Attitude and heading reference system

Abstract: Design Cutting-Edge Aided Navigation Systems for Advanced Commercial & Military Applications Aided Navigation is a design-oriented textbook and guide to building aided navigation systems for smart cars, precision farming vehicles, smart weapons, unmanned aircraft, mobile robots, and other advanced applications. The navigation guide contains two parts explaining the essential theory, concepts, and tools, as well as the methodology in aided navigation case studies with sufficient detail to serve as the basis for application-oriented analysis and design. Filled with detailed illustrations and examples, this expert design tool takes you step-by-step through coordinate systems, deterministic and stochastic modeling, optimal estimation, and navigation system design. Authoritative and comprehensive, Aided Navigation features: End-of-chapter exercises throughout Part I In-depth case studies of aided navigation systems Numerous Matlab-based examples Appendices define notation, review linear algebra, and discuss GPS receiver interfacing Source code and sensor data to support examples is available through the publisher-supported website Inside this Complete Guide to Designing Aided Navigation Systems • Aided Navigation Theory: Introduction to Aided Navigation • Coordinate Systems • Deterministic Modeling • Stochastic Modeling • Optimal Estimation • Navigation System Design • Navigation Case Studies: Global Positioning System (GPS) • GPS-Aided Encoder • Attitude and Heading Reference System • GPS-Aided Inertial Navigation System (INS) • Acoustic Ranging and Doppler-Aided INS Table of contents I. Theory Part I: Overview Chapter 1. Overview Chapter 2. Reference Frames Chapter 3. Deterministic Systems Chapter 4. Stochastic Processes Chapter 5. Optimal State Estimation Chapter 6. Performance Analysis Chapter 7. Navigation System Design II. Application Part II: Overview Chapter 8. Global Positioning System Chapter 9. GPS Aided Encoder-Based Dead-Reckoning Chapter 10. AHRS Chapter 11. Aided Inertial Navigation Chapter 12. LBL and Doppler Aided INS Appendix A: Notation Appendix B: Linear Algebra Review Appendix C: Calculation of GPS Satellite Position & Velocity Appendix D: Quaternions Bibliography Index

Abstract: A sigma-point Kalman filter is derived for integrating GPS measurements with inertial measurements from gyros and accelerometers to determine both the position and the attitude of a moving vehicle. Sigma-point filters use a carefully selected set of sample points to more accurately map the probability distribution than the linearization of the standard extended Kalman filter (KKF), leading to faster convergence from inaccurate initial conditions in position/attitude estimation problems. The filter formulation is based on standard inertial navigation equations. The global attitude parameterization is given by a quaternion, while a generalized three-dimensional attitude representation is used to define the local attitude error. A multiplicative quaternion-error approach is used to guarantee that quaternion normalization is maintained in the filter. Simulation and experimental results are shown to compare the performance of the sigma-point filter with a standard EKF approach.

Abstract: A method for heading determination is described that will include the effects of pitch and roll as well as the magnetic properties of the vehicle. Using solid-state magnetic sensors and a tilt sensor, a low cost compass system can be realized. Commercial airlines today use attitude and heading reference systems that cost tens of thousands of dollars. For general aviation, or small private aircraft, this is too costly for most pilot's budget. The compass system described here provides heading, pitch and roll outputs accurate to one degree, or better. The shortfall of this low-cost approach is that the compass outputs are affected by acceleration and turns. A solution to this problem is also presented.

Abstract: A three-axis, magnetometer/Kalman filter, attitude-determination system for a spacecraft in low-altitude Earth orbit is developed, analyzed, and simulation tested. The motivation for developing this system is to achieve three-axis knowledge using magnetic field measurements only. The extended Kalman filter estimates the attitude, attitude rates, and constant disturbance torques. Covariance computation and simulation testing are used to evaluate performance. One test case, a gravity-gradient stabilized spacecraft with a pitch momentum wheel and a magnetically anchored damper, is a real satellite on which this attitude determination system will be used. The application to a nadir-pointing satellite and the estimation of disturbance torques represent the significant extensions contributed by this paper. Beyond its usefulness purely for attitude determination, this system could be used as a part of a low-cost, three-axis attitude stabilization system. I. Introduction T HE objective of this work has been to develop a low-cost system for estimation of three-axis, spacecraft-attitude information based solely on three-axis magnetometer measurements from one satellite orbit. Such a system will be useful for missions that operate in an inclined, low-Earth orbit and require only coarse attitude information. It can also serve as the sensor part of a low-cost, three-axis, closed-loop attitude control system or as a backup attitude estimator. A single three-axis magnetometer measurement can give only two-axes worth of attitude information and no attitude rate or disturbance torque information. Therefore, this attitude determination system must use a sequence of magnetometer measurements. It processes these measurements recursively in a Kalman filter. This paper describes the design, development, analysis, and simulation testing of a Kalman filter arid reports its expected peformance. A follow-on, postlaunch paper is planned to report actual performance.

Abstract: Development, calibration and alignment of a miniature magnetic and inertial measurement unit, which is used as an attitude and heading reference system, are presented. Several guidelines were followed during the design process to make the magnetic and inertial measurement unit suitable for various kinds of applications, thus the system is designed both as small as possible but still modular, consisting of three inertial sensor units, a magnetic sensor unit and a control unit. Complete calibration and alignment procedure is described and an adaptive Kalman filter concept for fusing various sensors’ attitude and heading data is introduced and discussed. The characteristics of the magnetic and inertial measurement unit as an attitude and heading reference system are evaluated. The algorithm showed remarkable performance in the orientation determination as the average root mean square error was less than 1.2° over the entire appliable operating range.