed (4) Draw model probability plots. 2.Target_track.m main functions: to produce the target locus. 3.Model_mix.m main functions: IMM algorithm, it is estimated each model integration. 4.Kalman.m main functions: the model filter condition, and it seems natural function of the output.)
    2020-07-02 07:40:02下载
    积分:1
  • OFDMWLANssimulation
    OFDM在无线局域网中应用,包括编码,信道估计和同步算法(OFDM in Wireless LAN applications, including coding, channel estimation and synchronization algorithms)
    2009-04-06 19:41:26下载
    积分:1
  • icalab
    矩阵实验室的内容,对于学习盲源分析的同学有好处(Matrix content of the laboratory for the analysis of blind source learning students will benefit)
    2007-09-15 10:12:21下载
    积分:1
  • matlab_envelope-_code
    信号包络求法,此法为hilbert变换和微分法的matlab源程序,有注释;(envelope curve calculation)
    2013-01-22 17:28:21下载
    积分:1
  • OMP24x12
    利用空调调制信号本身固有的稀疏特性和压缩感知信号重构算法的MATLAB代码。(The use of air conditioning modulation signals inherent characteristics and compressed sensing sparse signal reconstruction algorithm MATLAB code.)
    2016-06-18 20:26:56下载
    积分:1
  • Face_Recognition_Using_Laplacianfaces
    face recognition system in matlab...
    2009-09-07 04:33:08下载
    积分:1
  • xiaobosuanfa
    采样频率 fs=10000 轴承外环故障信号 fid=fopen( bearingout.dat , r ) 故障 N=1024 xdata=fread(fid,N, int16 ) fclose(fid) xdata=(xdata-mean(xdata))/std(xdata,1) 时域波形 figure(1) plot(1:N,xdata) xlabel( 时间 t/n ) ylabel( 电压 V/v ) db10小波进行4层分解 一维小波分解 [c,l] = wavedec(xdata,4, db10 ) 重构第1~4层细节信号 d4 = wrcoef( d ,c,l, db10 ,4) d3 = wrcoef( d ,c,l, db10 ,3) d2 = wrcoef( d ,c,l, db10 ,2) d1 = wrcoef( d ,c,l, db10 ,1) ( Sampling frequency fs = 10000 bearing outer ring fault signal fid = fopen (' bearingout.dat' , ' r' ) failure N = 1024 xdata = fread (fid, N, ' int16' ) fclose (fid ) xdata = (xdata-mean (xdata))/std (xdata, 1) time-domain waveform figure (1) plot (1: N, xdata) xlabel (' Time t/n' ) ylabel ( ' voltage V/v' ) db10 wavelet decomposition 4 layer one-dimensional wavelet decomposition [c, l] = wavedec (xdata, 4, ' db10' ) 1 ~ 4 reconstructed detail signal d4 = wrcoef (' d' , c, l, ' db10' , 4) d3 = wrcoef (' d' , c, l, ' db10' , 3) d2 = wrcoef (' d' , c, l, ' db10' , 2) d1 = wrcoef (' d' , c, l, ' db10' , 1) )
    2011-05-21 16:48:36下载
    积分:1
  • invertA.m
    Given a matrix the result its the Invert matrix
    2011-07-21 17:55:17下载
    积分:1
  • 696518资源总数
  • 105877会员总数
  • 14今日下载