摘要
为了提高自主、无源组合导航系统的精度和可靠性,针对惯性/地磁组合导航系统中滤波发散、量测噪声统计特征随实际情况不同而变化的问题,本文在无迹卡尔曼滤波的基础上,通过监测滤波新息的方差和均值变化,采用模糊自适应滤波算法,"在线"调整模型中的噪声方差阵,来改变滤波器的估计均方误差和滤波增益。通过自适应调整Sigma采样中权值的比例因子α,来解决UT变换的非局部效应,达到提高组合导航的精度的作用。仿真结果表明,模糊自适应卡尔曼滤波器可以有效的提高惯性/地磁组合导航系统,克服了传统滤波算法的缺点和不足,提高了滤波精度。
To improve the autonomous,passive navigation precision and stability,divergence and measurement noise which varied with environments often occurs in inertial navigation system/geomagnetic navigation system（INS/GNS）integrated navigation system.On the basis of unscented Kalman filter,according to change of the variance and mean value of new information.The noise＇s covariance in the model is modified ＂online＂ to changes estimating mean square deviation error and filtering gain of Kalman filtering;Through change the scaling factor α of weight in sigma sampling adaptively to solve nonlocal effect in UT transform,to improve the positioning accuracy of the navigation system.Simulation result presents fuzzy adaptive Kalman filter is very efficient for INS/GNS integrated navigation system,overcome the shortcomings of the traditional filtering method,improve the accuary of filtering.
出处
《舰船科学技术》
2010年第5期68-72,共5页
Ship Science and Technology
关键词
模糊自适应
组合导航
比例因子
无迹卡尔曼滤波
UT变换
fuzzy adaptive
integrated navigation
scaling factor
unscented Kalman filter
UT transform
