【摘要】 根据水下平台晃动的规律建立了晃动模型,对水下晃动平台姿态估计的精度分析展开研究.仿真验证了平台以匀速运动、匀加速运动两种情况下的卡尔曼滤波算法和简化的自适应卡尔曼滤波算法的姿态估计精度.仿真结果表明:匀速运动模式两种算法的估计误差在同一范围内;匀加速运动模式,卡尔曼算法具有更快的收敛速度,而自适应卡尔曼算法的估计方差约为卡尔曼算法的50%以下.更多还原

【Abstract】 The accuracy analysis of attitude estimation of underwater swaying platform is the main purpose in this paper.A swaying model is built based on the platform swaying rule,then Kalman filter and simplified adaptive Kalman filter algorithms are adopted to simulate the attitude estimation accuracy under two kinds of uniform:Uniform motion and uniform acceleration.The simulation results show:The estimation errors of the two algorithms are below the same boundary when the motion is uniform;If the motion is of uniform acceleration,the Kalman filter algorithm has a faster convergence rate while the adaptive Kalman filter algorithm has a smaller estimation variance equaling to 50% of that for Kalman filter algorithm.Therefore,the attitude estimation performance of adaptive Kalman filter is better than that of Kalman filter algorithm under complicated conditions.更多还原