283 lines
8.5 KiB
Mathematica
283 lines
8.5 KiB
Mathematica
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%% 功能：单人呼吸心跳原始数据采集与MATLAB处理
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%% 基于平台 IWR1642EVM+DCA1000
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%% 思考：如何将IWR1843EVM+DCA1000采集得到的数据移植到这份代码上
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%% ========================================================================
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clc;clear;close all;
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%% =========================================================================
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%% 读取数据部分
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numADCSamples = 200; % number of ADC samples per chirp
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numADCBits = 16; % number of ADC bits per sample
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numRX = 4; % number of receivers
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numLanes = 2; % do not change. number of lanes is always 2
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isReal = 0; % set to 1 if real only data, 0 if complex data0
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chirpLoop = 2;
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%% 雷达参数设置
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Fs=4e6; %ADC采样率 见配置说明
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c=3*1e8; %光速
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ts=numADCSamples/Fs;%ADC采样时间
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slope=70e12; %调频斜率
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B_valid =ts*slope; %有效带宽
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detaR=c/(2*B_valid);%距离分辨率
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%% 读取Bin文件
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Filename = 'xxx.bin'; %文件名
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fid = fopen(Filename,'r');
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adcDataRow = fread(fid, 'int16');
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if numADCBits ~= 16
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l_max = 2^(numADCBits-1)-1;
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adcDataRow(adcDataRow > l_max) = adcDataRow(adcDataRow > l_max) - 2^numADCBits;
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end
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fclose(fid);
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fileSize = size(adcDataRow, 1);
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PRTnum = fix(fileSize/(numADCSamples*numRX));
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fileSize = PRTnum * numADCSamples*numRX;
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adcData = adcDataRow(1:fileSize);
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% real data reshape, filesize = numADCSamples*numChirps
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if isReal
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numChirps = fileSize/numADCSamples/numRX;
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LVDS = zeros(1, fileSize);
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%create column for each chirp
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LVDS = reshape(adcData, numADCSamples*numRX, numChirps);
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%each row is data from one chirp
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LVDS = LVDS.';
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else
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numChirps = fileSize/2/numADCSamples/numRX; %含有实部虚部除以2
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LVDS = zeros(1, fileSize/2);
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%combine real and imaginary part into complex data
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%read in file: 2I is followed by 2Q
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counter = 1;
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for i=1:4:fileSize-1
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LVDS(1,counter) = adcData(i) + sqrt(-1)*adcData(i+2);
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LVDS(1,counter+1) = adcData(i+1)+sqrt(-1)*adcData(i+3); counter = counter + 2;
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end
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% create column for each chirp
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LVDS = reshape(LVDS, numADCSamples*numRX, numChirps);
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%each row is data from one chirp
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LVDS = LVDS.';
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end
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%% 重组数据
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adcData = zeros(numRX,numChirps*numADCSamples);
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for row = 1:numRX
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for i = 1:numChirps
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adcData(row, (i-1)*numADCSamples+1:i*numADCSamples) = LVDS(i, (row-1)*numADCSamples+1:row*numADCSamples);
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end
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end
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retVal= reshape(adcData(1, :), numADCSamples, numChirps); %取第二个接收天线数据，数据存储方式为一个chirp一列
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process_adc = retVal(:,1:4:end);
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%% 距离维FFT（1个chirp)
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% figure;
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% plot((1:numADCSamples)*detaR,db(abs(fft(process_adc(:,1)))));
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% xlabel('距离（m）');
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% ylabel('幅度(dB)');
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% title('距离维FFT（1个chirp）');
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% figure;
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% plot(db(abs(fft(process_adc(:,1)))))
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%% 相位解缠绕部分
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RangFFT = 512;
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fft_data_last = zeros(1,RangFFT);
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range_max = 0;
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adcdata = process_adc;
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numChirps = size(adcdata, 2);
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%% 距离维FFT
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fft_data = fft(adcdata,RangFFT);
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fft_data = fft_data.';
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fft_data_abs = abs(fft_data);
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fft_data_abs(:,1:4)=0; %去除直流分量
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real_data = real(fft_data);
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imag_data = imag(fft_data);
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for i = 1:numChirps
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for j = 1:RangFFT %对每一个距离点取相位 extract phase
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angle_fft(i,j) = atan2(imag_data(i, j),real_data(i, j));
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end
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end
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% Range-bin tracking 找出能量最大的点，即人体的位置
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for j = 1:RangFFT
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for i = 1:numChirps % 进行非相干积累
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fft_data_last(j) = fft_data_last(j) + fft_data_abs(i,j);
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end
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if ( fft_data_last(j) > range_max)
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range_max = fft_data_last(j);
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max_num = j;
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end
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end
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%% 取出能量最大点的相位 extract phase from selected range bin
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angle_fft_last = angle_fft(:,max_num);
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%% 进行相位解缠 phase unwrapping(手动解)，自动解可以采用MATLAB自带的函数unwrap()
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n = 1;
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for i = 1+1:numChirps
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diff = angle_fft_last(i) - angle_fft_last(i-1);
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if diff > pi
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angle_fft_last(i:end) = angle_fft_last(i:end) - 2*pi;
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n = n + 1;
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elseif diff < -pi
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angle_fft_last(i:end) = angle_fft_last(i:end) + 2*pi;
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end
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end
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%% phase difference 相位差分后的数据
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angle_fft_last2=zeros(1,numChirps);
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for i = 1:numChirps-1
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angle_fft_last2(i) = angle_fft_last(i+1) - angle_fft_last(i);
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angle_fft_last2(numChirps)=angle_fft_last(numChirps)-angle_fft_last(numChirps-1);
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end
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% figure;
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% plot(angle_fft_last2);
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% xlabel('点数（N）');
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% ylabel('相位');
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% title('相位差分后的结果');
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%% IIR带通滤波 Bandpass Filter 0.1-0.6hz，得到呼吸的数据
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fs =20; %呼吸心跳信号采样率
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COE1=chebyshev_IIR; %采用fdatool生成函数
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save coe1.mat COE1;
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breath_data = filter(COE1,angle_fft_last2);
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% figure;
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% plot(breath_data);
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% xlabel('时间/点数');
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% ylabel('幅度');
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% title('呼吸时域波形');
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%% 谱估计 -FFT -Peak interval
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N1=length(breath_data);
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fshift = (-N1/2:N1/2-1)*(fs/N1); % zero-centered frequency
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breath_fre = abs(fftshift(fft(breath_data))); %--FFT
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% figure;
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% plot(fshift,breath_fre);
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% xlabel('频率（f/Hz）');
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% ylabel('幅度');
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% title('呼吸信号FFT ');
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breath_fre_max = 0; % 呼吸频率
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breath_index1 = length(breath_fre)/2;
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for i = 1:breath_index1%谱峰最大值搜索 对称其实可以取一半
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if (breath_fre(i) > breath_fre_max)
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breath_fre_max = breath_fre(i);
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if(breath_fre_max<1e-2) %幅度置信 判断是否是存在人的呼吸
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breath_index=numChirps+1;
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else
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breath_index=i;
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end
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end
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end
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breath_count =(fs*(breath_index1-breath_index)/numChirps)*60; %呼吸频率解算
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%% IIR带通滤波 Bandpass Filter 0.8-2hz 得到心跳的数据
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COE2=chebyshev_IIR2;
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save coe2.mat COE2;
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heart_data = filter(COE2,angle_fft_last2);
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N1=length(heart_data);
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fshift = (-N1/2:N1/2-1)*(fs/N1); % zero-centered frequency
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heart_fre = abs(fftshift(fft(heart_data)));
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% figure;
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% plot(fshift,heart_fre);
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% xlabel('频率（f/Hz）');
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% ylabel('幅度');
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% title('心跳信号FFT');
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heart_fre_max = 0;
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heart_index1 = length(heart_fre)/2 ;
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for i = 1:heart_index1
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if (heart_fre(i) > heart_fre_max)
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heart_fre_max = heart_fre(i);
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if(heart_fre_max<1e-2)%幅度置信 判断是否是存在人的心跳
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heart_index=numChirps+1;
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else
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heart_index=i;
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end
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end
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end
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heart_count =(fs*(heart_index1-(heart_index-1))/numChirps)*60%心跳频率解算
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% 2399个帧，约为120s，
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% 如果数据长度够长，则雷达会51.2s对呼吸数据和心跳数据进行一次刷新，
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%以便实现更为精确的检测。
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disp(['呼吸：',num2str(breath_count),' 心跳：',num2str(heart_count)])
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%% 动画演示
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%读入波形
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breath_fre;
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heart_fre;
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count =0;
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%显示波形长度
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L =500;
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T_frame =0.05 ;%50ms
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for i = 1:length(breath_fre)-L-1
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figure(10);
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count=count+i;
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[breath_pks,breath_locs] = findpeaks(breath_data(i:i+L )) ;
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breath_fre =(60/ (L*T_frame))*length(breath_pks);
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[heart_pks,heart_locs] = findpeaks(heart_data(i:i+L )) ;
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heart_fre =(60/ (L*T_frame))*length(heart_pks);
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if count>500
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subplot(121);
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plot((i:i+L)*T_frame,breath_data(i:i+L ),'g');
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grid on
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xlim([i,i+L]*T_frame);
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ylim([-0.8,0.8]);
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hold on
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xlabel('时间（s）');
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ylabel('幅度');
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title(['呼吸时域波形',num2str(breath_fre),'次']);
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hold off
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subplot(122);
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plot((i:i+L)*T_frame,heart_data(i:i+L ),'r');
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grid on
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xlim([i,i+L]*T_frame);
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ylim([-0.8,0.8]);
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hold on
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xlabel('时间（s）');
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ylabel('幅度');
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title(['心跳时域波形:',num2str(heart_fre),'次']);
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hold off
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else
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%呼吸时域
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subplot(121);
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plot((i:i+L)*T_frame,breath_data(i:i+L ),'g');grid on
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xlim([i,i+L]*T_frame);
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ylim([-0.8,0.8]);
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hold on
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xlabel('时间（s）');
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ylabel('幅度');
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title(['呼吸时域波形:',num2str(breath_fre),'次']);
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hold off
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subplot(122);
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plot((i:i+L)*T_frame,heart_data(i:i+L ),'r');grid on
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xlim([i,i+L]*T_frame);
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ylim([-0.8,0.8]);
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hold on
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xlabel('时间（s）');
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ylabel('幅度');
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title(['心跳时域波形:',num2str(heart_fre),'次']);
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end
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hold off
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end
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