A new method of weak signal detection based on improved matching pursuit algorithm

Author

Xu, Gang ; Gao, Jie

Author_Institution

Dept. of Electr. & Electron. Eng., North China Electr. Power Univ., Beijing

fYear

2008

fDate

1-8 June 2008

Firstpage

538

Lastpage

542

Abstract

In this paper, the theory of sparse decomposition is introduced to weak signal detection, and the improved matching pursuit (MP) algorithm is studied to accomplish anti-interference process of some typical signals, such as a weak sine wave signal submerged in strong noises. The improved matching pursuit algorithm uses dual-parameter Gabor dictionary, and the iterative times can be modified in accordance with the signal to noise ratio (SNR), the genetic algorithm is also used to improve the efficiency of searching time-frequency atoms, thereby achieving high searching efficiency of time-frequency atoms and rapid noise restraining. The results of experiments indicated that the improved algorithm can effectively increase the searching speed by approximately 100 times and reduce the noises above SNR -15.

Keywords

genetic algorithms; iterative methods; signal detection; time-frequency analysis; Gabor dictionary; anti-interference process; genetic algorithm; improved matching pursuit algorithm; signal-to-noise ratio; sparse decomposition theory; weak signal detection; Dictionaries; Genetic algorithms; Iterative algorithms; Matching pursuit algorithms; Noise reduction; Pursuit algorithms; Signal detection; Signal processing; Signal to noise ratio; Time frequency analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 2008. IJCNN 2008. (IEEE World Congress on Computational Intelligence). IEEE International Joint Conference on

Conference_Location

Hong Kong

ISSN

1098-7576

Print_ISBN

978-1-4244-1820-6

Electronic_ISBN

1098-7576

Type

conf

DOI

10.1109/IJCNN.2008.4633845

Filename

4633845