Narrowband Interference Suppression Using RKF-Based Recurrent Neural Network in Spread Spectrum System

2008 ◽  
Author(s):  
Ding-Jie Xu ◽  
Pi-Jie Zhao ◽  
Feng Shen ◽  
Hong Zhao
Keyword(s):  
Neural Network ◽  
Recurrent Neural Network ◽  
Spread Spectrum ◽  
Interference Suppression ◽  
Narrowband Interference

Interference Suppression for Satellite Navigation Based on Neural Network and Wavelet Packets Transform

2012 ◽  
Vol 457-458 ◽  
pp. 1111-1117
Author(s):  
Yang Chun Shi ◽  
You Bao Liu
Keyword(s):  
Neural Network ◽  
Spread Spectrum ◽  
Simple Structure ◽  
Interference Suppression ◽  
Direct Sequence Spread Spectrum ◽  
Wavelet Packets ◽  
Interference Signal ◽  
Transform Domain ◽  
System A ◽  
Data Adaptive

To suppress the interference in the direct sequence spread spectrum (DSSS) system, a transform domain message data adaptive identify (TISI) algorithm is proposed in this paper, based on two improved algorithms: Power distributing predominance wavelet packets transform (PDP-WPT) and extended BP neural network (EBPNN). Firstly, PDP-WPT is presented to track the interference signal effectively, which improves the convergence rate of TISI. Secondly, the message data can be identified in transform domain by adaptability EBPNN, which has simple structure and enhanced numerical robustness. Simulation results show that TISI can improve the capability of interference suppression by 32% compared with widely used conventional algorithms.

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