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An Improved Interacting Multiple Model Algorithm for INS/DVL Integrated Navigation System

机译:INS / DVL组合导航系统的一种改进的交互多模型算法

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In Inertial Navigation System (INS)/ Doppler Velocity Log (DVL) integrated navigation system, due to the time-varying measurement noise, the inaccurate measurement model results in substantial estimation errors or even filter divergence. To address this problem, Interacting Multiple Model (IMM) algorithm which uses more than one model is always considered. The efficiency of IMM algorithm depends on the accuracy of model set. In order to cover the real model with smaller model set, an Improved IMM(IIMM) algorithm is proposed in this paper. A variable model set based on the model probability weighted average of the model parameter is generated to pursue the real model. Meanwhile, the time-varying state transition probability matrix based on model probability difference is introduced to accelerate the switch of model set to the true model. Simulation and experiment indicate that the model set can cover the true model rapidly and precisely with only three models, and the accuracy of the SINS/DVL integrated navigation system is improved by applying the proposed method.
机译:在惯性导航系统(INS)/多普勒速度测井(DVL)集成导航系统中,由于测量噪声随时间变化,因此不准确的测量模型会导致相当大的估计误差,甚至会导致滤波器发散。为了解决此问题,始终考虑使用多个模型的交互多模型(IMM)算法。 IMM算法的效率取决于模型集的准确性。为了用较小的模型集覆盖真实模型,提出了一种改进的IMM(IIMM)算法。生成基于模型参数的模型概率加权平均值的变量模型集,以追求真实模型。同时,引入了基于模型概率差异的时变状态转移概率矩阵,以加速模型集向真实模型的转换。仿真和实验表明,该模型集仅用三个模型就可以快速,准确地覆盖真实模型,通过应用该方法可以提高SINS / DVL组合导航系统的精度。

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