CAJ | 학술논문

针对动力定位船舶,采用基于无迹卡尔曼滤波(UKF)的联邦滤波技术,利用多种位置参考系统和电罗经的测量值来实现对船舶运动状态的估计.从传感器测量原理出发,采用非线性的测量方程,实现对多种位置参考系统传感器特征的描述,利用 UKF 滤波方法和联邦滤波结构将动力定位船舶配备的多个冗余位置参考系统的测量数据进行有效融合,从而提高对船舶运动状态估计的精度和可靠性.仿真结果表明,采用基于UKF的联邦滤波方法可以有效实现对动力定位船舶相关运动状态的估计.
침대동력정위선박,채용기우무적잡이만려파(UKF)적련방려파기술,이용다충위치삼고계통화전라경적측량치래실현대선박운동상태적고계.종전감기측량원리출발,채용비선성적측량방정,실현대다충위치삼고계통전감기특정적묘술,이용 UKF 려파방법화련방려파결구장동력정위선박배비적다개용여위치삼고계통적측량수거진행유효융합,종이제고대선박운동상태고계적정도화가고성.방진결과표명,채용기우UKF적련방려파방법가이유효실현대동력정위선박상관운동상태적고계.
@@@@For the dynamic positioning ship, based on the Unscented Kalman Filter (UKF), a federated filter is designed to estimate the ship motion states by using the measurements from different position reference systems (PRS) on the ship. From the point of measurement principle, the nonlinear measurement equations are used to describe the characteristic of different kinds of PRS. With the combination of UKF filter method and federated filter structure, this method can effectively achieve a good data fusion effect for the redundancy PRS to accomplish the goal of estimating the ship motion states with good accuracy. The simulation results show that the UKF based federated filter can meet the need for the state estimation for the dynamic positioning ship.