Kalman-Filter-Based Orientation Determination Using Inertial/Magnetic Sensors: Observability Analysis and Performance Evaluation
In this paper we present a quaternion-based Extended Kalman Filter (EKF) for estimating the three-dimensional orientation of a rigid body. The EKF exploits the measurements from an Inertial Measurement Unit (IMU) that is integrated with a tri-axial magnetic sensor. Magnetic disturbances and gyro bia...
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| Format: | Article |
| Language: | English |
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MDPI AG
2011-09-01
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| Series: | Sensors |
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| Online Access: | http://www.mdpi.com/1424-8220/11/10/9182/ |
| _version_ | 1798002804442267648 |
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| author | Angelo Maria Sabatini |
| author_facet | Angelo Maria Sabatini |
| author_sort | Angelo Maria Sabatini |
| collection | DOAJ |
| description | In this paper we present a quaternion-based Extended Kalman Filter (EKF) for estimating the three-dimensional orientation of a rigid body. The EKF exploits the measurements from an Inertial Measurement Unit (IMU) that is integrated with a tri-axial magnetic sensor. Magnetic disturbances and gyro bias errors are modeled and compensated by including them in the filter state vector. We employ the observability rank criterion based on Lie derivatives to verify the conditions under which the nonlinear system that describes the process of motion tracking by the IMU is observable, namely it may provide sufficient information for performing the estimation task with bounded estimation errors. The observability conditions are that the magnetic field, perturbed by first-order Gauss-Markov magnetic variations, and the gravity vector are not collinear and that the IMU is subject to some angular motions. Computer simulations and experimental testing are presented to evaluate the algorithm performance, including when the observability conditions are critical. |
| first_indexed | 2024-04-11T11:57:52Z |
| format | Article |
| id | doaj.art-d47687456c8e44c6a2b64021fbae85dd |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-11T11:57:52Z |
| publishDate | 2011-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-d47687456c8e44c6a2b64021fbae85dd2022-12-22T04:25:05ZengMDPI AGSensors1424-82202011-09-0111109182920610.3390/s111009182Kalman-Filter-Based Orientation Determination Using Inertial/Magnetic Sensors: Observability Analysis and Performance EvaluationAngelo Maria SabatiniIn this paper we present a quaternion-based Extended Kalman Filter (EKF) for estimating the three-dimensional orientation of a rigid body. The EKF exploits the measurements from an Inertial Measurement Unit (IMU) that is integrated with a tri-axial magnetic sensor. Magnetic disturbances and gyro bias errors are modeled and compensated by including them in the filter state vector. We employ the observability rank criterion based on Lie derivatives to verify the conditions under which the nonlinear system that describes the process of motion tracking by the IMU is observable, namely it may provide sufficient information for performing the estimation task with bounded estimation errors. The observability conditions are that the magnetic field, perturbed by first-order Gauss-Markov magnetic variations, and the gravity vector are not collinear and that the IMU is subject to some angular motions. Computer simulations and experimental testing are presented to evaluate the algorithm performance, including when the observability conditions are critical.http://www.mdpi.com/1424-8220/11/10/9182/ambulatory human motion trackingorientation determinationinertial measurement unitExtended Kalman filterLie derivativesobservability of nonlinear systems |
| spellingShingle | Angelo Maria Sabatini Kalman-Filter-Based Orientation Determination Using Inertial/Magnetic Sensors: Observability Analysis and Performance Evaluation Sensors ambulatory human motion tracking orientation determination inertial measurement unit Extended Kalman filter Lie derivatives observability of nonlinear systems |
| title | Kalman-Filter-Based Orientation Determination Using Inertial/Magnetic Sensors: Observability Analysis and Performance Evaluation |
| title_full | Kalman-Filter-Based Orientation Determination Using Inertial/Magnetic Sensors: Observability Analysis and Performance Evaluation |
| title_fullStr | Kalman-Filter-Based Orientation Determination Using Inertial/Magnetic Sensors: Observability Analysis and Performance Evaluation |
| title_full_unstemmed | Kalman-Filter-Based Orientation Determination Using Inertial/Magnetic Sensors: Observability Analysis and Performance Evaluation |
| title_short | Kalman-Filter-Based Orientation Determination Using Inertial/Magnetic Sensors: Observability Analysis and Performance Evaluation |
| title_sort | kalman filter based orientation determination using inertial magnetic sensors observability analysis and performance evaluation |
| topic | ambulatory human motion tracking orientation determination inertial measurement unit Extended Kalman filter Lie derivatives observability of nonlinear systems |
| url | http://www.mdpi.com/1424-8220/11/10/9182/ |
| work_keys_str_mv | AT angelomariasabatini kalmanfilterbasedorientationdeterminationusinginertialmagneticsensorsobservabilityanalysisandperformanceevaluation |