complementaryFilter

Orientation estimation from a complementary filter

Description

The complementaryFilter System object™ fuses accelerometer, gyroscope, and magnetometer sensor data to estimate device orientation and angular velocity.

To estimate orientation using this object:

  1. Create the complementaryFilter object and set its properties.

  2. Call the object with arguments, as if it were a function.

To learn more about how System objects work, see What Are System Objects? (MATLAB).

Creation

Description

FUSE = complementaryFilter returns a complementaryFilter System object, FUSE, for sensor fusion of accelerometer, gyroscope, and magnetometer data to estimate device orientation and angular velocity.

FUSE = complementaryFilter('ReferenceFrame',RF) returns a complementaryFilter System object that fuses accelerometer, gyroscope, and magnetometer data to estimate device orientation relative to the reference frame RF. Specify RF as 'NED' (North-East-Down) or 'ENU' (East-North-Up). The default value is 'NED'.

example

FUSE = complementaryFilter(___,Name,Value) sets each property Name to the specified Value. Unspecified properties have default values.

Properties

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Unless otherwise indicated, properties are nontunable, which means you cannot change their values after calling the object. Objects lock when you call them, and the release function unlocks them.

If a property is tunable, you can change its value at any time.

For more information on changing property values, see System Design in MATLAB Using System Objects (MATLAB).

Input sample rate of the sensor data in Hz, specified as a positive scalar.

Tunable: No

Data Types: single | double

Accelerometer gain, specified as a real scalar in the range of [0, 1]. The gain determines how much the accelerometer measurement is trusted over the gyroscope measurement for orientation estimation. This property is tunable.

Data Types: single | double

Magnetometer gain, specified as a real scalar in the range of [0, 1]. The gain determines how much the magnetometer measurement is trusted over the gyroscope measurement for orientation estimation. This property is tunable.

Data Types: single | double

Enable magnetometer input, specified as true or false.

Data Types: logical

Output orientation format, specified as 'quaternion' or 'Rotation matrix'. The size of the output depends on the output orientation format:

  • 'quaternion' –– Output is an N-by-1 quaternion.

  • 'Rotation matrix' –– Output is a 3-by-3-by-N rotation matrix.

N is the number of samples.

Data Types: char | string

Usage

Description

example

[orientation,angularVelocity] = FUSE(accelReadings,gyroReadings,magReadings) fuses accelerometer, gyroscope, and magnetometer data to compute orientation and angular velocity. To use this syntax, set the HasMagnetometer property as true.

[orientation,angularVelocity] = FUSE(accelReadings,gyroReadings) fuses accelerometer and gyroscope data to compute orientation and angular velocity. To use this syntax, set the HasMagnetometer property as false.

Input Arguments

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Accelerometer readings in the sensor body coordinate system in m/s2, specified as an N-by-3 matrix. N is the number of samples, and the three columns of accelReadings represent the [x y z] measurements. Accelerometer readings are assumed to correspond to the sample rate specified by the SampleRate property. In the filter, the gravity constant g is assumed to be 9.81 m/s2.

Data Types: single | double

Gyroscope readings in the sensor body coordinate system in rad/s, specified as an N-by-3 matrix. N is the number of samples, and the three columns of gyroReadings represent the [x y z] measurements. Gyroscope readings are assumed to correspond to the sample rate specified by the SampleRate property.

Data Types: single | double

Magnetometer readings in the sensor body coordinate system in µT, specified as an N-by-3 matrix. N is the number of samples, and the three columns of magReadings represent the [x y z] measurements. Magnetometer readings are assumed to correspond to the sample rate specified by the SampleRate property.

Data Types: single | double

Output Arguments

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Orientation that rotates quantities from the local navigation coordinate system to the body coordinate system, returned as quaternions or an array. The size and type of orientation depends on whether the OrienationFormat property is set to 'quaternion' or 'Rotation matrix':

  • 'quaternion' –– the output is an N-by-1 vector of quaternions, where N is the number of samples.

  • 'Rotation matrix' –– the output is a 3-by-3-by-N array of rotation matrices, where N is the number of samples.

Data Types: quaternion | single | double

Angular velocity expressed in the sensor body coordinate system in rad/s, returned as an N-by-3 array, where N is the number of samples.

Data Types: single | double

Object Functions

To use an object function, specify the System object as the first input argument. For example, to release system resources of a System object named obj, use this syntax:

release(obj)

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stepRun System object algorithm
releaseRelease resources and allow changes to System object property values and input characteristics
resetReset internal states of System object
cloneCreate duplicate System object
isLockedDetermine if System object is in use

Examples

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Load the rpy_9axis file, which contains recorded accelerometer, gyroscope, and magnetometer sensor data from a device oscillating in pitch (around y-axis), then yaw (around z-axis), and then roll (around x-axis). The file also contains the sample rate of the recording.

ld = load('rpy_9axis.mat');
accel = ld.sensorData.Acceleration;
gyro = ld.sensorData.AngularVelocity;
mag = ld.sensorData.MagneticField;

Create a complementary filter object with sample rate equal to the frequency of the data.

Fs  = ld.Fs;  % Hz
fuse = complementaryFilter('SampleRate', Fs);

Fuse accelerometer, gyroscope, and magnetometer data using the filter.

q = fuse(accel, gyro, mag);

Visualize the results.

plot(eulerd( q, 'ZYX', 'frame'));
title('Orientation Estimate');
legend('Z-rotation', 'Y-rotation', 'X-rotation');
ylabel('Degrees');

References

[1] Valenti, R., I. Dryanovski, and J. Xiao. "Keeping a good attitude: A quaternion-based orientation filter for IMUs and MARGs." Sensors. Vol. 15, Number 8, 2015, pp. 19302-19330.

Extended Capabilities

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

Introduced in R2019b