plot radio metrics as a function of distance

aerpaw/results/plotRadioLogs.m

@@ -1,9 +1,12 @@
-function [f, R] = plotRadioLogs(resultsPath)
+function [f, fDist, R] = plotRadioLogs(resultsPath, G, tLim)
     arguments (Input)
         resultsPath (1, 1) string;
+        G cell = {};
+        tLim (1, 2) datetime = [datetime(-Inf, 'ConvertFrom', 'datenum'), datetime(Inf, 'ConvertFrom', 'datenum')];
     end
     arguments (Output)
         f (1, 1) matlab.ui.Figure;
+        fDist (1, 1) matlab.ui.Figure;
         R cell;
     end
 
@@ -41,6 +44,7 @@ function [f, R] = plotRadioLogs(resultsPath)
     metricNames = ["SNR", "Power", "Quality", "PathLoss", "NoiseFloor", "FreqOffset"];
     yLabels     = ["SNR (dB)", "Power (dB)", "Quality", "Path Loss (dB)", "Noise Floor (dB)", "Freq Offset (MHz)"];
 
+    % --- Time-based figure ---
     f = figure;
     tl = tiledlayout(numel(metricNames), 1, 'TileSpacing', 'compact', 'Padding', 'compact');
 
@@ -57,10 +61,10 @@ function [f, R] = plotRadioLogs(resultsPath)
             for ti = 1:numel(txIDs)
                 txID = txIDs(ti);
                 rows = tbl(tbl.TxUAVID == txID, :);
+                rows = rows(rows.Timestamp >= tLim(1) & rows.Timestamp <= tLim(2), :);
                 vals = rows.(metricNames(mi));
 
-                % Skip if all NaN for this metric
+                if isempty(rows) || all(isnan(vals))
-                if all(isnan(vals))
                     continue;
                 end
 
@@ -81,4 +85,100 @@ function [f, R] = plotRadioLogs(resultsPath)
     end
 
     title(tl, 'Radio Channel Metrics');
+
+    % --- Distance-based figure ---
+    fDist = figure;
+
+    if isempty(G)
+        return;
+    end
+
+    tl2 = tiledlayout(numel(metricNames), 1, 'TileSpacing', 'compact', 'Padding', 'compact');
+
+    for mi = 1:numel(metricNames)
+        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, :);
+
+                if isempty(rows)
+                    continue;
+                end
+
+                rows = rows(rows.Timestamp >= tLim(1) & rows.Timestamp <= tLim(2), :);
+                if isempty(rows)
+                    continue;
+                end
+
+                vals = rows.(metricNames(mi));
+                if all(isnan(vals))
+                    continue;
+                end
+
+                % Map 0-based UAV IDs to 1-based GPS cell indices
+                txGpsIdx = double(txID) + 1;
+                rxGpsIdx = double(rows.RxUAVID(1)) + 1;
+
+                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
+
+                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>
+                ci = ci + 1;
+            end
+        end
+
+        ylabel(ax, yLabels(mi));
+        if mi == numel(metricNames)
+            xlabel(ax, 'Distance (m)');
+        end
+        legend(ax, legendEntries, 'Location', 'best');
+        hold(ax, 'off');
+    end
+
+    title(tl2, 'Radio Channel Metrics vs Distance');
 end

aerpaw/results/resultsAnalysis.m

@@ -26,9 +26,8 @@ seaToGroundLevel = 110; % measured approximately from USGS national map viewer
 plotWholeFlight = true; % do not attempt to automatically trim initial and final positioning and landing from flight plot (buggy)
 [fGlobe, G] = plotGpsLogs(resultsPath, seaToGroundLevel, true);
 
-% Plot radio statistics
+% Plot radio statistics (time-based and distance-based)
-[fRadio, R] = plotRadioLogs(resultsPath);
+[fRadio, fRadioDist, R] = plotRadioLogs(resultsPath, G, controller.timestamp([1, end]));
-set(findobj(fRadio, 'Type', 'axes'), 'XLim', controller.timestamp([1, end]));
 
 %% Run simulation
 % Run miSim using same AERPAW scenario definition CSV