Practice for Measuring Ultrasonic Velocity in Advanced Ceramics with Broadband Pulse-Echo Cross-Correlation Method

2018 ◽  
Author(s):  
Keyword(s):  
Ultrasonic Velocity ◽  
Cross Correlation ◽  
Correlation Method ◽  
Advanced Ceramics ◽  
Broadband Pulse ◽  
Pulse Echo

scholarly journals A Recursive Algorithm for Indoor Positioning Using Pulse-Echo Ultrasonic Signals

Sensors ◽  
2020 ◽  
Vol 20 (18) ◽  
pp. 5042
Author(s):  
Salvatore A. Pullano ◽  
Maria Giovanna Bianco ◽  
Davide C. Critello ◽  
Michele Menniti ◽  
Antonio La Gatta ◽  
...  
Keyword(s):  
Communication Systems ◽  
Polyvinylidene Fluoride ◽  
Cross Correlation ◽  
Recursive Algorithm ◽  
Low Frequency ◽  
Correlation Method ◽  
Experimental Results ◽  
Ultrasonic Signals ◽  
Average Improvement ◽  
Pulse Echo

Low frequency ultrasounds in air are widely used for real-time applications in short-range communication systems and environmental monitoring, in both structured and unstructured environments. One of the parameters widely evaluated in pulse-echo ultrasonic measurements is the time of flight (TOF), which can be evaluated with an increased accuracy and complexity by using different techniques. Hereafter, a nonstandard cross-correlation method is investigated for TOF estimations. The procedure, based on the use of template signals, was implemented to improve the accuracy of recursive TOF evaluations. Tests have been carried out through a couple of 60 kHz custom-designed polyvinylidene fluoride (PVDF) hemicylindrical ultrasonic transducers. The experimental results were then compared with the standard threshold and cross-correlation techniques for method validation and characterization. An average improvement of 30% and 19%, in terms of standard error (SE), was observed. Moreover, the experimental results evidenced an enhancement in repeatability of about 10% in the use of a recursive positioning system.

Application of cross correlation to HREM images of surfaces

1987 ◽  
Vol 45 ◽  
pp. 754-755
Author(s):  
D. E. Luzzi ◽  
L. D. Marks ◽  
M. I. Buckett
Keyword(s):  
Cross Correlation ◽  
A Priori ◽  
Matrix Material ◽  
Correlation Method ◽  
Accurate Knowledge ◽  
Complex Image ◽  
Fourier Filtering ◽  
The Matrix ◽  
Low Pass ◽  
Data Reduction Technique

As the HREM becomes increasingly used for the study of dynamic localized phenomena, the development of techniques to recover the desired information from a real image is important. Often, the important features are not strongly scattering in comparison to the matrix material in addition to being masked by statistical and amorphous noise. The desired information will usually involve the accurate knowledge of the position and intensity of the contrast. In order to decipher the desired information from a complex image, cross-correlation (xcf) techniques can be utilized. Unlike other image processing methods which rely on data massaging (e.g. high/low pass filtering or Fourier filtering), the cross-correlation method is a rigorous data reduction technique with no a priori assumptions.We have examined basic cross-correlation procedures using images of discrete gaussian peaks and have developed an iterative procedure to greatly enhance the capabilities of these techniques when the contrast from the peaks overlap.

Cross-Correlation Method for the Formation of Laser Energy Fields with Complex Distributions

2013 ◽  
Vol 58 (2) ◽  
pp. 122-125 ◽  
Author(s):  
O.V. Gnatovskyy ◽  
◽  
A.M. Negriyko ◽  
V.O. Gnatovskyy ◽  
A.V. Sidorenko ◽  
...  
Keyword(s):  
Cross Correlation ◽  
Laser Energy ◽  
Correlation Method

scholarly journals A Novel Gesture Recognition System Based on CSI Extracted from a Smartphone with Nexmon Firmware

Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 222
Author(s):  
Tao Li ◽  
Chenqi Shi ◽  
Peihao Li ◽  
Pengpeng Chen
Keyword(s):  
Frequency Domain ◽  
Gesture Recognition ◽  
Channel State Information ◽  
Cross Correlation ◽  
Recognition Accuracy ◽  
Correlation Method ◽  
Bottom Layer ◽  
Recognition System ◽  
Channel State ◽  
State Information

In this paper, we propose a novel gesture recognition system based on a smartphone. Due to the limitation of Channel State Information (CSI) extraction equipment, existing WiFi-based gesture recognition is limited to the microcomputer terminal equipped with Intel 5300 or Atheros 9580 network cards. Therefore, accurate gesture recognition can only be performed in an area relatively fixed to the transceiver link. The new gesture recognition system proposed by us breaks this limitation. First, we use nexmon firmware to obtain 256 CSI subcarriers from the bottom layer of the smartphone in IEEE 802.11ac mode on 80 MHz bandwidth to realize the gesture recognition system’s mobility. Second, we adopt the cross-correlation method to integrate the extracted CSI features in the time and frequency domain to reduce the influence of changes in the smartphone location. Third, we use a new improved DTW algorithm to classify and recognize gestures. We implemented vast experiments to verify the system’s recognition accuracy at different distances in different directions and environments. The results show that the system can effectively improve the recognition accuracy.

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