112 lines
4.2 KiB
Matlab
112 lines
4.2 KiB
Matlab
function R = readRadioLogs(logPath)
|
|
arguments (Input)
|
|
logPath (1, 1) string {isfolder(logPath)};
|
|
end
|
|
arguments (Output)
|
|
R (:, 8) table;
|
|
end
|
|
|
|
% Extract receiving UAV ID from directory name (e.g. "uav0_..." → 0)
|
|
[~, dirName] = fileparts(logPath);
|
|
rxID = int32(sscanf(dirName, 'uav%d'));
|
|
|
|
metrics = ["quality", "snr", "power", "noisefloor", "freqoffset"];
|
|
logs = dir(logPath);
|
|
logs = logs(endsWith({logs(:).name}, metrics + "_log.txt"));
|
|
|
|
R = table(datetime.empty(0,1), zeros(0,1,'int32'), zeros(0,1,'int32'), zeros(0,1), zeros(0,1), zeros(0,1), zeros(0,1), zeros(0,1), ...
|
|
'VariableNames', ["Timestamp", "TxUAVID", "RxUAVID", "SNR", "Power", "Quality", "NoiseFloor", "FreqOffset"]);
|
|
|
|
for ii = 1:numel(logs)
|
|
filepath = fullfile(logs(ii).folder, logs(ii).name);
|
|
|
|
% Determine which metric this file contains
|
|
metric = "";
|
|
for m = 1:numel(metrics)
|
|
if endsWith(logs(ii).name, metrics(m) + "_log.txt")
|
|
metric = metrics(m);
|
|
break;
|
|
end
|
|
end
|
|
|
|
fid = fopen(filepath, 'r');
|
|
% Skip header lines: some files have 2 tail-error lines + 1 column
|
|
% header ("tx_uav_id,value"), others start with data immediately.
|
|
% Read until a line that looks like a data record, then rewind to it.
|
|
dataPattern = '^\[\d{4}-\d{2}-\d{2} \d{2}:\d{2}:\d{2}\.\d+\] [-\d]';
|
|
linePos = ftell(fid);
|
|
while true
|
|
line = fgetl(fid);
|
|
if ~ischar(line)
|
|
break; % EOF
|
|
end
|
|
if ~isempty(regexp(line, dataPattern, 'once'))
|
|
fseek(fid, linePos, 'bof'); % rewind to start of this line
|
|
break;
|
|
end
|
|
linePos = ftell(fid);
|
|
end
|
|
data = textscan(fid, '[%26c] %d,%f');
|
|
fclose(fid);
|
|
|
|
ts = datetime(cellstr(data{1}), 'InputFormat', 'yyyy-MM-dd HH:mm:ss.SSSSSS');
|
|
txId = int32(data{2});
|
|
val = data{3};
|
|
|
|
n = numel(ts);
|
|
t = table(ts, txId, repmat(rxID, n, 1), NaN(n,1), NaN(n,1), NaN(n,1), NaN(n,1), NaN(n,1), ...
|
|
'VariableNames', ["Timestamp", "TxUAVID", "RxUAVID", "SNR", "Power", "Quality", "NoiseFloor", "FreqOffset"]);
|
|
|
|
switch metric
|
|
case "snr", t.SNR = val;
|
|
case "power", t.Power = val;
|
|
case "quality", t.Quality = val;
|
|
case "noisefloor", t.NoiseFloor = val;
|
|
case "freqoffset", t.FreqOffset = val;
|
|
end
|
|
|
|
R = [R; t]; %#ok<AGROW>
|
|
end
|
|
|
|
R = sortrows(R, "Timestamp");
|
|
|
|
% Reconstruct per-measurement timestamps within GNURadio processing batches.
|
|
% The flowgraph accumulates one full PN sequence (4095 chips at samp_rate/sps)
|
|
% per measurement, but outputs the whole batch simultaneously with a single
|
|
% wall-clock timestamp. We reassign timestamps by counting backward from the
|
|
% batch processing time at the known PN period interval.
|
|
pn_period = 4095 / (2e6 / 16); % 32.76 ms per PN correlation period
|
|
|
|
for txId = unique(R.TxUAVID)'
|
|
rows = find(R.TxUAVID == txId);
|
|
if numel(rows) < 2, continue; end
|
|
|
|
dt = seconds(diff(R.Timestamp(rows)));
|
|
break_pos = [1; find(dt > 0.5) + 1];
|
|
end_pos = [break_pos(2:end) - 1; numel(rows)];
|
|
|
|
for b = 1:numel(break_pos)
|
|
idx = rows(break_pos(b) : end_pos(b));
|
|
batch_ts = posixtime(R.Timestamp(idx));
|
|
t_ref = max(batch_ts);
|
|
|
|
% Multiple metric files share the same processing timestamp for
|
|
% each PN period, so group by unique original timestamp rather
|
|
% than treating every row as a separate PN period.
|
|
[~, ~, group_id] = unique(batch_ts);
|
|
n_groups = max(group_id);
|
|
new_ts = t_ref - (n_groups - 1 : -1 : 0)' * pn_period;
|
|
|
|
for g = 1:n_groups
|
|
R.Timestamp(idx(group_id == g)) = ...
|
|
datetime(new_ts(g), 'ConvertFrom', 'posixtime');
|
|
end
|
|
end
|
|
end
|
|
|
|
% Remove rows during defined guard period between TDM shifts
|
|
R(R.TxUAVID == -1, :) = [];
|
|
|
|
% Remove self-reception rows (TX == RX)
|
|
R(R.TxUAVID == R.RxUAVID, :) = [];
|
|
end |