DocumentCode :
2543277
Title :
Robust recognition of high-frequency CW signal corrupted by impulsive noise
Author :
Li, Guojun ; Lin, Jinzhao ; Zhou, Xiaona
Author_Institution :
Coll. of Commun. Eng., Chongqing Univ., Chongqing, China
fYear :
2012
fDate :
29-31 May 2012
Firstpage :
1929
Lastpage :
1933
Abstract :
High-frequency Continue Wave (CW) telegraph has been an important tactical communication mode. However, this telegraph signal is often corrupted by impulsive disturbance and exhibits serious frequency deviation due to the poor High-frequency channel. As a result, the conventional fixed frequency tracking method based on Gaussian noise assumption may lose the tracking of time-varying CW signal. To enhance its automatic recognition and provide a reliable substitute for human effort, an automatic detection and recognition system is proposed. The system presented here first utilizes a robust extension of Kalman filter to approximate the time-varying CW telegraph waveform in the presence of impulsive interference. Then the Support Vector Machine (SVM) algorithm is applied to the recognition of CW telegraph with unstable code speed. Experimental results indicate that the proposed system could effectively suppress the impulsive noise and provide a high recognition rate for the time-varying CW signal.
Keywords :
Kalman filters; impulse noise; interference suppression; military communication; signal denoising; signal detection; support vector machines; telegraphy; time-varying filters; waveform analysis; CW telegraph recognition; Gaussian noise assumption; Kalman filter; SVM algorithm; automatic detection system; automatic recognition system; fixed frequency tracking method; frequency deviation; high-frequency channel; high-frequency continue wave telegraph; impulsive disturbance; impulsive interference; impulsive noise; robust high-frequency CW signal recognition; support vector machine algorithm; tactical communication mode; telegraph signal; time-varying CW signal tracking; time-varying CW telegraph waveform; Character recognition; Kalman filters; Mathematical model; Noise; Robustness; Support vector machines; Training; Adaptive filter; H; High-frequency (HF) CW telegraph; Kalman filter; M-estimation; Morse Code; Support Vector Machine;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems and Knowledge Discovery (FSKD), 2012 9th International Conference on
Conference_Location :
Sichuan
Print_ISBN :
978-1-4673-0025-4
Type :
conf
DOI :
10.1109/FSKD.2012.6233844
Filename :
6233844
Link To Document :
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