Using linear smoothing to improve the modulation recognition performance

Automatic classification of modulation signals plays an important role in communication applications such as speech recognition, intelligent demodulator and electronic warfare etc. But how to improve the performance of the modulation classification algorithms in low SNR condition is an important pro...

Full description

Saved in:
Bibliographic Details
Main Authors: Yafeng Yao, Zailu Huang
Format: Conference Proceeding
Language:English
Subjects:
Automatic speech recognition
Classification algorithms
Demodulation
Electronic warfare
Monitoring
Noise reduction
Signal processing
Signal to noise ratio
Smoothing methods
Speech recognition
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Automatic classification of modulation signals plays an important role in communication applications such as speech recognition, intelligent demodulator and electronic warfare etc. But how to improve the performance of the modulation classification algorithms in low SNR condition is an important problem during their practical application. We present a method that adopts linear smoothing to preprocess the intercepted signal, decreases the influence of the noise to the signal characteristic and then extracts the key features, so the features are reliable to antijamming and can identify the various signals in low SNR range. Simulation indicates the linear smoothing process is simply computed aid the improvement of the algorithm that used it is effective.
DOI:10.1109/NLPKE.2003.1275873