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首页> 外文会议>IEEE International Conference on Information and Automation >IMM-UKF Based Land-Vehicle Navigation With Low-Cost GPS/INS
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IMM-UKF Based Land-Vehicle Navigation With Low-Cost GPS/INS

机译：基于IMM-UKF的陆车载导航，低成本GPS / INS

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The motivation of INS/GPS integration is to develop a navigation system that overcomes the shortcomings of each system. Its implementation is essentially based on the filter techniques and error models of INS. If the model changes with the environment, the estimation accuracy is degraded. In this paper, an Interacting Multiple Model Unscented Kalman Filter (IMM-UKF) method was proposed to jointly estimate the position information. This modeling approach makes it possible to employ the UKF to deal with the problem of nonlinear filtering with uncertainty noise. The output of the IMM-UKF is the weighted sum of a bank of parallel unscented Kalman filters. Simulations show that compared with the conventional Kalman filtering approach, the IMM-UKF algorithm is more stable and effective, thus improving the convergence speed and accuracy.
机译：INS / GPS集成的动机是开发一种导航系统，克服了每个系统的缺点。其实现基本上基于INS的滤波器技术和错误模型。如果模型随环境变化，则估计精度会降低。在本文中，提出了一种互复制的卡尔曼滤波器（IMM-UKF）方法，共同估计位置信息。这种建模方法使得可以使用UKF来处理非线性滤波的非线性滤波问题。 IMM-UKF的输出是并行无需卡尔曼滤波器银行的加权总和。仿真表明，与传统的卡尔曼滤波方法相比，IMM-UKF算法更稳定且有效，从而提高了收敛速度和精度。

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