If no other tasks exist, the radar scans the space one angular cell at a time. In this example, a raster scan is used to cover the desired airspace. The search tasks can be considered as deterministic. Because of this resource allocation, a critical component when using a multifunction radar is resource management. If resources are used for tracking tasks, then those resources are not available for searching tasks until the tracking tasks are finished. In general, a radar has finite resources to spend on its tasks. While using one multifunction radar to perform multiple tasks has its advantages, it also has a higher cost and more sophisticated logic. 'Velocity',tgtvel(:,2).', 'AccelerationSource', 'Property'. KinematicTrajectory( 'SampleRate',prf, 'Position',tgtpos(:,2).'. 'Velocity',tgtvel(:,1).', 'AccelerationSource', 'Property'. KinematicTrajectory( 'SampleRate',prf, 'Position',tgtpos(:,1).'. Radarplat = platform(scene, 'Position', 'Sensors',)

'Velocity', 'AccelerationSource', 'Property'. Radartraj = kinematicTrajectory( 'SampleRate',prf, 'Position'. Scene = radarScenario( 'UpdateRate',prf) The multifunction radar uses a tracker that associates the detections to the tracks using a global nearest neighbor (GNN) algorithm. If the track has a few missed updates, the tracker deletes the track. Similarly, if no detections are assigned to a track, the track is coasted (predicted without correction). If enough detections are obtained, the track becomes confirmed. At first, a track is created with a tentative status. In most cases, whether the new track represents a true target or false target is unclear. If a detection cannot be assigned to any track already maintained by the tracker, the tracker initiates a new track. The tracker maintains a list of tracks, that is, estimates of target states in the area of interest. The detections are fed into a tracker, which performs several operations. 'OperatingFrequency',fc, 'SquintAngle',1) Monfeed = phased.MonopulseFeed( 'SensorArray',ant, 'PropagationSpeed',c.

Tvg = phased.TimeVaryingGain( 'RangeLoss',rngloss, 'ReferenceLoss',refloss) Mf = phased.MatchedFilter( 'Coefficients',mfcoeff, 'GainOutputPort', true)

Raster scan code in matlab