evaluateBatch
Description
[
returns the track summary, truth summary, and the assignment history based on a log of
tracks and a log of truths using the trackSummary
,truthSummary
,assignHistory
] = evaluateBatch(assignmentMetric
,tracklog
,truthlog
)trackingAssignmentMetric
object. The
function places tracks and truths of the same time in a group and performs assignment
between the tracks and truths in each group.
Tip
This function ignores the MaxUnreportedPeriod
property of the
trackAssignmentMetrics
object. The function computes a maximum unreported
period value based on the tracklog
and
truthlog
inputs and uses the calculated value to delete tracks
and truths if they are not updated within the maximum period.
Examples
Evaluate Track Metrics for Recorded Data
First, load the stored track data.
load trackmetricex tracklog truthlog
Create a trackAssignmentMetric
object.
tam = trackAssignmentMetrics;
Use the evaluateBatch
object function to obtain the track summary, the truth summary, and the assignment history.
[trackSummary,truthSummary,assignHistory] = evaluateBatch(tam,tracklog,truthlog)
trackSummary = struct with fields:
TotalNumTracks: 4
NumFalseTracks: 0
MaxSwapCount: 3
TotalSwapCount: 5
MaxDivergenceCount: 8
TotalDivergenceCount: 17
MaxDivergenceLength: 314
TotalDivergenceLength: 434
MaxRedundancyCount: 1
TotalRedundancyCount: 3
MaxRedundancyLength: 169
TotalRedundancyLength: 199
MaxTimeBetweenReports: 0.0187
MeanTimeBetweenReports: 0.0187
truthSummary = struct with fields:
TotalNumTruths: 2
NumMissingTruths: 0
MaxEstablishmentLength: 84
TotalEstablishmentLength: 140
MaxBreakCount: 4
TotalBreakCount: 7
MaxBreakLength: 645
TotalBreakLength: 813
MaxTimeBetweenReports: 0.0187
MeanTimeBetweenReports: 0.0187
assignHistory=2678×1 struct array with fields:
Time
TrackIDs
TruthIDs
Next, create a trackErrorMetrics
object.
tem = trackErrorMetrics;
Use the evaluateBatch
object function to obtain the cumulative track and truth error metric tables as well as the track and truth error history tables.
[cumTrackError,cumTruthError,trackErrorHistory,truthErrorHistory] = evaluateBatch(tem,tracklog,truthlog,assignHistory)
cumTrackError=4×5 table
TrackID posRMS velRMS posANEES velANEES
_______ ______ ______ ________ ________
1 117.69 43.951 0.58338 0.44127
2 129.7 42.8 0.81094 0.42509
6 371.35 87.083 4.5208 1.6952
8 130.45 53.914 1.0448 0.44813
cumTruthError=2×5 table
TruthID posRMS velRMS posANEES velANEES
_______ ______ ______ ________ ________
2 258.21 65.078 2.2514 0.93359
3 134.41 48.253 0.96314 0.49183
trackErrorHistory=4600×6 table
Time TrackID posRMS velRMS posANEES velANEES
______ _______ ______ ______ ________ ________
1.064 1 30.104 12.092 0.049206 0.024983
1.0827 1 29.996 12.092 0.035699 0.022217
1.1013 1 29.89 12.092 0.035276 0.022217
1.12 1 29.785 12.092 0.034862 0.022217
1.1387 1 29.681 12.092 0.034458 0.022217
1.1573 1 29.579 12.092 0.034065 0.022217
1.176 1 29.478 12.092 0.033682 0.022217
1.1947 1 29.379 12.092 0.03331 0.022217
1.2133 1 29.281 12.092 0.032948 0.022217
1.232 1 29.184 12.092 0.032597 0.022217
1.2507 1 29.089 12.092 0.032257 0.022217
1.2693 1 28.995 12.092 0.031927 0.022217
1.288 1 28.902 12.092 0.031608 0.022217
1.3067 1 28.812 12.092 0.0313 0.022217
1.3253 1 28.722 12.092 0.031003 0.022217
1.344 1 28.634 12.092 0.030715 0.022217
⋮
truthErrorHistory=4403×6 table
Time TruthID posRMS velRMS posANEES velANEES
______ _______ ______ ______ ________ ________
1.064 2 30.104 12.092 0.049206 0.024983
1.0827 2 29.996 12.092 0.035699 0.022217
1.1013 2 29.89 12.092 0.035276 0.022217
1.12 2 29.785 12.092 0.034862 0.022217
1.1387 2 29.681 12.092 0.034458 0.022217
1.1573 2 29.579 12.092 0.034065 0.022217
1.176 2 29.478 12.092 0.033682 0.022217
1.1947 2 29.379 12.092 0.03331 0.022217
1.2133 2 29.281 12.092 0.032948 0.022217
1.232 2 29.184 12.092 0.032597 0.022217
1.2507 2 29.089 12.092 0.032257 0.022217
1.2693 2 28.995 12.092 0.031927 0.022217
1.288 2 28.902 12.092 0.031608 0.022217
1.3067 2 28.812 12.092 0.0313 0.022217
1.3253 2 28.722 12.092 0.031003 0.022217
1.344 2 28.634 12.092 0.030715 0.022217
⋮
Input Arguments
assignmentMetric
— Track assignment metrics object
trackAssignmentMetrics
System object
Track assignment metrics object, specified as a trackAssignmentMetrics
System object™.
tracklog
— Recorded track log
array of objects or structures | cell array of objects or structures
Recorded track log, specified as an array of objects or structures. Alternately,
you can specify it as a cell array of objects or structures. Each object or structure
must have an UpdateTime
property or field, respectively.
If the DistanceFunctionFormat
property is specified as
'built-in'
, each object must be an objectTrack
object and each
structure must be a track structure. The fields of the track structure should be the
same as the properties of the objectTrack
object. The track structure
must at least have the State
, StateCovariance
,
TrackID
, and UpdateTime
fields.
truthlog
— Recorded truth log
array of structures | cell array of structures | trackScenarioRecording
object
Recorded truth log, specified as an array of structures, a cell array of
structures, or a trackingScenarioRecording
object. Each structure must have a
Time
field.
If the DistanceFunctionFormat
property is specified as
'built-in'
, each structure must have at least these
fields.
Field | Description |
---|---|
Time | Time of the truth, specified as a nonnegative scalar. |
PlatformID | Unique identifier for the platform, specified as a positive integer. This is a required field with no default value. |
Position | Position of the platform in scenario coordinates, specified as a real-valued 1-by-3 row vector.
|
Velocity | Velocity of the platform in scenario coordinates, specified as a
real-valued 1-by-3 row vector. Units are meters per second. The default
value is |
You can use the platformPoses
function of the trackingScenario
object to generate this structure except the
Time
field, which you can obtain via the
SimulationTime
property of the trackingScenario
object.
Output Arguments
trackSummary
— Track assignment summary
structure
Track assignment summary, returned as a structure. The structure has these fields.
Field | Description |
TotalNumTracks | The total number of unique track identifiers encountered |
NumFalseTracks | The number of tracks never assigned to any truth |
MaxSwapCount | Maximum number of track swaps of each track. A track swap occurs whenever a track is assigned to a different truth. |
TotalSwapCount | Total number of track swaps of each track. A track swap occurs whenever a track is assigned to a different truth. |
MaxDivergenceCount | Maximum number of divergences. A track is divergent when the result
of the |
TotalDivergenceCount | Total number of divergences. A track is divergent when the result of the divergence distance function is greater than the divergence threshold. |
MaxDivergenceLength | Maximum number of updates during which each track was in a divergent state |
TotalDivergenceLength | Total number of updates during which each track was in a divergent state |
MaxRedundancyCount | The maximum number of additional tracks assigned to the same truth |
TotalRedundancyCount | The total number of additional tracks assigned to the same truth |
MaxRedundancyLength | Maximum number of updates during which each track was in a redundant state |
TotalRedundancyLength | Total number of updates during which each track was in a redundant state |
MaxTimeBetweenReports | The maximum time interval between adjacent track updates to the metric
across all tracks. The field is returned as NaN if there
has been only one update to the metric. |
MeanTimeBetweenReports | The average time interval between adjacent track updates to the metric
across all tracks. The field is returned as NaN if there
has been only one update to the metric. |
truthSummary
— Truth assignment summary
structure
Truth assignment summary, returned as a structure. The structure has these fields.
Field | Description |
TotalNumTruths | The total number of unique truth identifiers encountered |
NumMissingTruths | The number of truths never established with any track |
MaxEstablishmentLength | Maximum number of updates before a truth was associated with any track while inside the coverage area. The lengths of missing truths do not count toward this summary metric. |
TotalEstablishmentLength | Total number of updates before a truth was associated with any track while inside the coverage area. The lengths of missing truths do not count toward this summary metric. |
MaxBreakCount | Maximum number of times each truth was unassociated with any track after being established. |
TotalBreakCount | Total number of times each truth was unassociated with any track after being established. |
MaxBreakLength | Maximum number of updates during which each truth was in a broken state |
TotalBreakLength | Total number of updates during which each truth was in a broken state |
MaxTimeBetweenReports | The maximum time interval between adjacent truth updates to the metric
across all truths. The field is returned as NaN if there
has been only one update to the metric. |
MeanTimeBetweenReports | The average time interval between adjacent truth updates to the metric
across all truths. The field is returned as NaN if there
has been only one update to the metric. |
assignHistory
— Assignment history
array of structures
Assignment history, returned as an array of structures. Each structure has these fields.
Field | Description |
---|---|
Time | Time of assignment, returned as a nonnegative scalar. |
TrackIDs | IDs of tracks, returned as a vector of track IDs. |
TruthIDs | IDs of truths, returned as a vector of truth IDs. |
The corresponding tracks and truths from the TrackIDs
and TruthIDs
fields are assigned to each other.
Data Types: struct
Version History
Introduced in R2023bR2024a: Performance improvement
evaluateBatch
shows improved performance for longer input logs with
at least 1000 elements. For example, this code is about 5x faster than in the previous
release:
function t = timingTest [truthlog,tracklog] = createlonglogs(1000); tam = trackAssignmentMetrics(); tic; evaluateBatch(tam,tracklog,truthlog); toc end function [truths,tracks]=createlonglogs(numSteps) v = ones(1,3); t1 = [struct("PlatformID",1,"Position",v,"Velocity",v,"Time",1);... struct("PlatformID",2,"Position",10*v,"Velocity",10*v,"Time",1)]; t2 = [objectTrack(TrackID=1,state=ones(6,1));... objectTrack(TrackID=2,state=10*ones(6,1))]; truths = cell(numSteps,1); tracks = cell(numSteps,1); for i=1:numSteps truths{i} = t1; truths{i}(1).Time = i; truths{i}(2).Time = i; tracks{i} = t2; tracks{i}(1).UpdateTime = i; tracks{i}(2).UpdateTime = i; end end
The approximate execution times are:
R2023b: 9.6 s
R2024a: 1.8 s
The code was timed on a Windows 11, AMD(R) EPYC 74F3 24-Core Processor @ 3.19 GHz test
system by calling the timingTest
function.
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