Signal time-frequency analysis for RF emitter detection and location

2018 ◽  
Author(s):  
Huai-Jing Du ◽  
Fred Dilkes
Keyword(s):  
Frequency Analysis ◽  
Time Frequency Analysis ◽  
Time Frequency ◽  
Signal Time

ICE Fault Diagnosis Method Based on Mutual Information and WVD Time-Frequency Analysis

2014 ◽  
Vol 525 ◽  
pp. 741-745 ◽  
Author(s):  
Xin Jun Wang ◽  
Yan Ping Cai ◽  
Xu Ze Lin
Keyword(s):  
Mutual Information ◽  
Frequency Analysis ◽  
Original Signal ◽  
Intrinsic Mode Functions ◽  
Time Frequency Analysis ◽  
Time Frequency ◽  
Modal Component ◽  
Diagnosis Method ◽  
Feature Information ◽  
Signal Time

A new time-frequency analysis method based on mutual information and EMD-WVD time-frequency analysis is proposed. The method uses EMD to decompose signals into independent intrinsic mode functions (IMF), uses the mutual information of EMD intrinsic mode components and original signal as basis to determine EMD false modal component, and uses WVD of EMD true Intrinsic Mode to reconstruct the WVD of original signal for feature information extraction. ICE fault signal time-frequency analysis results show that the proposed method can effectively improve the accuracy of WVD time-frequency analysis, and correctly analyze characteristics of the signal.

Chirp Signal Time-Frequency Analysis Characteristic Comparison

2012 ◽  
Vol 226-228 ◽  
pp. 568-571 ◽  
Author(s):  
Jing Lei Zhou ◽  
Fan Wang
Keyword(s):  
Frequency Analysis ◽  
Chirp Signal ◽  
Analysis Method ◽  
Time Frequency Analysis ◽  
Signal Noise ◽  
Time Frequency ◽  
Sine Signal ◽  
Non Stationary Signal ◽  
Signal Time ◽  
Selection Of

Chirp signal is a typical non-stationary signal, and have been widely used in communication, sonar, radar and so on. So, this signal is worth to analysis. In order to show the characteristics, this paper first introduces the definition and formula of each algorithm, then with all kinds of time-frequency analysis method to the signals, and the signal to add two sine signal noise are analyzed, the comparison of the characteristics of the method in the paper, and the signal for the analysis, the selection of an appropriate analysis. Through analysis and comparison, when dealing with the signal, Hilbert-Huang transformation not only has a better gathered characteristic, but also has a better resolution to distinguish the sine signal noise. Finally, use the MATLAB software simulation to obtain the result.

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