@inproceedings{4c918cd04f384c04acade166aba12ffb,
title = "Novel detection method for multi-component LFM signals",
abstract = "Multi-components Linear Frequency-Modulated (LFM) signal of emitter recognition is everywhere in signal environments in practice, it is important to recognize it for electronic intelligence. To effectively detect and recognize multi-component LFM emitter signals, a new emitter signal analysis method based on the complex Independent Component Analysis(ICA), second-order time moments and Wigner-Hough transform(WHT) (ISW) was proposed. The idea which was adopted to this method was the time-domain separation, the LFM signal and noise discrimination and time-frequency analysis. In the low SNR cases, the problem which is generally plagued by noised of feature extraction of multi-component LFM signal based on Wigner-Hough transform is overcome. Compared to the traditional method of time-frequency analysis, the computer simulation results show that the proposed method for the multi-component LFM signal separation and feature extraction was better.",
keywords = "Feature extraction, ISW, Multi-component LFM emitter signal, Time-frequency analysis",
author = "Qiang Guo and Li, \{Ya Jun\} and Wang, \{Chang Hong\} and Cao, \{He Yang\}",
year = "2010",
doi = "10.1109/PCSPA.2010.189",
language = "英语",
isbn = "9780769541808",
series = "Proceedings - 2010 1st International Conference on Pervasive Computing, Signal Processing and Applications, PCSPA 2010",
pages = "759--762",
booktitle = "Proceedings - 2010 1st International Conference on Pervasive Computing, Signal Processing and Applications, PCSPA 2010",
note = "1st International Conference on Pervasive Computing, Signal Processing and Applications, PCSPA 2010 ; Conference date: 17-09-2010 Through 19-09-2010",
}