一种改进自适应增量Kalman滤波的传递对准算法

A Improved Adaptive Incremental Filtering Algorithm of Transfer Alignment

针对舰船机动能力弱,以及陀螺漂移随时间发散、载体弹性形变等随机扰动等带来的惯导系统传递对准滤波精度降低的问题,提出一种基于"速度+位置+姿态"匹配法的自适应增量Kalman滤波算法。建立传递对准状态空间模型,区分类别设计自适应因子,构建增量Kalman滤波器。仿真结果表明:该算法能够提高捷联惯导系统信息利用率,仅在舰船摇摆状态下,就能实现快速对准,实时估计时变量测噪声,消除不确定系统误差所带来的干扰,对准精度高,工程应用前景广阔。

For the ship maneuvering performance is poor, and the problem of the drift of the gyro diverges with time, filtering precision of the INS transter alignment reduction caused by random disturbance such as elastic deformation. An adaptive incremental Kahnan filtering algorithm based on the ＂velocity＋position＋attitude＂ matching method is proposed.. In this algorithm, the state space model of transter alignment is established, designing classified adaptive tactors, structuring adaptive incremental Kahnan filter. Computer simulation results show that this algorithm can improve the used-ratio of SINS information, realize rapid alignment only under the ship swaying state, realize real-time estimation of time variable noise, alignment precision is high and the prospect of engineering application is broad.