Archived
add ant data; add null algorithm switch
to evaluate amp-phase consistency of phased array at different frequency, tens of data set is sampled; in dl814_k7_cal_coarse, the switch of ad9361 data and test data is added, and the depth of rx data ila is enlarged to 131072
This commit is contained in:
LFS
Executable → Regular
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+13
-1
@@ -33,5 +33,17 @@ for i=1:32
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end
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end
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weight_stream_data_ind
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weight_stream_data_index = 1;
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flag = 1;
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while (flag)
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weight_stream_data_str = num2str(weight_stream_data((1:32)+weight_stream_data_index-1)');
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tmp = bin2dec(erase(convertCharsToStrings(weight_stream_data_str)," "));
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if (tmp == hex2dec("7E7E7E7E"))
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flag = 0;
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else
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weight_stream_data_index = weight_stream_data_index + 1;
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end
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end
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+204
@@ -0,0 +1,204 @@
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%% File Header/文件说明
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%
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% Beamforming with phased array derives signal characteristics from phase
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% differences between sensors. Therefore the amplitude-phase consistence is
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% vital to phased systems.
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%
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% The script analyzes the amp-phase relations of ILA captured data, the format
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% of which is square-shaped pseudorandorm bit sequence. Each channel is
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% processed seperately with different frequency shifts and different optimum
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% sampling points. The estimation of amplitude and phase are based on
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% acculumated correlation peaks.
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%
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clc; clear;
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%% initial parameters/初始参数
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interp = 8; % interpolation factor
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channelNum = 4;
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dataLen = 8192;
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fs = 48e6;
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dataFile = [...
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"iladata_25.0G_1-1.csv",...
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"iladata_25.0G_1-2.csv",...
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"iladata_25.0G_1-3.csv",...
|
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"iladata_25.1G_1-1.csv",...
|
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"iladata_25.1G_1-2.csv",...
|
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"iladata_25.1G_1-3.csv",...
|
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"iladata_25.2G_1-1.csv",...
|
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"iladata_25.2G_1-2.csv",...
|
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"iladata_25.2G_1-3.csv",...
|
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"iladata_25.3G_1-1.csv",...
|
||||
"iladata_25.3G_1-2.csv",...
|
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"iladata_25.3G_1-3.csv",...
|
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"iladata_25.4G_1-1.csv",...
|
||||
"iladata_25.4G_1-2.csv",...
|
||||
"iladata_25.4G_1-3.csv",...
|
||||
"iladata_25.5G_1-1.csv",...
|
||||
"iladata_25.5G_1-2.csv",...
|
||||
"iladata_25.5G_1-3.csv",...
|
||||
"iladata_25.6G_1-1.csv",...
|
||||
"iladata_25.6G_1-2.csv",...
|
||||
"iladata_25.6G_1-3.csv",...
|
||||
"iladata_25.7G_1-1.csv",...
|
||||
"iladata_25.7G_1-2.csv",...
|
||||
"iladata_25.7G_1-3.csv",...
|
||||
"iladata_25.8G_1-1.csv",...
|
||||
"iladata_25.8G_1-2.csv",...
|
||||
"iladata_25.8G_1-3.csv",...
|
||||
"iladata_25.9G_1-1.csv",...
|
||||
"iladata_25.9G_1-2.csv",...
|
||||
"iladata_25.9G_1-3.csv",...
|
||||
"iladata_26.0G_1-1.csv",...
|
||||
"iladata_26.0G_1-2.csv",...
|
||||
"iladata_26.0G_1-3.csv",...
|
||||
"iladata_26.1G_1-1.csv",...
|
||||
"iladata_26.1G_1-2.csv",...
|
||||
"iladata_26.1G_1-3.csv",...
|
||||
"iladata_26.2G_1-1.csv",...
|
||||
"iladata_26.2G_1-2.csv",...
|
||||
"iladata_26.2G_1-3.csv",...
|
||||
"iladata_26.3G_1-1.csv",...
|
||||
"iladata_26.3G_1-2.csv",...
|
||||
"iladata_26.3G_1-3.csv",...
|
||||
"iladata_26.4G_1-1.csv",...
|
||||
"iladata_26.4G_1-2.csv",...
|
||||
"iladata_26.4G_1-3.csv",...
|
||||
"iladata_26.5G_1-1.csv",...
|
||||
"iladata_26.5G_1-2.csv",...
|
||||
"iladata_26.5G_1-3.csv",...
|
||||
"iladata_26.6G_1-1.csv",...
|
||||
"iladata_26.6G_1-2.csv",...
|
||||
"iladata_26.6G_1-3.csv",...
|
||||
"iladata_26.7G_1-1.csv",...
|
||||
"iladata_26.7G_1-2.csv",...
|
||||
"iladata_26.8G_1-1.csv",...
|
||||
"iladata_26.8G_1-2.csv",...
|
||||
"iladata_26.8G_1-3.csv",...
|
||||
"iladata_26.9G_1-1.csv",...
|
||||
"iladata_26.9G_1-2.csv",...
|
||||
"iladata_26.9G_1-3.csv",...
|
||||
"iladata_27.0G_1-1.csv",...
|
||||
"iladata_27.0G_1-2.csv",...
|
||||
"iladata_27.0G_1-3.csv",...
|
||||
];
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dataFileNum = length(dataFile);
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% standard pn sequence
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pnSequence = comm.PNSequence('Polynomial','x^7+x^6+1', ...
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'InitialConditions',[zeros(1,6),1],'SamplesPerFrame',2^7-1);
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PRBS7 = pnSequence();
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PRBS7_polar = 1-2*[PRBS7;0];
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chipLen = length(PRBS7_polar); % pn chip length
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symNum = dataLen/chipLen/interp; % total symbol number
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symNumPerAccum = 1; % symbol nbumber of each accumulation
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accNum = symNum/symNumPerAccum; % total accumulation numbers, i.e. peak numbers
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ampEstSymMax = zeros(dataFileNum,channelNum);
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ampEstSymMin = zeros(dataFileNum,channelNum);
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ampEstSymAvg = zeros(dataFileNum,channelNum);
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angleEstSymMax = zeros(dataFileNum,channelNum);
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angleEstSymMin = zeros(dataFileNum,channelNum);
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angleEstSymAvg = zeros(dataFileNum,channelNum);
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ampEstSymMaxList = strings(dataFileNum+1,channelNum+1);
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ampEstSymMinList = strings(dataFileNum+1,channelNum+1);
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ampEstSymAvgList = strings(dataFileNum+1,channelNum+1);
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angleEstSymMaxList = strings(dataFileNum+1,channelNum+1);
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angleEstSymMinList = strings(dataFileNum+1,channelNum+1);
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angleEstSymAvgList = strings(dataFileNum+1,channelNum+1);
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ampEstSymMaxList(1,:) = ["Amp Max Value", "ch1", "ch2", "ch3", "ch4"];
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ampEstSymMinList(1,:) = ["Amp Min Value", "ch1", "ch2", "ch3", "ch4"];
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ampEstSymAvgList(1,:) = ["Amp Avg Value", "ch1", "ch2", "ch3", "ch4"];
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angleEstSymMaxList(1,:) = ["Angle Max Value", "ch1", "ch2", "ch3", "ch4"];
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angleEstSymMinList(1,:) = ["Angle Min Value", "ch1", "ch2", "ch3", "ch4"];
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angleEstSymAvgList(1,:) = ["Angle Avg Value", "ch1", "ch2", "ch3", "ch4"];
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ampEstSymMaxList(2:end,1) = dataFile;
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ampEstSymMinList(2:end,1) = dataFile;
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ampEstSymAvgList(2:end,1) = dataFile;
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angleEstSymMaxList(2:end,1) = dataFile;
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angleEstSymMinList(2:end,1) = dataFile;
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angleEstSymAvgList(2:end,1) = dataFile;
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for dataFileIndex = 1:dataFileNum
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disp(dataFile(dataFileIndex));
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%% data analysis
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% read data, and swap ch1 and ch2, because loop data locate at ch2 and ch4
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rxdata = readmatrix(dataFile(dataFileIndex));
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seqRx(:,1) = (rxdata(:, 6) + 1i*rxdata(:, 7)).';
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seqRx(:,2) = (rxdata(:, 4) + 1i*rxdata(:, 5)).';
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seqRx(:,3) = (rxdata(:, 8) + 1i*rxdata(:, 9)).';
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seqRx(:,4) = (rxdata(:,10) + 1i*rxdata(:,11)).';
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% compensate frequecny deviation and downsample at optimum sample position based
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% on the varience of constellation
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[seqRxDown,fd,samplePos] = suqareShapeFreqEst(seqRx,interp,fs,-25000,-21000,5);
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% split [seqRxDown] into multiple groups, each group contains several symbols to
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% be correlated with PRBS7 and accumulated
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seqRxDownSplit = reshape(seqRxDown(1:dataLen/interp,:),chipLen*symNumPerAccum, ...
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accNum,channelNum);
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seqRxAcc = zeros(chipLen,accNum,channelNum);
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desiredPnt = zeros(accNum,channelNum);
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ampEstSym = zeros(accNum,channelNum);
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angleEstSym = zeros(accNum,channelNum);
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for i = 1:accNum
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for j = 1:channelNum
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% correlation & multi-symbol accumulation
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groupCorrAcc = sum(...
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reshape(...
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conv(...
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flip(seqRxDownSplit(:,i,j)),...
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PRBS7_polar,'same'),...
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chipLen,symNumPerAccum),...
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2)';
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seqRxAcc(:,i,j) = groupCorrAcc;
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% peak position
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desiredPnt(i,j) = groupCorrAcc(abs(groupCorrAcc)==max(abs(groupCorrAcc)));
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end
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end
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for i = 1:channelNum
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ampEstSym(:,i) = abs(desiredPnt(:,i))./abs(desiredPnt(:,1));
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angleEstSym(:,i) = mod((angle(desiredPnt(:,i))-angle(desiredPnt(:,1)))/pi*180,360);
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end
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ampEstSymMax(dataFileIndex,:) = max(ampEstSym);
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ampEstSymMin(dataFileIndex,:) = min(ampEstSym);
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ampEstSymAvg(dataFileIndex,:) = mean(ampEstSym);
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angleEstSymMax(dataFileIndex,:) = max(angleEstSym);
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angleEstSymMin(dataFileIndex,:) = min(angleEstSym);
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angleEstSymAvg(dataFileIndex,:) = mean(angleEstSym);
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ampEstSymMaxList(dataFileIndex+1,2:end) = string(ampEstSymMax(dataFileIndex,:));
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ampEstSymMinList(dataFileIndex+1,2:end) = string(ampEstSymMin(dataFileIndex,:));
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ampEstSymAvgList(dataFileIndex+1,2:end) = string(ampEstSymAvg(dataFileIndex,:));
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angleEstSymMaxList(dataFileIndex+1,2:end) = string(angleEstSymMax(dataFileIndex,:));
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angleEstSymMinList(dataFileIndex+1,2:end) = string(angleEstSymMin(dataFileIndex,:));
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angleEstSymAvgList(dataFileIndex+1,2:end) = string(angleEstSymAvg(dataFileIndex,:));
|
||||
|
||||
end
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|
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|
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%% figures
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% figure(1);
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%
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% subplot(121);
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% plot(ampEstSym);
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% legend({"ch1","ch2","ch3","ch4"});
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% title("Amplitude Estimation");
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% ylim([min(ampEstSym,[],'all')-0.2,max(ampEstSym,[],'all')+0.2]);
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% grid on; grid minor;
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%
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% subplot(122);
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% plot(angleEstSym);
|
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% legend({"ch1","ch2","ch3","ch4"});
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% title("Angle Estimation");
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% ylim([-10,370]);
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% grid on; grid minor;
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||||
+199
@@ -0,0 +1,199 @@
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%% File Header/文件说明
|
||||
%
|
||||
% Beamforming with phased array derives signal characteristics from phase
|
||||
% differences between sensors. Therefore the amplitude-phase consistence is
|
||||
% vital to phased systems.
|
||||
%
|
||||
% The script analyzes the amp-phase relations of ILA captured data, the format
|
||||
% of which is square-shaped pseudorandorm bit sequence. Each channel is
|
||||
% processed seperately with different frequency shifts and different optimum
|
||||
% sampling points. The estimation of amplitude and phase are based on
|
||||
% acculumated correlation peaks.
|
||||
%
|
||||
clc; clear;
|
||||
%% initial parameters/初始参数
|
||||
interp = 8; % interpolation factor
|
||||
channelNum = 4;
|
||||
dataLen = 8192;
|
||||
fs = 48e6;
|
||||
dataFile = [...
|
||||
"iladata_25.0G_1-1.csv",...
|
||||
"iladata_25.0G_1-2.csv",...
|
||||
"iladata_25.0G_1-3.csv",...
|
||||
"iladata_25.1G_1-1.csv",...
|
||||
"iladata_25.1G_1-2.csv",...
|
||||
"iladata_25.1G_1-3.csv",...
|
||||
"iladata_25.2G_1-1.csv",...
|
||||
"iladata_25.2G_1-2.csv",...
|
||||
"iladata_25.2G_1-3.csv",...
|
||||
"iladata_25.3G_1-1.csv",...
|
||||
"iladata_25.3G_1-2.csv",...
|
||||
"iladata_25.3G_1-3.csv",...
|
||||
"iladata_25.4G_1-1.csv",...
|
||||
"iladata_25.4G_1-2.csv",...
|
||||
"iladata_25.4G_1-3.csv",...
|
||||
"iladata_25.5G_1-1.csv",...
|
||||
"iladata_25.5G_1-2.csv",...
|
||||
"iladata_25.5G_1-3.csv",...
|
||||
"iladata_25.6G_1-1.csv",...
|
||||
"iladata_25.6G_1-2.csv",...
|
||||
"iladata_25.6G_1-3.csv",...
|
||||
"iladata_25.7G_1-1.csv",...
|
||||
"iladata_25.7G_1-2.csv",...
|
||||
"iladata_25.7G_1-3.csv",...
|
||||
"iladata_25.8G_1-1.csv",...
|
||||
"iladata_25.8G_1-2.csv",...
|
||||
"iladata_25.8G_1-3.csv",...
|
||||
"iladata_25.9G_1-1.csv",...
|
||||
"iladata_25.9G_1-2.csv",...
|
||||
"iladata_25.9G_1-3.csv",...
|
||||
"iladata_26.0G_1-1.csv",...
|
||||
"iladata_26.0G_1-2.csv",...
|
||||
"iladata_26.0G_1-3.csv",...
|
||||
"iladata_26.1G_1-1.csv",...
|
||||
"iladata_26.1G_1-2.csv",...
|
||||
"iladata_26.1G_1-3.csv",...
|
||||
"iladata_26.2G_1-1.csv",...
|
||||
"iladata_26.2G_1-2.csv",...
|
||||
"iladata_26.2G_1-3.csv",...
|
||||
"iladata_26.3G_1-1.csv",...
|
||||
"iladata_26.3G_1-2.csv",...
|
||||
"iladata_26.3G_1-3.csv",...
|
||||
"iladata_26.4G_1-1.csv",...
|
||||
"iladata_26.4G_1-2.csv",...
|
||||
"iladata_26.4G_1-3.csv",...
|
||||
"iladata_26.5G_1-1.csv",...
|
||||
"iladata_26.5G_1-2.csv",...
|
||||
"iladata_26.5G_1-3.csv",...
|
||||
"iladata_26.6G_1-1.csv",...
|
||||
"iladata_26.6G_1-2.csv",...
|
||||
"iladata_26.6G_1-3.csv",...
|
||||
"iladata_26.7G_1-1.csv",...
|
||||
"iladata_26.7G_1-2.csv",...
|
||||
"iladata_26.8G_1-1.csv",...
|
||||
"iladata_26.8G_1-2.csv",...
|
||||
"iladata_26.8G_1-3.csv",...
|
||||
"iladata_26.9G_1-1.csv",...
|
||||
"iladata_26.9G_1-2.csv",...
|
||||
"iladata_26.9G_1-3.csv",...
|
||||
"iladata_27.0G_1-1.csv",...
|
||||
"iladata_27.0G_1-2.csv",...
|
||||
"iladata_27.0G_1-3.csv",...
|
||||
];
|
||||
dataFileNum = length(dataFile);
|
||||
|
||||
% standard pn sequence
|
||||
pnSequence = comm.PNSequence('Polynomial','x^7+x^6+1', ...
|
||||
'InitialConditions',[zeros(1,6),1],'SamplesPerFrame',2^7-1);
|
||||
PRBS7 = pnSequence();
|
||||
PRBS7_polar = 1-2*[PRBS7;0];
|
||||
|
||||
chipLen = length(PRBS7_polar); % pn chip length
|
||||
symNum = dataLen/chipLen/interp; % total symbol number
|
||||
symNumPerAccum = 1; % symbol nbumber of each accumulation
|
||||
accNum = symNum/symNumPerAccum; % total accumulation numbers, i.e. peak numbers
|
||||
|
||||
ampEstSymMax = zeros(dataFileNum,channelNum);
|
||||
ampEstSymMin = zeros(dataFileNum,channelNum);
|
||||
ampEstSymAvg = zeros(dataFileNum,channelNum);
|
||||
angleEstSymMax = zeros(dataFileNum,channelNum);
|
||||
angleEstSymMin = zeros(dataFileNum,channelNum);
|
||||
angleEstSymAvg = zeros(dataFileNum,channelNum);
|
||||
|
||||
ampEstSymMaxList = strings(dataFileNum+1,channelNum+1);
|
||||
ampEstSymMinList = strings(dataFileNum+1,channelNum+1);
|
||||
ampEstSymAvgList = strings(dataFileNum+1,channelNum+1);
|
||||
angleEstSymMaxList = strings(dataFileNum+1,channelNum+1);
|
||||
angleEstSymMinList = strings(dataFileNum+1,channelNum+1);
|
||||
angleEstSymAvgList = strings(dataFileNum+1,channelNum+1);
|
||||
|
||||
ampEstSymMaxList(1,:) = ["Amp Max Value", "ch1", "ch2", "ch3", "ch4"];
|
||||
ampEstSymMinList(1,:) = ["Amp Min Value", "ch1", "ch2", "ch3", "ch4"];
|
||||
ampEstSymAvgList(1,:) = ["Amp Avg Value", "ch1", "ch2", "ch3", "ch4"];
|
||||
angleEstSymMaxList(1,:) = ["Angle Max Value", "ch1", "ch2", "ch3", "ch4"];
|
||||
angleEstSymMinList(1,:) = ["Angle Min Value", "ch1", "ch2", "ch3", "ch4"];
|
||||
angleEstSymAvgList(1,:) = ["Angle Avg Value", "ch1", "ch2", "ch3", "ch4"];
|
||||
|
||||
ampEstSymMaxList(2:end,1) = dataFile;
|
||||
ampEstSymMinList(2:end,1) = dataFile;
|
||||
ampEstSymAvgList(2:end,1) = dataFile;
|
||||
angleEstSymMaxList(2:end,1) = dataFile;
|
||||
angleEstSymMinList(2:end,1) = dataFile;
|
||||
angleEstSymAvgList(2:end,1) = dataFile;
|
||||
|
||||
for dataFileIndex = 1:dataFileNum
|
||||
disp(dataFile(dataFileIndex));
|
||||
|
||||
%% data analysis
|
||||
|
||||
% read data, and swap ch1 and ch2, because loop data locate at ch2 and ch4
|
||||
rxdata = readmatrix(dataFile(dataFileIndex));
|
||||
seqRx(:,1) = (rxdata(:, 6) + 1i*rxdata(:, 7)).';
|
||||
seqRx(:,2) = (rxdata(:, 4) + 1i*rxdata(:, 5)).';
|
||||
seqRx(:,3) = (rxdata(:, 8) + 1i*rxdata(:, 9)).';
|
||||
seqRx(:,4) = (rxdata(:,10) + 1i*rxdata(:,11)).';
|
||||
|
||||
% compensate frequecny deviation and downsample at optimum sample position based
|
||||
% on the varience of constellation
|
||||
[seqRxDown,fd,samplePos] = suqareShapeFreqEst(seqRx,interp,fs,-25000,-21000,5);
|
||||
|
||||
% split [seqRxDown] into multiple groups, each group contains several symbols to
|
||||
% be correlated with PRBS7 and accumulated
|
||||
seqRxDownSplit = reshape(seqRxDown(1:dataLen/interp,:),chipLen*symNumPerAccum, ...
|
||||
accNum,channelNum);
|
||||
|
||||
seqRxAcc = zeros(chipLen,accNum,channelNum);
|
||||
desiredPnt = zeros(accNum,channelNum);
|
||||
ampEstSym = zeros(accNum,channelNum);
|
||||
angleEstSym = zeros(accNum,channelNum);
|
||||
|
||||
for i = 1:accNum
|
||||
for j = 1:channelNum
|
||||
% correlation & multi-symbol accumulation
|
||||
groupCorrAcc = sum(reshape(conv(flip(seqRxDownSplit(:,i,j)), ...
|
||||
PRBS7_polar,'same'),chipLen,symNumPerAccum),2)';
|
||||
seqRxAcc(:,i,j) = groupCorrAcc;
|
||||
% peak position
|
||||
desiredPnt(i,j) = groupCorrAcc(abs(groupCorrAcc)==max(abs(groupCorrAcc)));
|
||||
end
|
||||
end
|
||||
|
||||
for i = 1:channelNum
|
||||
ampEstSym(:,i) = abs(desiredPnt(:,i))./abs(desiredPnt(:,1));
|
||||
angleEstSym(:,i) = mod((angle(desiredPnt(:,i))-angle(desiredPnt(:,1)))/pi*180,360);
|
||||
end
|
||||
|
||||
ampEstSymMax(dataFileIndex,:) = max(ampEstSym);
|
||||
ampEstSymMin(dataFileIndex,:) = min(ampEstSym);
|
||||
ampEstSymAvg(dataFileIndex,:) = mean(ampEstSym);
|
||||
angleEstSymMax(dataFileIndex,:) = max(angleEstSym);
|
||||
angleEstSymMin(dataFileIndex,:) = min(angleEstSym);
|
||||
angleEstSymAvg(dataFileIndex,:) = mean(angleEstSym);
|
||||
|
||||
ampEstSymMaxList(dataFileIndex+1,2:end) = string(ampEstSymMax(dataFileIndex,:));
|
||||
ampEstSymMinList(dataFileIndex+1,2:end) = string(ampEstSymMin(dataFileIndex,:));
|
||||
ampEstSymAvgList(dataFileIndex+1,2:end) = string(ampEstSymAvg(dataFileIndex,:));
|
||||
angleEstSymMaxList(dataFileIndex+1,2:end) = string(angleEstSymMax(dataFileIndex,:));
|
||||
angleEstSymMinList(dataFileIndex+1,2:end) = string(angleEstSymMin(dataFileIndex,:));
|
||||
angleEstSymAvgList(dataFileIndex+1,2:end) = string(angleEstSymAvg(dataFileIndex,:));
|
||||
|
||||
end
|
||||
|
||||
|
||||
|
||||
%% figures
|
||||
% figure(1);
|
||||
%
|
||||
% subplot(121);
|
||||
% plot(ampEstSym);
|
||||
% legend({"ch1","ch2","ch3","ch4"});
|
||||
% title("Amplitude Estimation");
|
||||
% ylim([min(ampEstSym,[],'all')-0.2,max(ampEstSym,[],'all')+0.2]);
|
||||
% grid on; grid minor;
|
||||
%
|
||||
% subplot(122);
|
||||
% plot(angleEstSym);
|
||||
% legend({"ch1","ch2","ch3","ch4"});
|
||||
% title("Angle Estimation");
|
||||
% ylim([-10,370]);
|
||||
% grid on; grid minor;
|
||||
@@ -0,0 +1,50 @@
|
||||
function [dataOut, fdTarget, samplePosTarget] = suqareShapeFreqEst(dataIn, interp, fs, fmin, fmax, fd)
|
||||
%suqareShapeFreqEst - 利用星座图的集中程度在一定频率范围内使用频率步进估计方波成形信号的频偏
|
||||
%
|
||||
% data - input complex data, row vector
|
||||
% dataLen - data length
|
||||
% interp - interpolation rate
|
||||
% fs - sampling rate, in Herts
|
||||
% fmin - minimum estimation frequency, in Herts
|
||||
% fmax - maximum estimation frequency, in Herts
|
||||
% fd - estimation frequency step, in Herts
|
||||
|
||||
% dimension
|
||||
[dataLen,channelNum] = size(dataIn);
|
||||
|
||||
freqList = fmin:fd:fmax;
|
||||
freqNum = length(freqList);
|
||||
varRecord = zeros(freqNum,interp);
|
||||
|
||||
dataOut = zeros(dataLen/interp,channelNum);
|
||||
fdTarget = zeros(channelNum,1);
|
||||
samplePosTarget = zeros(channelNum,1);
|
||||
|
||||
for channel = 1:channelNum
|
||||
|
||||
for freq = 1:freqNum
|
||||
|
||||
% carrier
|
||||
cxr = exp(-1i*2*pi*freqList(freq)/fs*(0:dataLen-1)');
|
||||
|
||||
% apply frequency shift onto input data
|
||||
seqRx = dataIn(:,channel).*cxr;
|
||||
|
||||
for samplePos = 0:interp-1
|
||||
seqRxDown = downsample(seqRx,interp,samplePos); % 下采样
|
||||
seqRxDownQuaterOne = abs(real(seqRxDown)) + 1i*abs(imag(seqRxDown)); % 集中到第一象限
|
||||
varRecord(freq,samplePos+1) = var(seqRxDownQuaterOne);
|
||||
end
|
||||
|
||||
end
|
||||
|
||||
[fdIndex, samplePosIndex] = find(varRecord==min(min(varRecord)));
|
||||
fdTarget(channel) = freqList(fdIndex);
|
||||
samplePosTarget(channel) = samplePosIndex-1;
|
||||
|
||||
cxrTarget = exp(-1i*2*pi*fdTarget(channel)/fs*(0:dataLen-1)');
|
||||
seqRxTarget = dataIn(:,channel).*cxrTarget;
|
||||
dataOut(:,channel) = downsample(seqRxTarget,interp,samplePosTarget(channel));
|
||||
end
|
||||
|
||||
end
|
||||
@@ -0,0 +1,11 @@
|
||||
# 数据说明
|
||||
|
||||
1. iladata_ad9361_pure_noise.csv: 调零板 AD9361 单板噪声。
|
||||
|
||||
2. iladata_ad9361_ant_noise.csv: 调零板射频接收噪声。
|
||||
|
||||
3. iladata_ad9361_pure_noise_A-B.csv: 调零板 AD9361 单板噪声，第 A 次上电过程中第 B 次采集结果。
|
||||
|
||||
> 1~3 AD9361 配置均为 48Msps，BW 40MHz，外部本振，使用 AD9516-3 的 VCO 分频时钟。
|
||||
|
||||
4. iladata_814_1t2r_48msps_bwxxm_xxx_lo_A-B.csv：调零板 AD9361 单板噪声，48Msps，BW xxMHz，ext_lo 表示外部本振，int_lo 表示内部本振，第 A 次上电过程中第 B 次采集结果。
|
||||
Reference in New Issue
Block a user