perturb
Apply perturbations to object
Syntax
Description
applies the perturbations defined on the object, offsets
= perturb(obj
)obj
and returns the
offset values. You can define perturbations on the object by using the perturbations
function.
Examples
Define a waypoint trajectory. By default, this trajectory contains two waypoints.
traj = waypointTrajectory
traj = waypointTrajectory with properties: SampleRate: 100 SamplesPerFrame: 1 Waypoints: [2×3 double] TimeOfArrival: [2×1 double] Velocities: [2×3 double] Course: [2×1 double] GroundSpeed: [2×1 double] ClimbRate: [2×1 double] Orientation: [2×1 quaternion] AutoPitch: 0 AutoBank: 0 ReferenceFrame: 'NED'
Define perturbations on the Waypoints
property and the TimeOfArrival
property.
rng(2020); perturbs1 = perturbations(traj,'Waypoints','Normal',1,1)
perturbs1=2×3 table
Property Type Value
_______________ ________ __________________
"Waypoints" "Normal" {[ 1]} {[ 1]}
"TimeOfArrival" "None" {[NaN]} {[NaN]}
perturbs2 = perturbations(traj,'TimeOfArrival','Selection',{[0;1],[0;2]})
perturbs2=2×3 table
Property Type Value
_______________ ___________ _______________________________
"Waypoints" "Normal" {[ 1]} {[ 1]}
"TimeOfArrival" "Selection" {1×2 cell} {[0.5000 0.5000]}
Perturb the trajectory.
offsets = perturb(traj)
offsets=2×1 struct array with fields:
Property
Offset
PerturbedValue
The Waypoints
property and the TimeOfArrival
property have changed.
traj.Waypoints
ans = 2×3
1.8674 1.0203 0.7032
2.3154 -0.3207 0.0999
traj.TimeOfArrival
ans = 2×1
0
2
Create an insSensor
object.
sensor = insSensor
sensor = insSensor with properties: MountingLocation: [0 0 0] m RollAccuracy: 0.2 deg PitchAccuracy: 0.2 deg YawAccuracy: 1 deg PositionAccuracy: [1 1 1] m VelocityAccuracy: 0.05 m/s AccelerationAccuracy: 0 m/s² AngularVelocityAccuracy: 0 deg/s TimeInput: 0 RandomStream: 'Global stream'
Define the perturbation on the RollAccuracy
property as three values with an equal possibility each.
values = {0.1 0.2 0.3}
values=1×3 cell array
{[0.1000]} {[0.2000]} {[0.3000]}
probabilities = [1/3 1/3 1/3]
probabilities = 1×3
0.3333 0.3333 0.3333
perturbations(sensor,'RollAccuracy','Selection',values,probabilities)
ans=7×3 table
Property Type Value
_________________________ ___________ ______________________________________
"RollAccuracy" "Selection" {1×3 cell} {[0.3333 0.3333 0.3333]}
"PitchAccuracy" "None" {[ NaN]} {[ NaN]}
"YawAccuracy" "None" {[ NaN]} {[ NaN]}
"PositionAccuracy" "None" {[ NaN]} {[ NaN]}
"VelocityAccuracy" "None" {[ NaN]} {[ NaN]}
"AccelerationAccuracy" "None" {[ NaN]} {[ NaN]}
"AngularVelocityAccuracy" "None" {[ NaN]} {[ NaN]}
Perturb the sensor
object using the perturb function.
rng(2020) perturb(sensor); sensor
sensor = insSensor with properties: MountingLocation: [0 0 0] m RollAccuracy: 0.5 deg PitchAccuracy: 0.2 deg YawAccuracy: 1 deg PositionAccuracy: [1 1 1] m VelocityAccuracy: 0.05 m/s AccelerationAccuracy: 0 m/s² AngularVelocityAccuracy: 0 deg/s TimeInput: 0 RandomStream: 'Global stream'
The RollAccuracy
is perturbed to 0.5
deg.
Create an imuSensor
object and show its perturbable properties.
imu = imuSensor; perturbations(imu)
ans=17×3 table
Property Type Value
______________________________________ ______ __________________
"Accelerometer.MeasurementRange" "None" {[NaN]} {[NaN]}
"Accelerometer.Resolution" "None" {[NaN]} {[NaN]}
"Accelerometer.ConstantBias" "None" {[NaN]} {[NaN]}
"Accelerometer.NoiseDensity" "None" {[NaN]} {[NaN]}
"Accelerometer.BiasInstability" "None" {[NaN]} {[NaN]}
"Accelerometer.RandomWalk" "None" {[NaN]} {[NaN]}
"Accelerometer.TemperatureBias" "None" {[NaN]} {[NaN]}
"Accelerometer.TemperatureScaleFactor" "None" {[NaN]} {[NaN]}
"Gyroscope.MeasurementRange" "None" {[NaN]} {[NaN]}
"Gyroscope.Resolution" "None" {[NaN]} {[NaN]}
"Gyroscope.ConstantBias" "None" {[NaN]} {[NaN]}
"Gyroscope.NoiseDensity" "None" {[NaN]} {[NaN]}
"Gyroscope.BiasInstability" "None" {[NaN]} {[NaN]}
"Gyroscope.RandomWalk" "None" {[NaN]} {[NaN]}
"Gyroscope.TemperatureBias" "None" {[NaN]} {[NaN]}
"Gyroscope.TemperatureScaleFactor" "None" {[NaN]} {[NaN]}
⋮
Specify the perturbation for the NoiseDensity
property of the accelerometer as a uniform distribution.
perturbations(imu,'Accelerometer.NoiseDensity', ... 'Uniform',1e-5,1e-3);
Specify the perturbation for the RandomWalk
property of the gyroscope as a truncated normal distribution.
perts = perturbations(imu,'Gyroscope.RandomWalk', ... 'TruncatedNormal',2,1e-5,0,Inf);
Load prerecorded IMU data.
load imuSensorData.mat
numSamples = size(orientations);
Simulate the imuSensor
three times with different perturbation realizations.
rng(2021); % For repeatable results numRuns = 3; colors = ['b' 'r' 'g']; for idx = 1:numRuns % Clone IMU to maintain original values imuCopy = clone(imu); % Perturb noise values offsets = perturb(imuCopy); % Obtain the measurements [accelReadings,gyroReadings] = imuCopy(accelerations,angularVelocities,orientations); % Plot the results plot(times,gyroReadings(:,3),colors(idx)); hold on; end xlabel('Time (s)') ylabel('Z-Component of Gyro Readings (rad/s)') legend("First Pass","Second Pass","Third Pass"); hold off
Input Arguments
Object for perturbation, specified as an object. The objects that you can perturb include:
Output Arguments
Property offsets, returned as an array of structures. Each structure contains these fields:
Field Name | Description |
---|---|
Property | Name of perturbed property |
Offset | Offset values applied in the perturbation |
PerturbedValue | Property values after the perturbation |
Version History
Introduced in R2020b
See Also
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