DocumentCode :
3274898
Title :
Time-frequency representations for classification of ground penetrating radar echo signal
Author :
Zhou, Hui-Lin ; Tian, Mao ; Chen, Xiao-Li
Author_Institution :
Sch. of Electron. Inf., Wuhan Univ., China
fYear :
2005
fDate :
13-16 Dec. 2005
Firstpage :
597
Lastpage :
600
Abstract :
This paper deals with the classification of ground penetrating radar (GPR) echo signal using time-frequency representations. The algorithm fulfills automatically feature extraction and classification of the ground penetrating radar echo signal. We first use auto-ambiguity function as signal representation, which does not use time-frequency smoothing kernel to reduce cross-term. Cross-term is interference for visualization interpretation, but for classification it may be valuable information. Then we use Fisher´s discriminant ratio to rank the discriminant information of features, and in combination with using classification error rate of learning vector quantization neural network as evaluation function to select optimal features subset. Experimental results based on simulated and measured GPR data are presented.
Keywords :
feature extraction; ground penetrating radar; neural nets; quantisation (signal); radar computing; radar signal processing; signal classification; signal representation; GPR echo signal; auto-ambiguity function; feature extraction; ground penetrating radar; learning vector quantization neural network; signal classification; signal representation; time-frequency representations; Error analysis; Feature extraction; Ground penetrating radar; Interference; Kernel; Signal representations; Smoothing methods; Time frequency analysis; Vector quantization; Visualization; Fisher´s discriminant ratio (FDR); Time-frequency representations (TFRs); ground penetrating radar (GPR); learning vector quantization (LVQ) neural network;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Signal Processing and Communication Systems, 2005. ISPACS 2005. Proceedings of 2005 International Symposium on
Print_ISBN :
0-7803-9266-3
Type :
conf
DOI :
10.1109/ISPACS.2005.1595480
Filename :
1595480
Link To Document :
بازگشت