Application of the Wavelet Transform in Ultrasonic Echo Signal Processing

2009 ◽  
Author(s):  
Zhen-zhu Yu ◽  
Chong Zhao ◽  
Wei Ma
Keyword(s):  
Signal Processing ◽  
Wavelet Transform ◽  
Echo Signal ◽  
Ultrasonic Echo

scholarly journals Arrival-Time Detection in Wind-Speed Measurement: Wavelet Transform and Bayesian Information Criteria

Sensors ◽  
2020 ◽  
Vol 20 (1) ◽  
pp. 269 ◽  
Author(s):  
Wei Zhang ◽  
Zhipeng Li ◽  
Xuyang Gao ◽  
Yanjun Li ◽  
Yibing Shi
Keyword(s):  
Wavelet Transform ◽  
Wind Speed ◽  
Arrival Time ◽  
Time Window ◽  
Signal To Noise Ratio ◽  
Information Criteria ◽  
Echo Signal ◽  
Time Frequency ◽  
Ultrasonic Echo ◽  
Ultrasonic Anemometer

The time-difference method is a common one for measuring wind speed ultrasonically, and its core is the precise arrival-time determination of the ultrasonic echo signal. However, because of background noise and different types of ultrasonic sensors, it is difficult to measure the arrival time of the echo signal accurately in practice. In this paper, a method based on the wavelet transform (WT) and Bayesian information criteria (BIC) is proposed for determining the arrival time of the echo signal. First, the time-frequency distribution of the echo signal is obtained by using the determined WT and rough arrival time. After setting up a time window around the rough arrival time point, the BIC function is calculated in the time window, and the arrival time is determined by using the BIC function. The proposed method is tested in a wind tunnel with an ultrasonic anemometer. The experimental results show that, even in the low-signal-to-noise-ratio area, the deviation between mostly measured values and preset standard values is mostly within 5 μs, and the standard deviation of measured wind speed is within 0.2 m/s.

Application of Wavelet Transform in Radar Echo Signal Level Meter Denoising

2014 ◽  
Vol 644-650 ◽  
pp. 4399-4402
Author(s):  
Jian Wei Leng ◽  
Ya Ni Guo
Keyword(s):  
Signal Processing ◽  
Wavelet Transform ◽  
Radar System ◽  
Processing Method ◽  
Echo Signal ◽  
Signal Processing Method ◽  
Radar Echo ◽  
Wavelet Transform Analysis ◽  
Level Meter ◽  
Suppress Noise

Radar Level Meter is being more and more widely used in the industry field. However, due to the complex radar system, the noise contained in the clutter echo signal, and the interference within the system and hardware, it is quietly significant to study the research of radar echo reduction technology. Based on the introduction of radar level meter ‘working theory, This paper presents a wavelet transform analysis of the echo signal de-noising method. Studies have shown that the radar echo signal processing method of using wavelet transform can effectively suppress noise, remove interference and achieve echo signal de-noising processing.

Echo signal processing of laser rapid scanning based on wavelet transform

2007 ◽  
Author(s):  
Jinling Chen ◽  
Zhengfeng Xu ◽  
Delin Xie ◽  
Hongbin Chen ◽  
Jian Luo
Keyword(s):  
Signal Processing ◽  
Wavelet Transform ◽  
Echo Signal ◽  
Rapid Scanning

Feature Extraction of Underwater Target Ultrasonic Echo Based on Wavelet Transform

2014 ◽  
Vol 599-601 ◽  
pp. 1517-1522 ◽  
Author(s):  
Zheng Long Wu ◽  
Jie Li ◽  
Zhen Yu Guan
Keyword(s):  
Feature Extraction ◽  
Wavelet Transform ◽  
Signal Amplitude ◽  
Main Task ◽  
Echo Signal ◽  
Denoising Method ◽  
Ultrasonic Echo ◽  
Envelope Extraction ◽  
Underwater Target ◽  
Breaking Points

Ultrasonic detection has been widely used in underwater detectoscopes as an important method for underwater detection. Feature extraction of echo signal time-delay and amplitude is the main task of processing underwater ultrasonic signal. Underwater target ultrasonic echo signal is influenced by reverberation and noise from the sea and system itself, reverberation interference of signal background is the main difficulty for target echo detection. So we use denoising algorithm to denoise echo signal. At first this paper denoises the measured weighted background clutter data using wavelet threshold denoising method, then the paper extracts breaking points of echo signal through wavelet transform, at last the paper makes an envelope extraction using Hilbert transform combined with wavelet transform methods, and acquires the feature information of echo signal amplitude.

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