A Method to Detect Multi-components Linear FM Signal

Author

Ling-Huan, Wang ; Hong-Guang, Ma ; Jiawen, Zhang ; Mingshun, Ai

Author_Institution

Res. Inst. of High Technol., Xi´´an

Volume

4

fYear

2006

fDate

16-20 Nov. 2006

Abstract

The support vector clustering (SVC) algorithm was introduced to get the number of the pinnacles in the result of the time-frequency analysis and Radon transform of the multi-component linear FM (LFM) signal, and to finish the detection of the components of the LFM signal. Meanwhile, the preprocessing to reduce the points´ number of the input data-set for SVC, was proposed to improve the computation efficiency. And a novel cluster labeling method was developed to improve the SVC algorithm. The simulation results depict that the SVC-Radon-time-frequency approach is efficient for the detection and parameter estimation of the multi-component LFM signal with low SNR

Keywords

Radon transforms; parameter estimation; signal detection; support vector machines; time-frequency analysis; Radon transform; SVC-Radon-time-frequency approach; cluster labeling method; multi-component linear FM signal detection; parameter estimation; support vector clustering algorithm; time-frequency analysis; Clustering algorithms; Computational modeling; Data preprocessing; Filters; Labeling; Narrowband; Parameter estimation; Signal detection; Static VAr compensators; Time frequency analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing, 2006 8th International Conference on

Conference_Location

Beijing

Print_ISBN

0-7803-9736-3

Electronic_ISBN

0-7803-9736-3

Type

conf

DOI

10.1109/ICOSP.2006.346040

Filename

4129732