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radio plot cleanup

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This commit is contained in:
Kevin Dee
2026-05-16 15:08:00 -07:00
parent db6bcbb151
commit ac56d3fcd2
4 changed files with 190 additions and 52 deletions
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aerpaw/results/plotRadioLogs.m
+124 -49
View File
@@ -43,12 +43,44 @@ function [f, fDist, R] = plotRadioLogs(resultsPath, G, tLim)
metricNames = ["SNR", "Power", "Quality", "PathLoss", "NoiseFloor", "FreqOffset"];
yLabels = ["SNR (dB)", "Power (dB)", "Quality", "Path Loss (dB)", "Noise Floor (dB)", "Freq Offset (MHz)"];
nMetrics = numel(metricNames);
% --- Time-based figure ---
f = figure;
tl = tiledlayout(numel(metricNames), 1, 'TileSpacing', 'compact', 'Padding', 'compact');
tl = tiledlayout(nMetrics + 1, 1, 'TileSpacing', 'compact', 'Padding', 'compact');
for mi = 1:numel(metricNames)
% Distance vs time tile (first)
ax = nexttile(tl);
hold(ax, 'on'); grid(ax, 'on');
legendEntries = string.empty;
ci = 1;
if ~isempty(G)
for rxIdx = 1:nUAV
tbl = R{rxIdx};
txIDs = unique(tbl.TxUAVID);
for ti = 1:numel(txIDs)
txID = txIDs(ti);
rows = tbl(tbl.TxUAVID == txID, :);
rows = rows(rows.Timestamp >= tLim(1) & rows.Timestamp <= tLim(2), :);
if isempty(rows), continue; end
[~, ia] = unique(rows.Timestamp);
[radioPt, dist] = pairDist(rows(ia, :), G);
if isempty(dist) || all(isnan(dist)), continue; end
valid = ~isnan(dist);
si = mod(ci - 1, numel(styles)) + 1;
plot(ax, datetime(radioPt(valid), 'ConvertFrom', 'posixtime'), dist(valid), ...
styles(si), 'Color', colors(ci, :), 'MarkerSize', 3, 'LineWidth', 0.5);
legendEntries(end+1) = sprintf("TX %d → RX %d", txID, rows.RxUAVID(1)); %#ok<AGROW>
ci = ci + 1;
end
end
end
ylabel(ax, 'Distance (m)');
xlabel(ax, 'Time');
legend(ax, legendEntries, 'Location', 'best');
hold(ax, 'off');
for mi = 1:nMetrics
ax = nexttile(tl);
hold(ax, 'on');
grid(ax, 'on');
@@ -63,21 +95,30 @@ function [f, fDist, R] = plotRadioLogs(resultsPath, G, tLim)
rows = tbl(tbl.TxUAVID == txID, :);
rows = rows(rows.Timestamp >= tLim(1) & rows.Timestamp <= tLim(2), :);
vals = rows.(metricNames(mi));
valid = ~isnan(vals);
rows = rows(valid, :);
vals = vals(valid);
if isempty(rows) || all(isnan(vals))
if isempty(rows)
continue;
end
si = mod(ci - 1, numel(styles)) + 1;
plot(ax, rows.Timestamp, vals, styles(si), ...
'Color', colors(ci, :), 'MarkerSize', 3, 'LineWidth', 1);
'Color', colors(ci, :), 'MarkerSize', 3, 'LineWidth', 0.5);
legendEntries(end+1) = sprintf("TX %d → RX %d", txID, tbl.RxUAVID(1)); %#ok<AGROW>
% Median per 1/3-second time bin
[t_med, v_med] = timeBinMedian(posixtime(rows.Timestamp), vals, 1/3);
plot(ax, datetime(t_med, 'ConvertFrom', 'posixtime'), v_med, '-', ...
'Color', 'r', 'LineWidth', 2);
legendEntries(end+1) = sprintf("TX %d → RX %d (median)", txID, tbl.RxUAVID(1)); %#ok<AGROW>
ci = ci + 1;
end
end
ylabel(ax, yLabels(mi));
if mi == numel(metricNames)
if mi == nMetrics
xlabel(ax, 'Time');
end
legend(ax, legendEntries, 'Location', 'best');
@@ -93,9 +134,38 @@ function [f, fDist, R] = plotRadioLogs(resultsPath, G, tLim)
return;
end
tl2 = tiledlayout(numel(metricNames), 1, 'TileSpacing', 'compact', 'Padding', 'compact');
tl2 = tiledlayout(nMetrics + 1, 1, 'TileSpacing', 'compact', 'Padding', 'compact');
for mi = 1:numel(metricNames)
% Distance vs time tile (first)
ax = nexttile(tl2);
hold(ax, 'on'); grid(ax, 'on');
legendEntries = string.empty;
ci = 1;
for rxIdx = 1:nUAV
tbl = R{rxIdx};
txIDs = unique(tbl.TxUAVID);
for ti = 1:numel(txIDs)
txID = txIDs(ti);
rows = tbl(tbl.TxUAVID == txID, :);
rows = rows(rows.Timestamp >= tLim(1) & rows.Timestamp <= tLim(2), :);
if isempty(rows), continue; end
[~, ia] = unique(rows.Timestamp);
[radioPt, dist] = pairDist(rows(ia, :), G);
if isempty(dist) || all(isnan(dist)), continue; end
valid = ~isnan(dist);
si = mod(ci - 1, numel(styles)) + 1;
plot(ax, datetime(radioPt(valid), 'ConvertFrom', 'posixtime'), dist(valid), ...
styles(si), 'Color', colors(ci, :), 'MarkerSize', 3, 'LineWidth', 0.5);
legendEntries(end+1) = sprintf("TX %d → RX %d", txID, rows.RxUAVID(1)); %#ok<AGROW>
ci = ci + 1;
end
end
ylabel(ax, 'Distance (m)');
xlabel(ax, 'Time');
legend(ax, legendEntries, 'Location', 'best');
hold(ax, 'off');
for mi = 1:nMetrics
ax = nexttile(tl2);
hold(ax, 'on');
grid(ax, 'on');
@@ -119,61 +189,39 @@ function [f, fDist, R] = plotRadioLogs(resultsPath, G, tLim)
end
vals = rows.(metricNames(mi));
if all(isnan(vals))
valid = ~isnan(vals);
rows = rows(valid, :);
vals = vals(valid);
if isempty(rows)
continue;
end
% Map 0-based UAV IDs to 1-based GPS cell indices
txGpsIdx = double(txID) + 1;
rxGpsIdx = double(rows.RxUAVID(1)) + 1;
[radioPt, dist] = pairDist(rows, G);
if isempty(dist) || all(isnan(dist)), continue; end
if txGpsIdx > numel(G) || rxGpsIdx > numel(G)
continue;
end
Gtx = G{txGpsIdx};
Grx = G{rxGpsIdx};
if ~ismember('East', Gtx.Properties.VariableNames) || ...
~ismember('East', Grx.Properties.VariableNames)
continue;
end
% Strip timezone before posixtime so radio and GPS timestamps
% are treated on the same scale (both are AERPAW wall-clock time)
txTs = Gtx.Timestamp; txTs.TimeZone = '';
rxTs = Grx.Timestamp; rxTs.TimeZone = '';
txPt = posixtime(txTs);
rxPt = posixtime(rxTs);
radioPt = posixtime(rows.Timestamp);
% Interpolate GPS positions at radio measurement times.
% Exclude NaN ENU entries (outside algorithm flight range).
validTx = ~isnan(Gtx.East);
validRx = ~isnan(Grx.East);
txE = interp1(txPt(validTx), Gtx.East(validTx), radioPt, 'linear', NaN);
txN = interp1(txPt(validTx), Gtx.North(validTx), radioPt, 'linear', NaN);
txU = interp1(txPt(validTx), Gtx.Up(validTx), radioPt, 'linear', NaN);
rxE = interp1(rxPt(validRx), Grx.East(validRx), radioPt, 'linear', NaN);
rxN = interp1(rxPt(validRx), Grx.North(validRx), radioPt, 'linear', NaN);
rxU = interp1(rxPt(validRx), Grx.Up(validRx), radioPt, 'linear', NaN);
dist = vecnorm([txE - rxE, txN - rxN, txU - rxU], 2, 2);
if all(isnan(dist))
continue;
end
% Drop points where GPS interpolation returned NaN
validDist = ~isnan(dist);
rowTs = radioPt(validDist);
dist = dist(validDist);
vals = vals(validDist);
si = mod(ci - 1, numel(styles)) + 1;
scatter(ax, dist, vals, 9, colors(ci, :), strrep(styles(si), "-", ""), 'filled');
legendEntries(end+1) = sprintf("TX %d → RX %d", txID, rows.RxUAVID(1)); %#ok<AGROW>
% Median per 1/3-second time bin, plotted against median distance
[~, dv_med] = timeBinMedian(rowTs, [dist, vals], 1/3);
[d_med, si_sort] = sort(dv_med(:, 1));
v_med = dv_med(si_sort, 2);
plot(ax, d_med, v_med, '-', 'Color', 'r', 'LineWidth', 2);
legendEntries(end+1) = sprintf("TX %d → RX %d (median)", txID, rows.RxUAVID(1)); %#ok<AGROW>
ci = ci + 1;
end
end
ylabel(ax, yLabels(mi));
if mi == numel(metricNames)
if mi == nMetrics
xlabel(ax, 'Distance (m)');
end
legend(ax, legendEntries, 'Location', 'best');
@@ -182,3 +230,30 @@ function [f, fDist, R] = plotRadioLogs(resultsPath, G, tLim)
title(tl2, 'Radio Channel Metrics vs Distance');
end
function [radioPt, dist] = pairDist(rows, G)
% Interpolate GPS-based inter-UAV distance at each row's timestamp.
radioPt = []; dist = [];
txGpsIdx = double(rows.TxUAVID(1)) + 1;
rxGpsIdx = double(rows.RxUAVID(1)) + 1;
if txGpsIdx > numel(G) || rxGpsIdx > numel(G), return; end
Gtx = G{txGpsIdx};
Grx = G{rxGpsIdx};
if ~ismember('East', Gtx.Properties.VariableNames) || ...
~ismember('East', Grx.Properties.VariableNames), return; end
txTs = Gtx.Timestamp; txTs.TimeZone = '';
rxTs = Grx.Timestamp; rxTs.TimeZone = '';
txPt = posixtime(txTs);
rxPt = posixtime(rxTs);
radioPt = posixtime(rows.Timestamp);
validTx = ~isnan(Gtx.East);
validRx = ~isnan(Grx.East);
txE = interp1(txPt(validTx), Gtx.East(validTx), radioPt, 'linear', NaN);
txN = interp1(txPt(validTx), Gtx.North(validTx), radioPt, 'linear', NaN);
txU = interp1(txPt(validTx), Gtx.Up(validTx), radioPt, 'linear', NaN);
rxE = interp1(rxPt(validRx), Grx.East(validRx), radioPt, 'linear', NaN);
rxN = interp1(rxPt(validRx), Grx.North(validRx), radioPt, 'linear', NaN);
rxU = interp1(rxPt(validRx), Grx.Up(validRx), radioPt, 'linear', NaN);
dist = vecnorm([txE - rxE, txN - rxN, txU - rxU], 2, 2);
end
aerpaw/results/readRadioLogs.m
+34
View File
@@ -70,6 +70,40 @@ function R = readRadioLogs(logPath)
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, :) = [];
aerpaw/results/timeBinMedian.m
+29
View File
@@ -0,0 +1,29 @@
function [t_med, v_med] = timeBinMedian(t, v, binWidth)
% Compute median of each column of v within fixed-width time bins.
%
% t - (N,1) posixtime values
% v - (N,K) data matrix; one column per quantity
% binWidth - scalar bin width in seconds
%
% t_med - (B,1) median time of each non-empty bin
% v_med - (B,K) median of each column per non-empty bin
edges = (floor(min(t) / binWidth) * binWidth) : binWidth : ...
(floor(max(t) / binWidth) * binWidth + binWidth);
bins = discretize(t, edges);
nBins = numel(edges) - 1;
K = size(v, 2);
t_all = NaN(nBins, 1);
v_all = NaN(nBins, K);
for bi = 1:nBins
mask = bins == bi;
if ~any(mask), continue; end
t_all(bi) = median(t(mask));
v_all(bi,:) = median(v(mask,:), 1);
end
ok = ~isnan(t_all);
t_med = t_all(ok);
v_med = v_all(ok, :);
end
test/test_miSim.m
+3 -3
View File
@@ -9,8 +9,8 @@ classdef test_miSim < matlab.unittest.TestCase
plotCommsGeometry = false; % disable plotting communications geometries
% Sim
maxIter = 50;
timestep = 0.05;
maxIter = 250;
timestep = 0.1;
% Domain
domain = rectangularPrism; % domain geometry
@@ -31,7 +31,7 @@ classdef test_miSim < matlab.unittest.TestCase
% Agents
initialStepSize = 0.2; % gradient ascent step size at the first iteration. Decreases linearly to 0 based on maxIter.
initialMaxAngleStepSize = 5; % angular step size (degrees) for tilt/azimuth gradient ascent per timestep.
initialMaxAngleStepSize = 0.1; % angular step size (degrees) for tilt/azimuth gradient ascent per timestep.
minAgents = 3; % Minimum number of agents to be randomly generated
maxAgents = 4; % Maximum number of agents to be randomly generated
useDoubleIntegrator = false;