Title
A Detection Method of Radar Signal by Wavelet Transforms
Abstract
In this paper, an effective detection method of radar signal is presented based on the wavelet analysis. The purpose of this paper is to provide the review of the wavelet analysis research and to detect radar target from radar echo. The theory of wavelet analysis is presented including continuous and discrete wavelet transform. Then specific application, namely radar target detection is presented. In this paper, using wavelet transform to preprocess the radar echo, we are able to obtain multiple data series at different scales of the wavelet transform. These multiple data series can then be used as input to sensors of independent component analysis for detection of a single independent source. The proposed method is applied to radar target detection using a real signal series. It is demonstrated that the method in combination with wavelet transform is effective with feasible result. It has greater theoretical significance and actual applied value in regarded to radar signal processing and target identifying in our aerial defense weapon system.
Year
DOI
Venue
2007
10.1109/FSKD.2007.18
FSKD (2)
Keywords
Field
DocType
radar target,discrete wavelet,wavelet analysis,radar signal detection method,real signal series,wavelet transforms,radar cross-sections,radar signal,multiple data series,detection method,independent component analysis,radar signal processing,aerial defense weapon system,wavelet analysis research,radar target detection,radar detection,radar echo,military radar,effective detection method,discrete wavelet transform,wavelet transform
Radar,Lifting scheme,Pattern recognition,Computer science,Second-generation wavelet transform,Discrete wavelet transform,Artificial intelligence,Stationary wavelet transform,Wavelet packet decomposition,Wavelet,Wavelet transform
Conference
Volume
ISBN
Citations 
2
978-0-7695-2874-8
2
PageRank 
References 
Authors
0.41
4
4
Name
Order
Citations
PageRank
Shanwen Zhang131734.71
Jianbo Fan284.06
Lidan Shou337048.66
Jinxiang Dong431165.36