Study of ocean ambient noise characteristics based on vector signal processing of acoustic

2012 ◽  
Vol 131 (4) ◽  
pp. 3484-3484
Author(s):  
Jialiang Li ◽  
Jianheng Lin ◽  
Xuejuan Yi
Keyword(s):  
Signal Processing ◽  
Ambient Noise ◽  
Noise Characteristics ◽  
Vector Signal

The Application of Single Vector Sensor in Direction Tracing of Water-Entry Object

2013 ◽  
Vol 341-342 ◽  
pp. 601-604
Author(s):  
Di Xiao ◽  
Lan Yue Zhang
Keyword(s):  
Signal Processing ◽  
Particle Velocity ◽  
Sound Intensity ◽  
Water Entry ◽  
Azimuth Angle ◽  
Velocity Signal ◽  
Complex Sound ◽  
Simulating Experiment ◽  
Vector Sensor ◽  
Vector Signal

Water-entry signal was important to broadcast the water-entry object. The vector sensor could gain the pressure and particle velocity signal, so the azimuth angle of water-entry signal could be estimated by single vector sensor. The complex sound intensity method was applied in vector signal processing in azimuth estimation. The estimated deviation in different SNR was give out via simulating experiment. The method was used in the experiment on the lake and was proved to be effective.

Low-frequency ambient noise characteristics and budget in the South China Sea basin

2012 ◽  
Vol 132 (3) ◽  
pp. 2057-2057
Author(s):  
Ching-Sang Chiu ◽  
Christopher W. Miller ◽  
John E. Joseph
Keyword(s):  
South China Sea ◽  
South China ◽  
Ambient Noise ◽  
Low Frequency ◽  
The South China Sea ◽  
The South ◽  
China Sea ◽  
Noise Characteristics

Signal Processing of Fluorescent Optical Fiber Temperature Measurement Based on Hilbert-Huang Transform

2014 ◽  
Vol 1052 ◽  
pp. 447-453
Author(s):  
Ya Juan Yang ◽  
Zhi Yong Wang ◽  
Xiao Ping Yang ◽  
Yong Xin Shao
Keyword(s):  
Signal Processing ◽  
Optical Fiber ◽  
Temperature Measurement ◽  
Electromagnetic Interference ◽  
Signal To Noise Ratio ◽  
Extreme Environment ◽  
Intrinsic Mode Functions ◽  
Hilbert Huang Transform ◽  
Noise Characteristics ◽  
Novel Approach

The technology of fluorescent optical fiber temperature measurement has been used in many fields to accurately measure the variations of temperature, especially in some extreme environment, such as strong electromagnetic interference under, high voltage conditions. Wavelet analysis is the most frequent method used for signal processing in this technology. This method has excellent local characteristics and its precise of processing is high, whereas its result relies heavily on the selection of the wavelet basis, and has certain limitation. In this paper, a novel approach for fluorescent signal processing based on Hilbert-Huang transform is presented. A given signal is decomposed into a collection of intrinsic mode functions (IMF) by empirical mode decomposition, then Hilbert spectral analysis is performed for each of the IMF. According to the difference of signal and noise characteristics, HHT can generate adaptive modal functions and remove the noise from signal effectively, so that the signal to noise ratio can be improved. The result of experiment shows that HHT features convenient usage, fast processing and high resolution in time and frequency domains.

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