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OpenAlex konusu

Inertial Sensor and Navigation

Bu sayfa OpenAlex konu etiketine göre çalışmaları ve o konuda görünen akademisyenleri listeler. YÖKSİS temel alan / yan dal değildir.

OpenAlex 1.143 eser 70 yazar konusu

Çalışmalar

1.143 eser

  1. YÖKSİS JCR Q1 OpenAlex üst %1 OpenAlex 100.0%

    A low-cost solid-state inertial navigation system (INS) for mobile robotics applications is described. Error models for the inertial sensors are generated and included in an extended Kalman filter (EKF) for estimating the position and orientation of a moving robot vehicle. Two different solid-state gyroscopes have bee…

  2. YÖKSİS SJR Q1 JCR Q1 OpenAlex üst %1 OpenAlex 99.5%

    This paper presents a cardinalized probability hypothesis density (CPHD) filter for extended targets that can result in multiple measurements at each scan. The probability hypothesis density (PHD) filter for such targets has been derived by Mahler, and different implementations have been proposed recently. To achieve…

  3. YÖKSİS SJR Q2 JCR Q1 OpenAlex üst %10 OpenAlex 96.3%

    Özet henüz yok.

  4. YÖKSİS SJR Q2 JCR Q1 OpenAlex üst %10 OpenAlex 96.3%

    Özet henüz yok.

  5. YÖKSİS SJR Q1 JCR Q1 OpenAlex üst %10 OpenAlex 97.0%

    In this article, the real-time comparison of extended and unscented Kalman filter algorithms, which estimate the stator stationary axis components of stator currents, the stator stationary axis components of rotor fluxes, the rotor mechanical speed, and the load torque including viscous friction term, are performed un…

  6. YÖKSİS SJR Q1 JCR Q1 OpenAlex üst %10 OpenAlex 97.0%

    In this article, the real-time comparison of extended and unscented Kalman filter algorithms, which estimate the stator stationary axis components of stator currents, the stator stationary axis components of rotor fluxes, the rotor mechanical speed, and the load torque including viscous friction term, are performed un…

  7. YÖKSİS SJR Q2 JCR Q2 OpenAlex üst %1 OpenAlex 99.9%

    Özet henüz yok.

  8. YÖKSİS SJR Q2 JCR Q2 OpenAlex üst %1 OpenAlex 99.9%

    Özet henüz yok.

  9. YÖKSİS SJR Q1 JCR Q2 OpenAlex üst %1 OpenAlex 99.9%

    SUMMARY Unscented Kalman filter (UKF) is a filtering algorithm that gives sufficiently good estimation results for the estimation problems of nonlinear systems even when high nonlinearity is in question. However, in case of system uncertainty or measurement malfunctions, the UKF becomes inaccurate and diverges by time…

  10. YÖKSİS JCR Q4 OpenAlex üst %1 OpenAlex 99.9%

    SUMMARY Unscented Kalman filter (UKF) is a filtering algorithm that gives sufficiently good estimation results for the estimation problems of nonlinear systems even when high nonlinearity is in question. However, in case of system uncertainty or measurement malfunctions, the UKF becomes inaccurate and diverges by time…

  11. YÖKSİS SJR Q1 JCR Q3 OpenAlex üst %1 OpenAlex 99.8%

    Özet henüz yok.

  12. YÖKSİS OpenAlex üst %1 OpenAlex 99.8%

    Özet henüz yok.

Akademisyenler

70 akademisyen