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Time-varying optimal distributed fusion white noise deconvolution estimator

  • Research Article
  • Published:
Frontiers of Electrical and Electronic Engineering

Abstract

White noise deconvolution has a wide range of applications including oil seismic exploration, communication, signal processing, and state estimation. Using the Kalman filtering method, the time-varying optimal distributed fusion white noise deconvolution estimator is presented for the multisensor linear discrete time-varying systems. It is derived from the centralized fusion white noise deconvolution estimator so that it is identical to the centralized fuser, i.e., it has the global optimality. It is superior to the existing distributed fusion white noise estimators in the optimality and the complexity of computation. A Monte Carlo simulation for the Bernoulli-Gaussian input white noise shows the effectiveness of the proposed results.

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Authors and Affiliations

  1. College of Electrical Engineering, Heilongjiang University, Harbin, 150080, China

    Xiaojun Sun & Guangming Yan

Authors
  1. Xiaojun Sun
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  2. Guangming Yan
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Correspondence to Xiaojun Sun.

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Sun, X., Yan, G. Time-varying optimal distributed fusion white noise deconvolution estimator. Front. Electr. Electron. Eng. 7, 318–325 (2012). https://doi.org/10.1007/s11460-012-0202-2

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  • DOI: https://doi.org/10.1007/s11460-012-0202-2

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