Establishment of Real-time HILS Environment for Small UAV Using 6 D.O.F Motion Table

Cha, Hyungkyu; Jeong, Jinseok; Shi, Ha-Young; Yoon, Jong-Su; Kang, Beom-Soo

doi:10.5139/jksas.2019.47.5.326

Cited by 1 publication

(1 citation statement)

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“…Motion table: This machine was used to rotate the sensor around the X-, Y-, and Z-axes to an orientation angle required by the computer software. The software was developed as real-time harware-in-the-loop simulation (HILS) testing tool for small UAVs [ 25 ]. The specifications of the motion table are given in Table 4 ;…”

Section: Computer Simulation and Experimentationmentioning

confidence: 99%

Improved Attitude and Heading Accuracy with Double Quaternion Parameters Estimation and Magnetic Disturbance Rejection

Wondosen

Jeong

Kim

et al. 2021

Sensors

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The use of unmanned aerial vehicle (UAV) applications has grown rapidly over the past decade with the introduction of low-cost microelectromechanical system (MEMS)-based sensors that measure angular velocity, gravity, and magnetic field, which are important for an object orientation determination. However, the use of low-cost sensors has also been limited because their readings are easily distorted by unwanted internal and/or external noise signals such as environmental magnetic disturbance, which lead to errors in attitude and heading estimation results. In an extended Kalman filter (EKF) process, this study proposes a method for mitigating the effect of magnetic disturbance on attitude determination by using a double quaternion parameters for representation of orientation states, which decouples the magnetometer from attitude computation. Additionally, an online measurement error covariance matrix tuning system was implemented to reject the impact of magnetic disturbance on the heading estimation. Simulation and experimental tests were conducted to verify the performance of the proposed methods in resolving the magnetic noise effect on attitude and heading. The results showed that the proposed method performed better than complimentary, gradient descent, and single quaternion-based EKF.

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Section: Computer Simulation and Experimentationmentioning

confidence: 99%