Kalman Filtering of Fractal Stochastic Signals Based on Wavelet Transform

ZHAO Juan; MA Hong; YOU Zhi-sheng; Michio Umeda

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Kalman Filtering of Fractal Stochastic Signals Based on Wavelet Transform

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- Kalman Filtering of Fractal Stochastic Signals Based on Wavelet Transform
- Acta Electronica Sinica Vol. 29, Issue 9, Pages: 1157-1160(2001)
- 作者机构：
  
  1. 四川大学数学学院,四川,成都,610064
  2. 四川大学计算机学院,四川,成都,610064
  3. 大阪电气通信大学情报工学部,日本大阪府寝屋川市
  4. 四川大学数学学院四川成都,610064
  5. 四川大学计算机学院四川成都,610064
  6. 大阪电气通信大学情报工学部日本大阪府寝屋川市
- 作者简介：
- 基金信息：
- DOI：
  CLC： TN911.7
- Published：2001
- 稿件说明：
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ZHAO Juan, MA Hong, YOU Zhi-sheng, et al. Kalman Filtering of Fractal Stochastic Signals Based on Wavelet Transform[J]. Acta Electronica Sinica, 2001, 29(9): 1157-1160.
DOI：

ZHAO Juan, MA Hong, YOU Zhi-sheng, et al. Kalman Filtering of Fractal Stochastic Signals Based on Wavelet Transform[J]. Acta Electronica Sinica, 2001, 29(9): 1157-1160. DOI：

摘要

本文基于多尺度卡尔曼滤波方法来估计淹没在加性高斯白噪声中的分形布朗运动.针对每一尺度

给出了相应的动态系统参数和运动模型方程以及更精确的估计算法.并与多尺度维纳滤波进行了对比

计算机仿真结果证明了其优越性.

Abstract

A filter bank design based on orthonormal wavelets and equipped with a multiscale Kalman filter was recently proposed for estimating fractal Brownian motion in additive Gaussian white noise.In this paper

we give the corresponding parameters of the dynamic system and more accurate estimation algorithm.Comparisons between Wiener and Kalman filters are given.Typical computer simulation results demonstrate its feasibility and effectiveness.

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