The RPEKF is a special type of filter that can be initialized using angle-only measurements, that is, azimuth and/or elevation. When the 'Frame' is set to 'spherical'and 'HasRange' is set to 'false', the detection has [azimuth elevation] measurements. Specify the measurement parameters appropriately to define an angle-only measurement with no range information.
measParam = struct('Frame','spherical','HasRange',false,'OriginPosition',[100;10;0]);
The objectDetection class defines an interface to the angle-only detection measured by the sensor. The MeasurementParameters field of objectDetection carries information about what the sensor is measuring.
detection = objectDetection(0,[30;30],'MeasurementParameters',measParam,'MeasurementNoise',2*eye(2));
The initrpekf function uses the angle-only detection to initialize the RPEKF.
rpekf = initrpekf(detection) %#ok
rpekf =
trackingGSF with properties:
State: [6x1 double]
StateCovariance: [6x6 double]
TrackingFilters: {6x1 cell}
ModelProbabilities: [6x1 double]
MeasurementNoise: [2x2 double]
You can also initialize the RPEKF with 10 filters and to operate within the range limits of [1000, 10,000] scenario units.
rangeLimits = [1000 10000];
numFilters = 10;
rpekf = initrpekf(detection, numFilters, rangeLimits)
rpekf =
trackingGSF with properties:
State: [6x1 double]
StateCovariance: [6x6 double]
TrackingFilters: {10x1 cell}
ModelProbabilities: [10x1 double]
MeasurementNoise: [2x2 double]
You can also specify the initrpekf function as a FilterInitializationFcn to the trackerGNN object.
funcHandle = @(detection)initrpekf(detection,numFilters,rangeLimits)
funcHandle = function_handle with value:
@(detection)initrpekf(detection,numFilters,rangeLimits)
tracker = trackerGNN('FilterInitializationFcn',funcHandle)
tracker =
trackerGNN with properties:
TrackerIndex: 0
FilterInitializationFcn: [function_handle]
Assignment: 'MatchPairs'
AssignmentThreshold: [30 Inf]
MaxNumTracks: 100
MaxNumSensors: 20
OOSMHandling: 'Terminate'
TrackLogic: 'History'
ConfirmationThreshold: [2 3]
DeletionThreshold: [5 5]
HasCostMatrixInput: false
HasDetectableTrackIDsInput: false
StateParameters: [1x1 struct]
NumTracks: 0
NumConfirmedTracks: 0
Visualize the filter.
tp = theaterPlot;
componentPlot = trackPlotter(tp,'DisplayName','Individual sums','MarkerFaceColor','r');
sumPlot = trackPlotter(tp,'DisplayName','Mixed State','MarkerFaceColor','g');
indFilters = rpekf.TrackingFilters;
pos = zeros(numFilters,3);
cov = zeros(3,3,numFilters);
for i = 1:numFilters
pos(i,:) = indFilters{i}.State(1:2:end);
cov(1:3,1:3,i) = indFilters{i}.StateCovariance(1:2:end,1:2:end);
end
componentPlot.plotTrack(pos,cov);
mixedPos = rpekf.State(1:2:end)';
mixedPosCov = rpekf.StateCovariance(1:2:end,1:2:end);
sumPlot.plotTrack(mixedPos,mixedPosCov);
