ctrectmeas

Measurement function of constant turn-rate motion model for rectangular targets

collapse all in page

Syntax

measurements = ctrectmeas(states,detections)

Description

measurements = ctrectmeas(states,detections) returns the expected measurements from the current rectangular states and detections for an extended target based on the constant turn-rate motion model. The gmphd object can use ctrectmeas as its MeasurementFcn.

example

Examples

collapse all

Open Live Script

Load detections and truth generated from a rectangular target.

load('rectangularTargetDetections.mat','detections','truthState');

Generate expected detections from the target's rectangular state and actual detections using ctrectmeas.

tgtState = [3;48;0;60;0;5;1.9];
zExp = ctrectmeas(tgtState,detections);

Set up visualization environment using theaterPlot.

theaterP = theaterPlot;
stateP = trackPlotter(theaterP,'DisplayName','State','MarkerFaceColor','g');
truthP = trackPlotter(theaterP,'DisplayName','Truth','MarkerFaceColor', 'b');
detP = detectionPlotter(theaterP,'DisplayName','Detections','MarkerFaceColor','r');
expDetP = detectionPlotter(theaterP,'DisplayName','Expected Detections','MarkerFaceColor','y');
l = legend(theaterP.Parent);
l.AutoUpdate = 'on';
hold on;
assignP = plot(theaterP.Parent,NaN,NaN,'-.','DisplayName','Association');

Plot actual and expected detections.

inDets = [detections{:}];
inMeas = horzcat(inDets.Measurement);
detP.plotDetection(inMeas');

zExpPlot = reshape(zExp,3,[]);
expDetP.plotDetection(zExpPlot');

Plot association lines.

zLines = nan(2,numel(detections)*3);
zLines(1,1:3:end) = zExpPlot(1,:);
zLines(2,1:3:end) = zExpPlot(2,:);
zLines(1,2:3:end) = inMeas(1,:);
zLines(2,2:3:end) = inMeas(2,:);
assignP.XData = zLines(1,:);
assignP.YData = zLines(2,:);

Plot truth and state.

truthPos = [truthState(1:2);0];
truthDims = struct('Length',truthState(6),...
    'Width',truthState(7),...
    'Height', 0,...
    'OriginOffset', [0 0 0]);
truthOrient = quaternion([truthState(4) 0 0],'eulerd', 'ZYX','frame');
truthP.plotTrack(truthPos',truthDims,truthOrient);

statePos = [tgtState(1:2);0];
stateDims = struct('Length',tgtState(6),...
    'Width',tgtState(7),...
    'Height',0,...
    'OriginOffset', [0 0 0]);
stateOrient = quaternion([tgtState(4) 0 0],'eulerd', 'ZYX','frame');
stateP.plotTrack(statePos', stateDims, stateOrient);

Figure contains an axes object. The axes object with xlabel X (m), ylabel Y (m) contains 5 objects of type line. One or more of the lines displays its values using only markers These objects represent State, Truth, Detections, Expected Detections, Association.

Input Arguments

collapse all

Current rectangular states, specified as a 7-by-N real-valued matrix, where N is the number of states. The seven-dimensional rectangular target state is defined as [x; y; s; θ; ω; L; W]:

VariableMeaning Unit
x

Position of the rectangle center in x direction

m
y

Position of the rectangle center in y direction

m
s

Speed in the heading direction

m/s
θ

Orientation angle of the rectangle with respect to x direction

degree
ω

Turn-rate

degree/s
L

Length of the rectangle

m
W

Width of the rectangle

m

Example: [1;2;2;30;1;4.7;1.8]

Data Types: single | double

Detections of target, specified as a 1-by-M cell array of objectDetection objects. The MeasurementParameters property (that specifies the transformation from the state-space to measurement-space) for each object must be the same for all the detections in the cell array.

Output Arguments

collapse all

Expected measurements, returned as a P-by-N-by-M real-valued array. P is the dimension of each measurement specified in the detections input, N is the number of states specified in the states input, and M is the number of detections specified in the detections input.

Extended Capabilities

expand all

C/C++ Code Generation
Generate C and C++ code using MATLAB® Coder™.

Version History

Introduced in R2019b

See Also

| | | | | |