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EN
The Alpha-Beta-Gamma tracking filter is useful for tracking a constant acceleration target with zero lag error in the steady state. It, however, depicts a constant lag error for a maneuvering target. Various algorithms of the Alpha-Beta-Gamma tracking filter exist in literature and each one of them presents its own unique challenges and advantages depending on the design requirement. This study investigates the operation of three Alpha-Beta-Gamma tracking filter design methods which include Benedict-Bordner also known as the Simpson filter, Gray-Murray filter and the fading memory constant acceleration filter. These filters are then compared based on the ability to reduce noise and follow a maneuvering target with minimum lag error, against the jerky model Alpha-Beta-Gamma-Eta. Results obtained from simulations of the input model of the target dynamics under consideration indicate an improvement in performance of the jerky model in comparison with the constant acceleration models.
EN
The tracking filter plays a key role in accurate estimation and prediction of maneuvering vessel’s position and velocity. Different methods are used for tracking. However, the most commonly used method is the Kalman filter and its modifications. The Alpha-Beta-Gamma filter is one of the special cases of the general solution pro-vided by the Kalman filter. It is a third order filter that computes the smoothed estimates of position, velocity and acceleration for the nth observation, and also predicts the next position and velocity. Although found to track a maneuvering target with a good accuracy than the constant velocity, Alpha-Beta filter, the Alpha-Beta-Gamma filter does not perform impressively under high maneuvers such as when the target is undergoing changing accelerations. This study, therefore, aims to track a highly maneuvering target experiencing jerky motions due to changing accelerations. The Alpha-Beta-Gamma filter is extended to include the fourth state that is, constant jerk to correct the sudden change of acceleration in order to improve the filter’s performance. Results obtained from simulations of the input model of the target dynamics under consideration indicate an improvement in performance of the jerky model, Alpha-Beta-Gamma-Eta, algorithm as compared to the constant acceleration model, Alpha-Beta-Gamma in terms of error reduction and stability of the filter during target maneuver.
EN
This paper is to develop the position error equations including the attitude errors, the errors of nadir and ship’s heading, and the errors of ship’s position in the free-gyro positioning and directional system. In doing so, the determination of ship’s position by two free gyro vectors was discussed and the algorithmic design of the free-gyro positioning and directional system was introduced briefly. Next, the errors of transformation matrices of the gyro and body frames, i.e., attitude errors, were examined and the attitude equations were also derived. The perturbations of the errors of the nadir angle including ship’s heading were investigated in each stage from the sensor of rate of motion of the spin axis to the nadir angle obtained. Finally, the perturbation error equations of ship’s position used the nadir angles were derived in the form of a linear error model and the concept of FDOP was also suggested by using covariance of position error.
4
Content available remote An Algorithmic Study on Positioning and Directional System by Free Gyros
EN
The authors aim to establish the theory necessary for developing free gyro positioning system and focus on measuring the nadir angle by using the motion rate of a free gyro. The azimuth of a gyro vector from the North can be given by using the property of the free gyro. The motion rate of the spin axis in the gy-ro frame is transformed into the platform frame and again into the NED (north-east-down) navigation frame. The nadir angle of a gyro vector is obtained by using the North components of the motion rate of the spin axis in the NED frame. The component has to be transformed into the horizontal component of the gyro by using the azimuth of the gyro vector and then has to be integrated over the sampling interval. Meanwhile the au-thors suggest north-finding principle by the angular velocity of the earth’s rotation. That is, ship's heading is obtained by using the fore-and-aft and athwartship components of the motion rate of the spin axis in the NED frame.
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