A Practical Method for Implementing an Attitude and Heading Reference System

This paper describes a practical and reliable algorithm for implementing an Attitude and Heading Reference System (AHRS). This kind of system is essential for real time vehicle navigation, guidance and control applications. When low cost sensors are used, efficient and robust algorithms are required for performance to be acceptable. The proposed method is based on an Extended Kalman Filter (EKF) in a direct configuration. In this case, the filter is explicitly derived from both the kinematic and error models. The selection of this kind of EKF configuration can help in ensuring a tight integration of the method for its use in filter-based localization and mapping systems in autonomous vehicles. Experiments with real data show that the proposed method is able to maintain an accurate and drift-free attitude and heading estimation. An additional result is to show that there is no ostensible reason for preferring that the filter have an indirect configuration over a direct configuration for implementing an AHRS system.

[1]  D. Gebre-Egziabher,et al.  A low-cost GPS/inertial attitude heading reference system (AHRS) for general aviation applications , 1998, IEEE 1998 Position Location and Navigation Symposium (Cat. No.98CH36153).

[2]  Yanhua Zhang,et al.  Adaptive filter for a miniature MEMS based attitude and heading reference system , 2004, PLANS 2004. Position Location and Navigation Symposium (IEEE Cat. No.04CH37556).

[3]  Robert E. Mahony,et al.  Nonlinear Complementary Filters on the Special Orthogonal Group , 2008, IEEE Transactions on Automatic Control.

[4]  Isaac Skog,et al.  Zero-Velocity Detection—An Algorithm Evaluation , 2010, IEEE Transactions on Biomedical Engineering.

[5]  Carlos Silvestre,et al.  A Geometric Approach to Strapdown Magnetometer Calibration in Sensor Frame , 2008 .

[6]  F. Markley.  Attitude Error Representations for Kalman Filtering , 2003 .

[7]  Dah-Jing Jwo,et al.  Critical remarks on the linearised and extended Kalman filters with geodetic navigation examples , 2010 .

[8]  M. Grassi,et al.  AIAA Guidance, Navigation, and Control Conference , 2008 .

[9]  N. Marchand,et al.  A low-cost air data attitude heading reference system for the tourism airplane applications , 2005, IEEE Sensors, 2005..

[10]  R.C. Hayward,et al.  Design of multi-sensor attitude determination systems , 2004, IEEE Transactions on Aerospace and Electronic Systems.

[11]  Felipe Espinosa,et al.  UAV Attitude Estimation Using Unscented Kalman Filter and TRIAD , 2012, IEEE Transactions on Industrial Electronics.

[12]  John B. Moore,et al.  Direct Kalman filtering approach for GPS/INS integration , 2002 .

[13]  Hugh F. Durrant-Whyte,et al.  Simultaneous localization and mapping: part I , 2006, IEEE Robotics & Automation Magazine.

[14]  M.A. Cordoba,et al.  Attitude and heading refernce system I-AHRS for the EFIGENIA autonomous unmanned aerial vehicles UAV based on MEMS sensor and a neural network strategy for attitude estimation , 2007, 2007 Mediterranean Conference on Control & Automation.

[15]  F. Markley,et al.  Nonlinear Attitude Filtering Methods , 2005 .

[16]  M. Shuster.  A survey of attitude representation , 1993 .

[17]  Antoni Grau,et al.  Attitude and Heading System based on EKF total state configuration , 2011, 2011 IEEE International Symposium on Industrial Electronics.

[18]  Rodrigo Munguía,et al.  Closing Loops With a Virtual Sensor Based on Monocular SLAM , 2009, IEEE Transactions on Instrumentation and Measurement.

[19]  Jinhui Lan,et al.  Constrained Filtering Method for MAV Attitude Determination , 2005, 2005 IEEE Instrumentationand Measurement Technology Conference Proceedings.

[20]  Carlos Silvestre,et al.  Geometric Approach to Strapdown Magnetometer Calibration in Sensor Frame , 2011, IEEE Transactions on Aerospace and Electronic Systems.

[21]  Young Soo Suh.  Orientation Estimation Using a Quaternion-Based Indirect Kalman Filter With Adaptive Estimation of External Acceleration , 2010, IEEE Transactions on Instrumentation and Measurement.

[22]  Malcolm D. Shuster.  Survey of attitude representations , 1993 .

[23]  Mark Euston,et al.  A complementary filter for attitude estimation of a fixed-wing UAV , 2008, 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems.