The Experts below are selected from a list of 243 Experts worldwide ranked by ideXlab platform

Jussi Collin - One of the best experts on this subject based on the ideXlab platform.

  • the Direction Cosine matrix algorithm in fixed point implementation and analysis
    International Conference on Acoustics Speech and Signal Processing, 2019
    Co-Authors: Alexandre Meirhaeghe, Jani Boutellier, Jussi Collin
    Abstract:

    Inertial navigation allows tracking and updating the position and orientation of a moving object based on accelerometer and gyroscope data without external positioning aid, such as GPS. Therefore, inertial navigation is an essential technique for, e.g., indoor positioning. As inertial navigation is based on integration of acceleration vector components, computation errors accumulate and make the position and orientation estimate drift. Even though maximum computation precision is desired, also efficiency needs consideration in the age of Internet-of-Things, to enable deployment of inertial navigation based applications to the smallest devices. This work formulates the Direction Cosine Matrix update algorithm, a central component for inertial navigation, in fixed-point and analyzes its precision and computation load compared to a regular floating-point implementation. The results show that the fixed-point version maintains very high precision, while requiring no floating point hardware for operation. The paper presents execution time results on three very different embedded processors.

  • ICASSP - The Direction Cosine Matrix Algorithm in Fixed-point: Implementation and Analysis
    ICASSP 2019 - 2019 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), 2019
    Co-Authors: Alexandre Meirhaeghe, Jani Boutellier, Jussi Collin
    Abstract:

    Inertial navigation allows tracking and updating the position and orientation of a moving object based on accelerometer and gyroscope data without external positioning aid, such as GPS. Therefore, inertial navigation is an essential technique for, e.g., indoor positioning. As inertial navigation is based on integration of acceleration vector components, computation errors accumulate and make the position and orientation estimate drift. Even though maximum computation precision is desired, also efficiency needs consideration in the age of Internet-of-Things, to enable deployment of inertial navigation based applications to the smallest devices. This work formulates the Direction Cosine Matrix update algorithm, a central component for inertial navigation, in fixed-point and analyzes its precision and computation load compared to a regular floating-point implementation. The results show that the fixed-point version maintains very high precision, while requiring no floating point hardware for operation. The paper presents execution time results on three very different embedded processors.

Alexandre Meirhaeghe - One of the best experts on this subject based on the ideXlab platform.

  • the Direction Cosine matrix algorithm in fixed point implementation and analysis
    International Conference on Acoustics Speech and Signal Processing, 2019
    Co-Authors: Alexandre Meirhaeghe, Jani Boutellier, Jussi Collin
    Abstract:

    Inertial navigation allows tracking and updating the position and orientation of a moving object based on accelerometer and gyroscope data without external positioning aid, such as GPS. Therefore, inertial navigation is an essential technique for, e.g., indoor positioning. As inertial navigation is based on integration of acceleration vector components, computation errors accumulate and make the position and orientation estimate drift. Even though maximum computation precision is desired, also efficiency needs consideration in the age of Internet-of-Things, to enable deployment of inertial navigation based applications to the smallest devices. This work formulates the Direction Cosine Matrix update algorithm, a central component for inertial navigation, in fixed-point and analyzes its precision and computation load compared to a regular floating-point implementation. The results show that the fixed-point version maintains very high precision, while requiring no floating point hardware for operation. The paper presents execution time results on three very different embedded processors.

  • ICASSP - The Direction Cosine Matrix Algorithm in Fixed-point: Implementation and Analysis
    ICASSP 2019 - 2019 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), 2019
    Co-Authors: Alexandre Meirhaeghe, Jani Boutellier, Jussi Collin
    Abstract:

    Inertial navigation allows tracking and updating the position and orientation of a moving object based on accelerometer and gyroscope data without external positioning aid, such as GPS. Therefore, inertial navigation is an essential technique for, e.g., indoor positioning. As inertial navigation is based on integration of acceleration vector components, computation errors accumulate and make the position and orientation estimate drift. Even though maximum computation precision is desired, also efficiency needs consideration in the age of Internet-of-Things, to enable deployment of inertial navigation based applications to the smallest devices. This work formulates the Direction Cosine Matrix update algorithm, a central component for inertial navigation, in fixed-point and analyzes its precision and computation load compared to a regular floating-point implementation. The results show that the fixed-point version maintains very high precision, while requiring no floating point hardware for operation. The paper presents execution time results on three very different embedded processors.

Mamoun F. Abdel-hafez - One of the best experts on this subject based on the ideXlab platform.

  • A Cascaded Approach for Quadrotor's Attitude Estimation
    Procedia Technology, 2014
    Co-Authors: Bara J. Emran, Mamoun F. Abdel-hafez, Michael Omari, Mohammad Abdel Kareem Jaradat
    Abstract:

    This paper presents a new methodology to estimate the orientation of a quadrotor using single low cost IMU sensor. The proposed solution uses two extended Kalman filters (EKF) along with a Direction Cosine Matrix (DCM) algorithm. An EKF is used to filter the noise signal of the angular rates measured by a 3-axis gyroscope sensor. Subsequently, a DCM algorithm uses the filtered gyro signal along with the reading from a 3-axis accelerometer and a 3-axis magnetometer sensor to compute the Euler angles. Finally, another EKF is presented to improve the estimation of the Euler angles. A complete simulation platform was developed using MatLab software to test the performance of the proposed method and compare it with two alternative methods.

  • Real-time implementation of GPS aided low-cost strapdown inertial navigation system
    Journal of Intelligent and Robotic Systems: Theory and Applications, 2011
    Co-Authors: Laith R Sahawneh, M.a. Al-jarrah, Khaled Assaleh, Mamoun F. Abdel-hafez
    Abstract:

    This work details the study, development, and experimental implemen- tation of GPS aided strapdown inertial navigation system (INS) using commercial off-the-shelf low-cost inertial measurement unit (IMU). The data provided by the inertial navigation mechanization is fused with GPS measurements using loosely- coupled linear Kalman filter implemented with the aid of MPC555 microcontroller. The accuracy of the estimation when utilizing a low-cost inertial navigation system (INS) is limited by the accuracy of the sensors used and the mathematical modeling of INS and the aiding sensors’ errors. Therefore, the IMU data is fused with the GPS data to increase the accuracy of the integrated GPS/IMU system. The equations required for the local geographic frame mechanization are derived. The Direction Cosine matrix approach is selected to compute orientation angles and the unified mathematical framework is chosen for position/velocity algorithm computations. This selection resulted in significant reduction in mechanization errors. It is shown that the constructed GPS/IMU system is successfully implemented with an accurate and reliable performance.

James Richard Forbes - One of the best experts on this subject based on the ideXlab platform.

  • Direction Cosine matrix based attitude control subject to actuator saturation
    Iet Control Theory and Applications, 2015
    Co-Authors: James Richard Forbes
    Abstract:

    Set-point attitude control of a rigid body explicitly preventing actuator saturation is considered. The attitude control approach developed does not employ any sort of Direction-Cosine-matrix (DCM) parameterisation, such as Euler angles or quaternions. Rather, the DCM is used directly within the feedback control algorithm. Together a proportional control term and an angular velocity control term make up the attitude controller. The angular velocity control is composed of a strictly positive real system subject to a special input non-linearity. The specific form of the proportional control and angular velocity control ensure control torques are below the saturation level of the on-board actuators. Two controller synthesis methods are considered. The first uses the linearised system, the solution to the linear quadratic regulator problem, and the Kalman–Yakubovich–Popov lemma to design the controller. The second employs a simple low-pass filter that is guaranteed to stabilise the closed-loop system; tuning the low-pass filter is also considered. Numerical simulation results demonstrate effective closed-loop control in the presence of plant disturbances and sensor noise.

Jani Boutellier - One of the best experts on this subject based on the ideXlab platform.

  • the Direction Cosine matrix algorithm in fixed point implementation and analysis
    International Conference on Acoustics Speech and Signal Processing, 2019
    Co-Authors: Alexandre Meirhaeghe, Jani Boutellier, Jussi Collin
    Abstract:

    Inertial navigation allows tracking and updating the position and orientation of a moving object based on accelerometer and gyroscope data without external positioning aid, such as GPS. Therefore, inertial navigation is an essential technique for, e.g., indoor positioning. As inertial navigation is based on integration of acceleration vector components, computation errors accumulate and make the position and orientation estimate drift. Even though maximum computation precision is desired, also efficiency needs consideration in the age of Internet-of-Things, to enable deployment of inertial navigation based applications to the smallest devices. This work formulates the Direction Cosine Matrix update algorithm, a central component for inertial navigation, in fixed-point and analyzes its precision and computation load compared to a regular floating-point implementation. The results show that the fixed-point version maintains very high precision, while requiring no floating point hardware for operation. The paper presents execution time results on three very different embedded processors.

  • ICASSP - The Direction Cosine Matrix Algorithm in Fixed-point: Implementation and Analysis
    ICASSP 2019 - 2019 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), 2019
    Co-Authors: Alexandre Meirhaeghe, Jani Boutellier, Jussi Collin
    Abstract:

    Inertial navigation allows tracking and updating the position and orientation of a moving object based on accelerometer and gyroscope data without external positioning aid, such as GPS. Therefore, inertial navigation is an essential technique for, e.g., indoor positioning. As inertial navigation is based on integration of acceleration vector components, computation errors accumulate and make the position and orientation estimate drift. Even though maximum computation precision is desired, also efficiency needs consideration in the age of Internet-of-Things, to enable deployment of inertial navigation based applications to the smallest devices. This work formulates the Direction Cosine Matrix update algorithm, a central component for inertial navigation, in fixed-point and analyzes its precision and computation load compared to a regular floating-point implementation. The results show that the fixed-point version maintains very high precision, while requiring no floating point hardware for operation. The paper presents execution time results on three very different embedded processors.