imuSensor and Allan Variance
Hello everyone,
I am creating an IMU simulation using the built-in imuSensor model in MATLAB. The block includes several parameters that define IMU noise characteristics, but I do not fully understand how these parameters relate to Allan variance–derived noise coefficients.
Here is the list of gyroscope parameters available in
——————————————————————————————
gyroparams with properties:
MeasurementRange: Inf rad/s
Resolution: 0 (rad/s)/LSB
ConstantBias: [0 0 0] rad/s
AxesMisalignment: [3⨯3 double] %
NoiseDensity: [0 0 0] (rad/s)/√Hz
BiasInstability: [0 0 0] rad/s
RandomWalk: [0 0 0] (rad/s)*√Hz
NoiseType: "double-sided"
BiasInstabilityCoefficients: [1⨯1 struct]
TemperatureBias: [0 0 0] (rad/s)/°C
TemperatureScaleFactor: [0 0 0] %/°C
AccelerationBias: [0 0 0] (rad/s)/(m/s²)
——————————————————————————————
I have estimated my sensor noise parameters from Allan variance analysis, specifically:
ARW (N)
Bias Instability (B)
Rate Random Walk (K)
My goal is to correctly map these Allan variance parameters N, B, and K to the corresponding imuSensor block parameters:
NoiseDensity
BiasInstability
RandomWalk
I would appreciate clarification on how these quantities correspond mathematically and physically, and how to correctly convert Allan variance results into the parameters expected by MATLAB’s IMU sensor model.Hello everyone,
I am creating an IMU simulation using the built-in imuSensor model in MATLAB. The block includes several parameters that define IMU noise characteristics, but I do not fully understand how these parameters relate to Allan variance–derived noise coefficients.
Here is the list of gyroscope parameters available in
——————————————————————————————
gyroparams with properties:
MeasurementRange: Inf rad/s
Resolution: 0 (rad/s)/LSB
ConstantBias: [0 0 0] rad/s
AxesMisalignment: [3⨯3 double] %
NoiseDensity: [0 0 0] (rad/s)/√Hz
BiasInstability: [0 0 0] rad/s
RandomWalk: [0 0 0] (rad/s)*√Hz
NoiseType: "double-sided"
BiasInstabilityCoefficients: [1⨯1 struct]
TemperatureBias: [0 0 0] (rad/s)/°C
TemperatureScaleFactor: [0 0 0] %/°C
AccelerationBias: [0 0 0] (rad/s)/(m/s²)
——————————————————————————————
I have estimated my sensor noise parameters from Allan variance analysis, specifically:
ARW (N)
Bias Instability (B)
Rate Random Walk (K)
My goal is to correctly map these Allan variance parameters N, B, and K to the corresponding imuSensor block parameters:
NoiseDensity
BiasInstability
RandomWalk
I would appreciate clarification on how these quantities correspond mathematically and physically, and how to correctly convert Allan variance results into the parameters expected by MATLAB’s IMU sensor model. Hello everyone,
I am creating an IMU simulation using the built-in imuSensor model in MATLAB. The block includes several parameters that define IMU noise characteristics, but I do not fully understand how these parameters relate to Allan variance–derived noise coefficients.
Here is the list of gyroscope parameters available in
——————————————————————————————
gyroparams with properties:
MeasurementRange: Inf rad/s
Resolution: 0 (rad/s)/LSB
ConstantBias: [0 0 0] rad/s
AxesMisalignment: [3⨯3 double] %
NoiseDensity: [0 0 0] (rad/s)/√Hz
BiasInstability: [0 0 0] rad/s
RandomWalk: [0 0 0] (rad/s)*√Hz
NoiseType: "double-sided"
BiasInstabilityCoefficients: [1⨯1 struct]
TemperatureBias: [0 0 0] (rad/s)/°C
TemperatureScaleFactor: [0 0 0] %/°C
AccelerationBias: [0 0 0] (rad/s)/(m/s²)
——————————————————————————————
I have estimated my sensor noise parameters from Allan variance analysis, specifically:
ARW (N)
Bias Instability (B)
Rate Random Walk (K)
My goal is to correctly map these Allan variance parameters N, B, and K to the corresponding imuSensor block parameters:
NoiseDensity
BiasInstability
RandomWalk
I would appreciate clarification on how these quantities correspond mathematically and physically, and how to correctly convert Allan variance results into the parameters expected by MATLAB’s IMU sensor model. allan variance imu sensör MATLAB Answers — New Questions
