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Radar Velocity Measurements Aided Navigation System for UAVs |
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Yeong Seo Kwon, Yong Hun Kim, Hoang Viet Do, San Hee Kang, Hak Ju Kim, Jin Woo Song(Sejong University, Korea) |
| In this paper, we propose a Radar/Inertial Navigation System (RINS) integrated system to address the Global Navigation Satellite System (GNSS) outage problem. The reliable velocity calculated by removing the outliers of the radar velocity can be used as a measurement of Extended Kalman Filter (EKF) to correct the estimation error. In addition, an adaptive algorithm is proposed to update the measurement covariance R over time using the standard deviation of velocity data from which outliers have been removed. The simulation results confirm that the radar/INS integration system gives high accuracy and robustness estimation. |
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Effect of Adaptive Fading Scheme on Invariant EKF for Initial Alignment Under Large Attitude Error and Wave Disturbance Condition |
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Jaehyuck Cha, Jeong Ho Hwang, Chan Gook Park(Seoul National University, Korea) |
| This paper proposes an invariant extended Kalman filter (IEKF) to which an adaptive fading scheme is applied as an initial alignment technique for marine vehicles in mooring condition. The adaptive fading scheme adjusting Kalman gain accelerates the convergence rate. The proposed method is verified by numerical simulation. |
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An Adaptive Approach based on Multi-State Constraint Kalman Filter for UAVs |
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Hoang Viet Do, Yong Hun Kim, Yeong Seo Kwon, San Hee Kang, Hak Ju Kim, Jin Woo Song(Sejong University, Korea) |
| The consistent of extended Kalman Filter-based estimator highly relies on the prior information of the process noise and the measurement noise covariance matrices. In this paper, we apply an adaptation rule to the well-known Multi-State Constraint Kalman Filter using innovation and residual information for a monocular VINS that is mounted in a drone. Since the vision process can give different estimated results due to various error sources such as the ambiguity or the quality of the camera, each epoch should have different weighting factors. Therefore, Q and R covariance matrices should be adapted. It is shown through the simulation that the proposed algorithm offers better performance. |
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Attitude Determination of High Spinning Motion under Uniaxial Saturation Condition |
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Juhwan Lee(Konkuk, Korea), Sangkyung Sung(Konkuk University, Korea) |
| In this paper, we present an attitude determination method of a high spinning object that rotates uniaxially. Accurate attitude estimation of the high spinning object, for example projectile and flying disc, is necessary for its dynamic analysis and control. However, since the high spinning rotation over 2000 deg/s causes most of the gyroscope's saturation, it is challenging to estimate the attitude. To solve this problem, we propose a new reduced state filter algorithm based on a proper Euler angle order for the uniaxially rotating object. Unlike the conventional gyro-magnetic attitude estim |
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