介绍了作为粒子滤波理论基础的递推贝叶斯估计的基本概念，说明了重要性函数对于粒子滤波器的设计是至关重要的。

The principle of Recursive Bayesian estimation was introduced which was the basis of Particle filter, and the significance of importance function to the design of particle filter was illustrated.

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通过假设预测方位和实测方位差值服从零均值的高斯分布，利用贝叶斯理论来修正各滤波器的权重。

And the weight of each filter is updated using Bayes theory based on the assumption that the difference between estimate and measurement bearings obeys Gaussian distributions with zero mean error.

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通过假设预测方位和实测方位差值服从零均值的高斯分布，利用贝叶斯理论来修正各滤波器的权重。

And the weight of each filter is updated using Bayes theory based on the assumption that the difference between estimate and measurement bearings obeys Gaussian distributions with zero mean error.

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