The aiding of a low-cost strapdown inertial measurement unit using vehicle model constraints for land vehicle applications
This paper presents a new method for improving the accuracy of inertial measurement units (IMUs) mounted on land vehicles. The algorithm exploits nonholonomic constraints that govern the motion of a vehicle on a surface to obtain velocity observation measurements which aid in the estimation of the a...
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| Published in | IEEE transactions on robotics and automation Vol. 17; no. 5; pp. 731 - 747 |
|---|---|
| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
New York
IEEE
01.10.2001
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1042-296X 2374-958X |
| DOI | 10.1109/70.964672 |
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| Abstract | This paper presents a new method for improving the accuracy of inertial measurement units (IMUs) mounted on land vehicles. The algorithm exploits nonholonomic constraints that govern the motion of a vehicle on a surface to obtain velocity observation measurements which aid in the estimation of the alignment of the IMU as well as the forward velocity of the vehicle. It is shown that this can be achieved without any external sensing provided that certain observability conditions are met. A theoretical analysis is provided together with a comparison of experimental results between a nonlinear implementation of the algorithm and an IMU/GPS navigation system. This comparison demonstrates the effectiveness of the algorithm. The real time implementation is also addressed through a multiple observation inertial aiding algorithm based on the information filter. The results show that the use of these constraints and vehicle speed guarantees the observability of the velocity and the attitude of the inertial unit, and hence bounds the errors associated with these states. The strategies proposed provides a tighter navigation loop which can sustain outages of GPS for a greater amount of time as compared to when the inertial unit is used with standard integration algorithms. |
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| AbstractList | This paper presents a new method for improving the accuracy of inertial measurement units (IMUs) mounted on land vehicles. The algorithm exploits nonholonomic constraints that govern the motion of a vehicle on a surface to obtain velocity observation measurements which aid in the estimation of the alignment of the IMU as well as the forward velocity of the vehicle. It is shown that this can be achieved without any external sensing provided that certain observability conditions are met. A theoretical analysis is provided together with a comparison of experimental results between a nonlinear implementation of the algorithm and an IMU/GPS navigation system. This comparison demonstrates the effectiveness of the algorithm. The real time implementation is also addressed through a multiple observation inertial aiding algorithm based on the information filter. The results show that the use of these constraints and vehicle speed guarantees the observability of the velocity and the attitude of the inertial unit, and hence bounds the errors associated with these states. The strategies proposed provides a tighter navigation loop which can sustain outages of GPS for a greater amount of time as compared to when the inertial unit is used with standard integration algorithms This paper presents a new method for improving the accuracy of inertial measurement units (IMUs) mounted on land vehicles. The algorithm exploits nonholonomic constraints that govern the motion of a vehicle on a surface to obtain velocity observation measurements which aid in the estimation of the alignment of the IMU as well as the forward velocity of the vehicle. It is shown that this can be achieved without any external sensing provided that certain observability conditions are met. A theoretical analysis is provided together with a comparison of experimental results between a nonlinear implementation of the algorithm and an IMU/GPS navigation system. This comparison demonstrates the effectiveness of the algorithm. The real time implementation is also addressed through a multiple observation inertial aiding algorithm based on the information filter. The results show that the use of these constraints and vehicle speed guarantees the observability of the velocity and the attitude of the inertial unit, and hence bounds the errors associated with these states. The strategies proposed provides a tighter navigation loop which can sustain outages of GPS for a greater amount of time as compared to when the inertial unit is used with standard integration algorithms. This paper presents a new method for improving the accuracy of inertial measurement units (IMUs) mounted on land vehicles. In contrast to the typical techniques used for IMUs mounted on flight vehicles, the algorithm exploits nonholonomic constraints that govern the motion of a vehicle on a surface to obtain velocity observation measurements which aid in the estimation of the alignment of the IMU as well as the forward velocity of the vehicle. |
| Author | Nebot, E. Sukkarieh, S. Durrant-Whyte, H. Dissanayake, G. |
| Author_xml | – sequence: 1 givenname: G. surname: Dissanayake fullname: Dissanayake, G. organization: Sch. of Aerospace, Mech. & Mechatronic Eng., Sydney Univ., NSW, Australia – sequence: 2 givenname: S. surname: Sukkarieh fullname: Sukkarieh, S. – sequence: 3 givenname: E. surname: Nebot fullname: Nebot, E. – sequence: 4 givenname: H. surname: Durrant-Whyte fullname: Durrant-Whyte, H. |
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| Snippet | This paper presents a new method for improving the accuracy of inertial measurement units (IMUs) mounted on land vehicles. The algorithm exploits nonholonomic... This paper presents a new method for improving the accuracy of inertial measurement units (IMUs) mounted on land vehicles. In contrast to the typical... |
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| SubjectTerms | Algorithm design and analysis Algorithms Automation Engineering Geographic information systems Global Positioning System Inertial Information filters Land Land vehicles Measurement Measurement units Motion estimation Motion measurement Navigation Observability Satellite navigation systems Vehicles Velocity measurement |
| Title | The aiding of a low-cost strapdown inertial measurement unit using vehicle model constraints for land vehicle applications |
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