Документация

% Create a bird's-eye plot and limit its axes
BEP = birdsEyePlot('Xlimits', [0 90], 'Ylimits', [-35 35]);

% Create a coverageAreaPlotter for a vision sensor and two radar modes
cap(1) = coverageAreaPlotter(BEP,'FaceColor','blue','EdgeColor','blue');
cap(2) = coverageAreaPlotter(BEP,'FaceColor','red','EdgeColor','red');
cap(3) = coverageAreaPlotter(BEP,'FaceColor','red','EdgeColor','red');

load('SensorConfigurationData.mat');
% Use the sensor configuration to plot the sensor coverage areas. Vision
% sensor uses the shaded blue coverage area and radar modes are shaded in
% red.
for i = 1:3
    plotCoverageArea(cap(i), [sensorParams(i).X, sensorParams(i).Y],...
        sensorParams(i).Range, sensorParams(i).YawAngle, sensorParams(i).FoV);
end

% Add title
title('Bird''s-Eye Plot')

% Load recorded data from a file
load('BirdsEyePlotExampleData.mat', 'dataToDisplay');

% Skip to the 125th time step, where there are 5 vision detections and
% multiple radar objects and tracks.
timeStep = 125;

% Extract the various data from the recorded file for that time step
[visionObjectsPos, radarObjectsPos, laneBoundaries, trackPositions, ...
    trackVelocities, trackCovariances, trackLabels, MIOlabel, MIOposition, ...
    MIOvelocity] = readDataFrame(dataToDisplay(timeStep));

% create a vision detection plotter put it in a struct for future use
bepPlotters.Vision = detectionPlotter(BEP, 'DisplayName','vision detection', ...
    'MarkerEdgeColor','blue', 'Marker','^');

% Combine all radar detections into one entry and store it for later update
bepPlotters.Radar = detectionPlotter(BEP, 'DisplayName','radar detection', ...
    'MarkerEdgeColor','red');

% Call the vision detections plotter
plotDetection(bepPlotters.Vision, visionObjectsPos);

% Repeat the above for radar detections
plotDetection(bepPlotters.Radar, radarObjectsPos);

% Create a track plotter that shows the last 10 track updates
bepPlotters.Track = trackPlotter(BEP, 'DisplayName','tracked object', ...
    'HistoryDepth',10);

% Create a track plotter to plot the most important object
bepPlotters.MIO = trackPlotter(BEP, 'DisplayName','most important object', ...
    'MarkerFaceColor','black');

% Call the track plotter to plot all the tracks
plotTrack(bepPlotters.Track, trackPositions, trackVelocities, trackCovariances, trackLabels);

% Repeat for the Most Important Object (MIO)
plotTrack(bepPlotters.MIO, MIOposition, MIOvelocity, MIOlabel);

% Create a plotter for lane boundaries
bepPlotters.LaneBoundary = laneBoundaryPlotter(BEP, ...
    'DisplayName','lane boundaries', 'Color',[.9 .9 0]);

% Call the lane boundaries plotter
plotLaneBoundary(bepPlotters.LaneBoundary, laneBoundaries);

% Rewind to the beginning of the recording file
timeStep = 0;
numSteps = numel(dataToDisplay); % Number of steps in the scenario

% Loop through the scenario as long as the bird's eye plot is open
while timeStep < numSteps && isvalid(BEP.Parent)
    % Promote the timeStep
    timeStep = timeStep + 1;

    % Capture the current time for a realistic display rate
    tic;

    % Read the data for that time step
    [visionObjectsPos, radarObjectsPos, laneBoundaries, trackPositions, ...
        trackVelocities, trackCovariances, trackLabels, MIOlabel, MIOposition, ...
        MIOvelocity] = readDataFrame(dataToDisplay(timeStep));

    % Plot detections
    plotDetection(bepPlotters.Vision, visionObjectsPos);
    plotDetection(bepPlotters.Radar, radarObjectsPos);

    % Plot tracks and MIO
    plotTrack(bepPlotters.Track, trackPositions, trackVelocities, trackCovariances, trackLabels);
    plotTrack(bepPlotters.MIO, MIOposition, MIOvelocity, MIOlabel);

    % Plot lane boundaries
    plotLaneBoundary(bepPlotters.LaneBoundary, laneBoundaries);

    % The recorded data was obtained at a rate of 20 frames per second.
    % Pause for 50 milliseconds for a more realistic display rate. You
    % would not need this when you process data and form tracks in this
    % loop.
    pause(0.05 - toc)
end

function [visionObjectsPos, radarObjectsPos, laneBoundaries, trackPositions, ...
    trackVelocities, trackCovariances, trackLabels, MIOlabel, MIOposition, ...
    MIOvelocity] = readDataFrame(dataFrame)
    visionObjectsPos    = dataFrame.visionObjectsPos;
    radarObjectsPos     = dataFrame.radarObjectsPos;
    laneBoundaries      = dataFrame.laneBoundaries;
    trackPositions      = dataFrame.trackPositions;
    trackVelocities     = dataFrame.trackVelocities;
    trackCovariances    = dataFrame.trackCovariances;
    trackLabels         = dataFrame.trackLabels;
    MIOlabel            = dataFrame.MIOlabel;
    MIOposition         = dataFrame.MIOposition;
    MIOvelocity         = dataFrame.MIOvelocity;
end