基于MATLAB的CFAR检测仿真+仿真操作录像

clc; clear; close all; warning off; addpath(genpath(pwd)); cfar = phased.CFARDetector('NumTrainingCells',200,'NumGuardCells',50,'Method','CA'); % Expected probability of False Alarm (no units) pfa_expected = 1e-2; % Setting parameters for CFAR Detector object cfar.ThresholdFactor = 'Auto'; cfar.ProbabilityFalseAlarm = pfa_expected; % Assume 10dB SNR ratio npower = db2pow(-10); % Total number of points Total_points = 1e3; %Number of trials done Num_of_Trials = 1; % Total cells in window Num_of_Cells = 251; % Index of Cell Under test Cut_Id = 126; % To obtain the detection threshold cfar.ThresholdOutputPort = true; % Seed to generate random number rs = RandStream('mt19937ar','Seed',2010); %Modeling Received Signal rsamp = randn(rs,Total_points,1)+1i*randn(rs,Total_points,1); Rx_Signal = linspace(1,10,Total_points)'; Rx_sld = abs(sqrt(npower*Rx_Signal./2).*rsamp).^2; % Applying CFAR funtion to get thresholds [x_detected,th] = cfar(Rx_sld,1:length(Rx_sld)); plot(1:length(Rx_sld),Rx_sld,1:length(Rx_sld),th,find(x_detected),Rx_sld(x_detected),'o') legend('Signal','Threshold','Detections','Location','northwest') title('Cell Averaging CFAR Detection ') xlabel('Time Index') ylabel('Threshold')