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gaussian_filter

于 2020-03-29 发布
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说明:  本文针对基于高斯分布的非线性滤波问题,开发并分析了实时和精确滤波器。我们提出了高斯滤波器的系统公式,并开发了高效和精确的数值积分。我们还讨论了混合高斯滤波器,其中条件概率密度由高斯分布之和近似。数值试验表明,新的滤波器在不增加额外费用的情况下显著地改善了扩展卡尔曼滤波器,并且新的高斯和滤波器具有接近最优的性能(In this paper we develop and analyze real-time and ac- curate filters for nonlinear filtering problems based on the Gaussian distributions. We present the systematic formulation of Gaussian filters and develop efficient and accurate numerical integration of the proposed filter. We also discuss the mixed Gaussian filters in which the conditional probability density is approximated by the sum of Gaussian distributions. Our numerical testings demonstrate that new filters significantly improve the extended Kalman filter with no additional cost and the new Gaussian sum filter .has a nearly optimal perfor- mance.)

文件列表:

gaussian_filter.m, 2645 , 2018-07-11

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