Not exactly clear of the detection boxes meaning in the radar from the automated driving toolbox

I have created a road scenario where the egocar travels and records the generated radar data. I have tried to experiment what every option can be set as but still I could not figure one thing. This question might be done but I do not clearly know what those boxes mean in the Birds eye plot found in the screenshot below. These can be detection but why they are only concentrated on the left side of the road that is just ahead of the ego car trajectory. For your reference, I have defined my radar as follows:

radarSensor = drivingRadarDataGenerator( ...
    'SensorIndex', 1, ...                %Sensor Identification nr, ...
    'UpdateRate', 10, ...                %Recirprocal of sample time    
    'MountingLocation', mount.loc, ... %case 4 [3.9 0.5 0]case 3[3.9 0 0] case 2[3.9 0.5 0]  case 1 [3.9 0 0], ... %in metres
    'MountingAngles', mount.angle, ...       %case 3&4 [20 0 0] case 1&2[0 0 0]Mounting rotation angles of the radar, in degrees [z_yaw, y_pitch, x_roll]    
    'HasElevation',true, ...             %Detection Reporting
    'HasRangeRate',true, ...
    'HasNoise',false,...
    'HasFalseAlarms',0,...               %an erroneous radar tgt detn from noise or other interfering signals
    'HasOcclusion', false,...            %true results in getting dets only fr radar which has a direct line of sight  
    'MaxNumReportsSource', 'Auto',...    %'MaxNumReportsSource', 'Auto', ...%auto - reports all detections or tracks property - only the first N valid dets or tracks, n is defined in 'MaxNumReports' property value
    'TargetReportFormat', 'Detections', ... %tgt reports as unclustered detns, tgt can have multiple detections
    'DetectionCoordinates', 'Sensor spherical', ... 
    'AzimuthResolution', 1, ...         %Measurement Resolution  (deg)
    'ElevationResolution', 1, ...       (deg)
    'RangeRateResolution', 0.5, ...     (m/s)
    'RangeResolution', 0.25, ...     
    'AzimuthBiasFraction',0.1,...       %Measurement Bias - %lower bound on accuracy of azimuth   
    'ElevationBiasFraction', 0.1, ...
    'RangeBiasFraction', 0.05, ...
    'RangeRateBiasFraction', 0.05, ...    
    'DetectionProbability', 0.9, ...    %Detection settings      
    'CenterFrequency', 77e9, ...        %Hz
    'FalseAlarmRate', [1e-3], ...
    'FieldOfView', [160 160], ...       %deg [azi(0,360] ele (0, 180]
    'RangeLimits', [0 150], ...         %m  [0 100e3]
    'Profiles', actorProfiles(scenario)); % structure/array that contains the physical and radar characteristics of an actor.

I would be thankful if someone sheds more light on this.

Answer 1

[Anurag]

Hi Balaji,

As per my understanding, you want to understand the reason for the concentration of the boxes being detected on the left side of the road as compared to the right side of the road.

These may be some of the reasons for issue you’re facing :

• Sensor Configuration: The radar sensor's mounting location and field of view can influence where it detects objects. It seems that the sensor is configured to have a field of view covering mainly the left side of the road.
• Sensor Placement: The placement of the radar sensor on the ego vehicle can affect its ability to detect objects in different areas. It's possible that the sensor's position is optimized for detecting objects on the left side of the road.
• Environment and Scenario: The concentration of detections might be reflective of the specific scenario you've set up. If there are more objects or interactions on the left side of the road, this could result in more detections in that area.
• Sensor Parameters: Check the parameters you've set for the radar sensor, such as detection probability, false alarm rate, and field of view. These parameters can affect how and where detections occur.

To get a better understanding of why detections are concentrated on the left side, you may want to review and possibly adjust the sensor's configuration, the scenario setup, and the characteristics of the objects in the scene. This can help ensure that the radar sensor behaves as expected and provides a more accurate representation of the environment.

Hope this helped.