Computer Science ›› 2019, Vol. 46 ›› Issue (6): 118-123.doi: 10.11896/j.issn.1002-137X.2019.06.017

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Improved FCME Algorithm Based on Binary Searching by Mean and Its Applicationsin E/SLF Channel Noise Detection

ZHAO Peng, JIANG Yu-zhong, ZHAI Qi, LI Chun-teng   

  1. (College of Electronic Engineering,Naval University of Engineering,Wuhan 430033,China)
  • Received:2018-05-11 Published:2019-06-24

Abstract: Extreme/Super Low Frequency (E/SLF,3 ~300 Hz) channel noise (CN) impulses are usually passivated by the transient effects in the receivers’ front-end stages,and it will cause the performance degradation for the common time-domain amplitude-based threshold detectors.Aiming at this problem,this paper proposed a detection method based on the constant false alarm rate ordering statistics (OS-CFAR) through local variance domain transforming (LVDT).In light of the potential divergency problem when FCME algorithm iteratively evaluates the background noise,this paper also presented an improved method namely binary searching method by mean (BSMM).BSMM doesn’t need to assume the initial clean set or sort process,and thus is more robust and has higher efficiency.Simulations show that the proposed method can reduce the computing time by more than 2 orders without losing estimation accuracy of background noise compared with the common FCME.Besides,the proposed CN detection method outperforms the local optimum threshold nonlinearities method (LOTNI).

Key words: Background noise estimation, Binary searching by mean, Channel noise detection, E/SLF communication, FCME algorithm

CLC Number: 

  • TN911.4
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