40 lines
1.1 KiB
Matlab
Executable File
40 lines
1.1 KiB
Matlab
Executable File
%% 超参数
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global c f_c B T_r N F_s M k lambda
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index = 1:1:N; %产生点向量
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IF_mat = zeros(M,N); %存储带有噪声的中频信号
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t = 0:1/F_s:T_r-1/F_s; %时间向量 确定256个点在一个Tr中的每个时刻
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t = t - T_r/2; %将fc作为中心频率
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dist = 10; %目标距离雷达50m的距离
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t_d = 2 * dist / c; %目标距离雷达的延迟
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velocity = -20; %目标距雷达的相对速度为30m/s
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f_d = 2 * f_c * velocity / c; %多普勒频移
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% f_d = 2 * (f_c - B/2) * velocity / c; %多普勒频移
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scat_coef = 0.8; %回波信号衰减的比例值
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s_T = chirp(t, f_c, t(end), f_c + B);
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pad = round(t_d * F_s);
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s_R = [zeros(1, pad), scat_coef * s_T(1: end - pad)];
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for i = 1: M
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s_T = 1*exp((1i*2*pi)*(f_c*(t+i*T_r)+k/2*t.^2)); %发射信号
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s_R = scat_coef*exp((1i*2*pi)*((f_c-f_d)*(t-t_d+i*T_r)+k/2*(t-t_d).^2)); %回波信号
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IF = s_T .* conj(s_R);
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% SNR = 10;
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% IF_Noise = awgn(IF, SNR, 'measured');
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IF_Noise = IF;
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IF_mat(i, :) = IF_Noise;
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end
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save('Ego_vehicle_ksy.mat','IF_mat');
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% figure;
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% subplot(211);
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% plot(t, s_T);
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% ylim([-1.3, 1.3]);
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%
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% subplot(212);
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% plot(t, s_R);
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% ylim([-1.3, 1.3]);
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