组合导航自适应交互多模型算法研究

针对交互多模型(IMM)方法模型集覆盖能力与计算量相矛盾的问题,提出了将简化的Sage-Husa自适应滤波与IMM相结合,构成一种自适应交互多模型的方法.简化的Sage-Husa自适应滤波首先给出噪声统计特性的粗略值,IMM方法以该粗略值为中心,对称地得到模型集,再进行IMM估计.车栽组合导航仿真表明,该算法能够以较少的模型实现对实际模态的覆盖,而且精度比IMM方法也进一步提高.

Research on algorithm of adaptive interacting multiple model for integrated navigation system

The interacting multiple model(IMM) estimator has the defect that the more sub-models,the worse real-time performance.An adaptive interacting multiple model(AIMM) algorithm is presented,which combines the IMM algorithm with the simplified Sage-Husa adaptive filtering algorithm.The Sage-Husa adaptive filter is used to estimate the rough value of measurement noise statistical characteristics.The parameters of sub-models are calculated by the rough value and then are fed into the sub-filters in IMM algorithm,where the sub-filters have different parameters of noise.Simulation results of land vehicle integrated navigation show that the AIMM algorithm can achieve the coverage of real situation through a few sub-models,and the accuracy is higher than the IMM algorithm.