diff --git a/Random PRI/Main.m b/Random PRI/Main.m
new file mode 100644
index 0000000..7280702
--- /dev/null
+++ b/Random PRI/Main.m	
@@ -0,0 +1,41 @@
+clc; clear; close all;
+
+parameters;
+
+global trail_times;
+
+[s_T_narrow, A] = narrow_signal_model(t, 1);
+
+A = A / 10;
+
+AH = A';
+
+H0 = [];
+for T = 1: trail_times
+    x = zeros(10, 1);
+    % x(4) = 0.8;
+    y = A * x;
+    y_noise = awgn(y, 15);
+    
+    x_hat = AH * y_noise;
+
+    H0 = [H0 x_hat'];
+end
+
+H1 = [];
+for T = 1: trail_times
+    x = zeros(10, 1);
+    x(4) = 0.8;
+    y = A * x;
+    y_noise = awgn(y, 15);
+    
+    x_hat = AH * y_noise;
+
+    H1 = [H1 x_hat(4)];
+end
+
+% figure; histfit(real(H0));
+% figure; histfit(real(H1));
+
+figure;
+plot()
diff --git a/Random PRI/narrow_signal_model.m b/Random PRI/narrow_signal_model.m
new file mode 100644
index 0000000..4169139
--- /dev/null
+++ b/Random PRI/narrow_signal_model.m	
@@ -0,0 +1,25 @@
+function [s_T_narrow, A_narrow] = narrow_signal_model(t, betas_narrow)
+    global f_c N_narrow N FIGURE N_wide numP f_s K_chirp T_r;
+
+    tt = 0: 1/f_s: numP * T_r - 1/f_s;
+
+    % 使用等效散射系数生成窄带情况信号模型
+    s_T_narrow = zeros(1, N * numP);
+    for j = 1: numP
+        idx = ((j-1) * N + (1:N_narrow));
+        tp = idx / f_s;
+        s_T_narrow(1, idx) = exp(1j * 2 * pi * (f_c * tp + 0.5 * K_chirp * tp .^ 2));
+    end
+
+    % s_T_narrow = exp(1j .* 2 .* pi .* f_c .* t);
+    s_R_narrows = zeros(N_narrow, N * numP);
+    for i = 1: N_narrow
+        p = i * (N_wide / N_narrow);
+        s_R_narrows(i, :) = betas_narrow * [zeros(1, p), s_T_narrow(1: end-p)];
+    end
+    
+    A_narrow = s_R_narrows';
+    if FIGURE
+        subplot(2, 1, 1); plot(tt, real(s_T_narrow));
+        subplot(2, 1, 2); plot(tt, real(s_R_narrows(1, :)));
+    end
\ No newline at end of file
diff --git a/Random PRI/parameters.m b/Random PRI/parameters.m
new file mode 100644
index 0000000..0f1d817
--- /dev/null
+++ b/Random PRI/parameters.m	
@@ -0,0 +1,59 @@
+global bandwidth T_p f_s T_s K_chirp f_c PRF T_r numP t tP c N M R_0...
+    delta_R_wide delta_R_narrow N_wide N_narrow ranges_wide...
+    ranges_narrow betas_wide FIGURE K_wide K_narrow trail_times...
+    method N_high TEST lambda tau iter_max noise_sigma FAR_N FAR_M noise_sigma_2 DEBUG_LEVEL...
+;
+
+f_c = 10e9; % X wave
+bandwidth = 100e6;
+T_p = 1e-5;
+f_s = 2 * bandwidth;
+T_s = 1 / f_s;
+K_chirp = bandwidth / T_p;
+T_r = T_p * 10;
+PRF = 1 / T_r;
+
+numP = 10;
+
+t = 0: 1 / f_s: T_r - 1 / f_s;
+tP = 0: 1 / f_s: T_r * numP - 1 / f_s;
+
+c = 3e8;        % 光速
+
+N = length(t);
+N_high = T_p * f_s;
+M = round(T_p * bandwidth);
+R_0 = 0;
+delta_R_wide = c ./ 2 ./ bandwidth;
+delta_R_narrow = T_p .* c ./ 2;
+N_wide = 100;
+N_narrow = round(N_wide / M);
+
+% alert(N > N_narrow);
+
+ranges_wide = R_0 + (0:N_wide) * delta_R_wide; % [1000, 4000]
+ranges_narrow = R_0 + (0:N_narrow) * delta_R_narrow; % [1000, 4000]
+betas_wide = linspace(1, 0.1, N_wide) + 1j * linspace(0.1, 1, N_wide);
+
+K_wide = round(N_wide / 10);
+K_narrow = round(K_wide / 10);
+
+FIGURE = false;
+trail_times = 5000;
+% method = "debiased_LASSO";
+% method = "LASSO";
+% method = "BP";
+method = "cVAMPro";
+TEST = false;
+
+lambda = 0.01;
+tau = 1e-6;
+iter_max = 1000;
+
+noise_sigma = 0.1;
+noise_sigma_2 = 0.1;
+
+FAR_N = 480;
+FAR_M = 10;
+
+DEBUG_LEVEL = 1;