Desktop_调度_场景生成_源码

%% Air Traffic Control % This example shows how to generate an air traffic control scenario, % simulate radar detections from an airport surveillance radar (ASR), and % configure a global nearest neighbor (GNN) tracker to track the simulated % targets using the radar detections. This enables you to evaluate % different target scenarios, radar requirements, and tracker % configurations without needing access to costly aircraft or equipment. % This example covers the entire synthetic data workflow. % Copyright 2017-2019 The MathWorks, Inc. %% Air Traffic Control Scenario % Simulate an air traffic control (ATC) tower and moving targets % in the scenario as _platforms_. Simulation of the motion of the platforms % in the scenario is managed by |trackingScenario|. % % Create a |trackingScenario| and add the ATC tower to the scenario. % Create tracking scenario scenario = trackingScenario; % Add a stationary platform to model the ATC tower tower = platform(scenario); %% Airport Surveillance Radar % Add an airport surveillance radar (ASR) to the ATC tower. A typical ATC % tower has a radar mounted 15 meters above the ground. This radar scans % mechanically in azimuth at a fixed rate to provide 360 degree coverage in % the vicinity of the ATC tower. Common specifications for an ASR are % listed: % % * Sensitivity: 0 dBsm @ 111 km % * Mechanical Scan: Azimuth only % * Mechanical Scan Rate: 12.5 RPM % * Electronic Scan: None % * Field of View: 1.4 deg azimuth, 10 deg elevation % * Azimuth Resolution: 1.4 deg % * Range Resolution: 135 m % % Model the ASR with the above specifications using the % |monostaticRadarSensor|. rpm = 12.5; fov = [1.4;10]; scanrate = rpm*360/60; % deg/s updaterate = scanrate/fov(1); % Hz radar = monostaticRadarSensor(1, 'Rotator', ... 'UpdateRate', updaterate, ... % Hz 'FieldOfView', fov, ... % [az;el] deg 'MaxMechanicalScanRate', scanrate, ... % deg/sec 'AzimuthResolution', fov(1), ... % deg 'ReferenceRange', 111e3, ... % m 'ReferenceRCS', 0, ... % dBsm 'RangeResolution', 135, ... % m 'HasINS', true, ... 'DetectionCoordinates', 'Scenario'); % Mount radar at the top of the tower radar.MountingLocation = [0 0 -15]; tower.Sensors = radar; %% % Tilt the radar so that it surveys a region beginning at 2 degrees above % the horizon. To do this, enable elevation and set the mechanical scan % limits to span the radar's elevation field of view beginning at 2 degrees % above the horizon. Because |trackingScenario| uses a North-East-Down % (NED) coordinate frame, negative elevations correspond to points above % the horizon. % Enable elevation scanning radar.HasElevation = true; % Set mechanical elevation scan to begin at 2 degrees above the horizon elFov = fov(2); tilt = 2; % deg radar.MechanicalScanLimits(2,:) = [-fov(2) 0]-tilt; % deg %% % Set the elevation field of view to be slightly larger than the elevation % spanned by the scan limits. This prevents raster scanning in elevation % and tilts the radar to point in the middle of the elevation scan limits. radar.FieldOfView(2) = elFov+1e-3; %% % The |monostaticRadarSensor| models range and elevation bias due to % atmospheric refraction. These biases become more pronounced at lower % altitudes and for targets at long ranges. Because the index of refraction % changes (decreases) with altitude, the radar signals propagate along a % curved path. This results in the radar observing targets at altitudes % which are higher than their true altitude and at ranges beyond their % line-of-sight range. %% % Add three airliners within the ATC control sector. One airliner % approaches the ATC from a long range, another departs, and the third is % flying tangential to the tower. Model the motion of these airliners over % a 60 second interval. % % |trackingScenario| uses a North-East-Down (NED) coordinate frame. When % defining the waypoints for the airliners below, the z-coordinate % corresponds to down, so heights above the ground are set to negative % values. % Duration of scenario sceneDuration = 60; % s % Inbound airliner ht = 3e3; spd = 900*1e3/3600; % m/s wp = [-5e3 -40e3 -ht;-5e3 -40e3+spd*sceneDuration -ht]; traj = waypointTrajectory('Waypoints',wp,'TimeOfArrival',[0 sceneDuration]); platform(scenario,'Trajectory', traj); % Outbound airliner ht = 4e3; spd = 700*1e3/3600; % m/s wp = [20e3 10e3 -ht;20e3+spd*sceneDuration 10e3 -ht]; traj = waypointTrajectory('Waypoints',wp,'TimeOfArrival',[0 sceneDuration]); platform(scenario,'Trajectory', traj); % Tangential airliner ht = 4e3; spd = 300*1e3/3600; % m/s wp = [-20e3 -spd*sceneDuration/2 -ht;-20e3 spd*sceneDuration/2 -ht]; traj = waypointTrajectory('Waypoints',wp,'TimeOfArrival',[0 sceneDuration]); platform(scenario,'Trajectory', traj); % Create a display to show the true, measured, and tracked positions of the % airliners. [theater,fig] = helperATCExample('Create Display',scenario); helperATCExample('Update Display',theater,scenario,tower); %% GNN Tracker % Create a |trackerGNN| to form tracks from the radar detections generated % from the three airliners. Update the tracker with the detections % generated after the completion of a full 360 degree scan in azimuth. % % The tracker uses the |initFilter| supporting function to initialize a % constant velocity extended Kalman filter for each new track. |initFilter| % modifies the filter returned by |initcvekf| to match the target % velocities and tracker update interval. tracker = trackerGNN( ... 'Assignment', 'Auction', ... 'AssignmentThreshold',50, ... 'FilterInitializationFcn',@initFilter); %% Simulate and Track Airliners % The following loop advances the platform positions until the end of the % scenario has been reached. For each step forward in the scenario, the % radar generates detections from targets in its field of view. The tracker % is updated with these detections after the radar has completed a 360 % degree scan in azimuth. % Set simulation to advance at the update rate of the radar scenario.UpdateRate = radar.UpdateRate; % Create a buffer to collect the detections from a full scan of the radar scanBuffer = {}; % Initialize the track array tracks = []; % Set random seed for repeatable results rng(2020) while advance(scenario) && ishghandle(fig) % Generate detections on targets in the radar's current field of view [dets,config] = detect(scenario); scanBuffer = [scanBuffer;dets]; %#ok<AGROW> % Update tracks when a 360 degree scan is complete simTime = scenario.SimulationTime; if config.IsScanDone % Update tracker tracks = tracker(scanBuffer,simTime); % Clear scan buffer for next scan scanBuffer = {}; elseif isLocked(tracker) % Predict tracks to the current simulation time tracks = predictTracksToTime(tracker,'confirmed',simTime); end % Update display with current beam position, buffered detections, and % track positions helperATCExample('Take Snapshots',fig,scenario,config); helperATCExample('Update Display',theater,scenario,tower,scanBuffer,tracks); helperATCExample('Take Snapshots',fig,scenario,config); end helperATCExample('Take Snapshots',fig,scenario,config); %% % Use |helperATCExample| to show the first snapshot taken at the % completion of the radar's second scan. helperATCExample('Show Snapshots',1); %% % The preceding figure shows the scenario at the end of the radar's second % 360 degree scan. Radar detections, shown as blue dots, are present for % each of the simulated airliners. At this point, the tracker has already % been updated by one complete scan of the radar. Internally, the tracker % has initialized tracks for each of the airliners. These tracks will be % shown after the update following this scan, when the tracks are promoted % to confirmed, meeting the t