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 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

Attitude Estimation and Control Using Linear-Like Complementary Filters: Theory and Experiment

This paper proposes new algorithms for attitude estimation and control based on fused inertial vector measurements using linear complementary filters principle. First, n-order direct and passive complementary filters combined with TRIAD algorithm are proposed to give attitude estimation solutions. These solutions which are efficient with respect to noise include the gyro bias estimation. Thereafter, the same principle of data fusion is used to address the problem of attitude tracking based on inertial vector measurements. Thus, instead of using noisy raw measurements in the control law a new solution of control that includes a linear-like complementary filter to deal with the noise is proposed. The stability analysis of the tracking error dynamics based on LaSalle's invariance theorem proved that almost all trajectories converge asymptotically to the desired equilibrium. Experimental results, obtained with DIY Quad equipped with the APM2.6 auto-pilot, show the effectiveness and the performance of the proposed solutions.Comment: Submitted for Journal publication on March 09, 2015. Partial results related to this work have been presented in IEEE-ROBIO-201

Design study for LANDSAT-D attitude control system

The gimballed Ku-band antenna system for communication with TDRS was studied. By means of an error analysis it was demonstrated that the antenna cannot be open loop pointed to TDRS by an onboard programmer, but that an autotrack system was required. After some tradeoffs, a two-axis, azimuth-elevation type gimbal configuration was recommended for the antenna. It is shown that gimbal lock only occurs when LANDSAT-D is over water where a temporary loss of the communication link to TDRS is of no consequence. A preliminary gimbal control system design is also presented. A digital computer program was written that computes antenna gimbal angle profiles, assesses percent antenna beam interference with the solar array, and determines whether the spacecraft is over land or water, a lighted earth or a dark earth, and whether the spacecraft is in eclipse

Robust longitudinal rate gyro bias estimation for reliable pitch attitude observation through utilization of a displaced accelerometer array

In this thesis, a novel attitude estimation device is proposed utilizing cost-effective measurement sensors. The device fuses a rate gyroscope with an accelerometer array to estimate and eliminate the rate gyro bias online yielding accurate real time aircraft attitude tracking. Attitude determination algorithms are dependent on instantaneous and accurate measurements of translational and rotational body rates for precise estimation of vehicle orientation in three-dimensional space. Measurement error of instantaneous rate sensors, gyroscopes, is introduced via inherent biases and signal noise resulting in gyro drift. Integration of the rate signal for calculation of a net displacement amplifies these minute measurement errors leading to inaccurate and unreliable attitude observation. The proposed device is a departure from typical attitude observers and bias estimators due to its reliance on accelerometers measuring the local gravitational vector in lieu of additional magnetic field sensors or GPS. The end result of this work is a longitudinal attitude estimation device able to compute a rate gyro bias in real-time producing accurate pitch angle tracking while subjected to simulated aircraft flight conditions. The effectiveness of the newly constructed attitude estimation algorithm is demonstrated by comparison of attitude and rate gyro bias estimates produced from noise corrupted and biased sensors with the actual attitude of a nonlinear aircraft model and true rate gyro bias

Survey of Motion Tracking Methods Based on Inertial Sensors: A Focus on Upper Limb Human Motion

Motion tracking based on commercial inertial measurements units (IMUs) has been widely studied in the latter years as it is a cost-effective enabling technology for those applications in which motion tracking based on optical technologies is unsuitable. This measurement method has a high impact in human performance assessment and human-robot interaction. IMU motion tracking systems are indeed self-contained and wearable, allowing for long-lasting tracking of the user motion in situated environments. After a survey on IMU-based human tracking, five techniques for motion reconstruction were selected and compared to reconstruct a human arm motion. IMU based estimation was matched against motion tracking based on the Vicon marker-based motion tracking system considered as ground truth. Results show that all but one of the selected models perform similarly (about 35 mm average position estimation error)