基于模糊自适应强跟踪滤波的惯性/地磁组合导航方法

摘要

针对在量测噪声统计特性发生变化时,基于滤波算法的惯性/地磁组合导航系统存在精度下降甚至发散的问题,提出了一种基于模糊自适应强跟踪滤波算法的惯性/地磁组合导航方法,该方法通过制定模糊规则,实时监控系统残差变化,自适应地调整柔化因子的大小,即增强了滤波器对时变噪声的跟踪能力又保证了滤波器处理当前信息的能力.仿真结果表明:该方法能够很好地抑制纯惯性导航系统随时间累积的误差,而且在量测噪声统计特性发生变化时,系统误差没有出现明显的跳变,保证了整个导航系统的精度,提高了系统的鲁棒性.%In view that the precision of INS/GNS integrated system decreases when the statistical properties of measurement noise changes, this paper puts forward an INS/GNS algorithm based on fuzzy adaptive strong tracking Kalman filter. The algorithm monitors the residue in real-time and adaptively adjusts the soften factor through establishing fuzzy rules. This not only improves the ability of tracking noise, but also guarantees the ability of handling current information. Simulation results prove that this algorithm can restrain the INS error's accumulating with time, and the error of the integrated system has no obvious change when the measurement nose statistical properties have varied. So the precision of the integrated system is ensured, and the robustness is improved.