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首页> 外文期刊>IEEE Transactions on Automatic Control >A nonlinear filtering algorithm based on an approximation of theconditional distribution
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A nonlinear filtering algorithm based on an approximation of theconditional distribution

机译：基于条件分布近似的非线性滤波算法

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摘要

An effective form of the Gaussian or moment approximation method for approximating optimal nonlinear filters with a diffusion signal process and discrete-time observations is presented. Various computational simplifications reduce the dimensionality of the numerical integrations that need to be done. This process, combined with an iterative Gaussian quadrature method, makes the filter effective for real-time use. The advantages are illustrated by a model that captures the general flavour of modeling the highly uncertain behavior of a ship near obstacles such as a shore line into which it cannot go, and must manoeuvre away in some unknown fashion. The observations are of very poor quality, yet the filter behaves well and is quite stable. The procedure does not rely on linearization, but attempts to compute the conditional moments directly by approximating the integrations used by the optimal filter
机译：提出了一种高斯或矩逼近方法的有效形​​式，该方法可通过扩散信号过程和离散时间观测值逼近最佳非线性滤波器。各种计算上的简化降低了需要进行的数值积分的维数。此过程与迭代高斯正交方法相结合，使滤波器对于实时使用有效。模型的优点体现在模型上，该模型捕捉了对障碍物（如无法进入的海岸线）附近的高度不确定行为进行建模的一般风格，并且必须以某种未知的方式进行操纵。观察结果的质量很差，但是滤波器的性能很好并且非常稳定。该过程不依赖于线性化，而是尝试通过近似最佳滤波器使用的积分来直接计算条件矩

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