Ultrasound field estimation method using a secondary source-array numerically constructed from a limited number of pressure measurements

2000 ◽  
Vol 107 (6) ◽  
pp. 3259-3265 ◽  
Author(s):  
Xiaobing Fan ◽  
Eduardo G. Moros ◽  
William L. Straube
Keyword(s):  
Estimation Method ◽  
Secondary Source ◽  
Pressure Measurements ◽  
Ultrasound Field ◽  
Field Estimation ◽  
Source Array

Far-Field Performances Prediction of High Frequency Projectors Using Secondary Source Array Method

2016 ◽  
Vol 25 (02) ◽  
pp. 1750002 ◽  
Author(s):  
Shiquan Wang
Keyword(s):  
High Frequency ◽  
Near Field ◽  
Directivity Pattern ◽  
Field Method ◽  
Voltage Response ◽  
Secondary Source ◽  
Far Field ◽  
Comparison Of The Results ◽  
Source Array ◽  
Good Agreement

This paper investigates the prediction of the far-field performances of high frequency projectors using the second source array method (SSAM). The far-field parameters can be calculated accurately using the complex acoustic pressure data of two very close parallel planes which lie in the near-field region of the projector. The paper simulates the feasibility of predicting the far-field parameters such as transmitting voltage response and the far-field directivity pattern. The predicting results are compared with that calculated using boundary element method (BEM). It shows very good agreement between the two methods. A planar high frequency projector is measured using the near-field method. In order to verify the predicting results, the far-field measurement is performed for the same projector. The comparison of the results shows that the near-field method is capable to precisely predict the far-field parameters of the projector.

Wavelet estimation for a multidimensional acoustic or elastic earth

Geophysics ◽  
1990 ◽  
Vol 55 (7) ◽  
pp. 902-913 ◽  
Author(s):  
Arthur B. Weglein ◽  
Bruce G. Secrest
Keyword(s):  
Estimation Method ◽  
Normal Derivative ◽  
Source Spectrum ◽  
Earth Model ◽  
Far Field ◽  
Wavelet Estimation ◽  
Seismic Wavelet ◽  
Array Pattern ◽  
The Earth ◽  
Source Array

A new and general wave theoretical wavelet estimation method is derived. Knowing the seismic wavelet is important both for processing seismic data and for modeling the seismic response. To obtain the wavelet, both statistical (e.g., Wiener‐Levinson) and deterministic (matching surface seismic to well‐log data) methods are generally used. In the marine case, a far‐field signature is often obtained with a deep‐towed hydrophone. The statistical methods do not allow obtaining the phase of the wavelet, whereas the deterministic method obviously requires data from a well. The deep‐towed hydrophone requires that the water be deep enough for the hydrophone to be in the far field and in addition that the reflections from the water bottom and structure do not corrupt the measured wavelet. None of the methods address the source array pattern, which is important for amplitude‐versus‐offset (AVO) studies. This paper presents a method of calculating the total wavelet, including the phase and source‐array pattern. When the source locations are specified, the method predicts the source spectrum. When the source is completely unknown (discrete and/or continuously distributed) the method predicts the wavefield due to this source. The method is in principle exact and yet no information about the properties of the earth is required. In addition, the theory allows either an acoustic wavelet (marine) or an elastic wavelet (land), so the wavelet is consistent with the earth model to be used in processing the data. To accomplish this, the method requires a new data collection procedure. It requires that the field and its normal derivative be measured on a surface. The procedure allows the multidimensional earth properties to be arbitrary and acts like a filter to eliminate the scattered energy from the wavelet calculation. The elastic wavelet estimation theory applied in this method may allow a true land wavelet to be obtained. Along with the derivation of the procedure, we present analytic and synthetic examples.

scholarly journals Bioinspired wind field estimation—part 1: Angle of attack measurements through surface pressure distribution

2018 ◽  
Vol 10 (3) ◽  
pp. 273-284 ◽  
Author(s):  
Nikola Gavrilovic ◽  
Murat Bronz ◽  
Jean-Marc Moschetta ◽  
Emmanuel Benard
Keyword(s):  
Angle Of Attack ◽  
Time Estimation ◽  
Pressure Measurements ◽  
Surface Pressure Distribution ◽  
Additional Equipment ◽  
Field Estimation ◽  
Aerial Vehicle ◽  
Unsteady Interaction ◽  
Wind Vane ◽  
Local Angle

One of the major challenges of Mini-Unmanned Aerial Vehicle flight is the unsteady interaction with turbulent environment while flying in lower levels of atmospheric boundary layer. Following inspiration from nature we expose a new system for angle of attack estimation based on pressure measurements on the wing. Such an equipment can be used for real-time estimation of the angle of attack during flight or even further building of wind velocity vector with additional equipment. Those information can find purpose in control and stabilization of the aircraft due to inequalities seen by the wing or even for various soaring strategies that rely on active control for energy extraction. In that purpose, flying wing aircraft has been used with totally four span-wise locations for local angle of attack estimation. In-flight angle of attack estimation from differential pressure measurements on the wing has been compared with magnetic sensor with wind vane. The results have shown that pressure ports give more reliable estimation of angle of attack when compared to values given by wind vane attached to a specially designed air-boom. Difference in local angle of attack at four span-wise locations has confirmed spatial variation of turbulence in low altitude flight. Moreover, theoretical law of energy dissipation for wind components described by Kaimal spectrum has shown acceptable match with estimated ones.

scholarly journals Fast Far-Field Estimation Method by Compact Single Cut Near-Field Measurements for Electrically Long Antenna Array

2018 ◽  
Vol 66 (11) ◽  
pp. 5859-5868 ◽  
Author(s):  
Yoshiki Sugimoto ◽  
Hiroyuki Arai ◽  
Toshiyuki Maruyama ◽  
Masahiko Nasuno ◽  
Masanobu Hirose ◽  
...  
Keyword(s):  
Antenna Array ◽  
Near Field ◽  
Estimation Method ◽  
Field Measurements ◽  
Far Field ◽  
Field Estimation

Horizontal wind field estimation method based on dual Lidars

2019 ◽  
Vol 48 (10) ◽  
pp. 1005008
Author(s):  
庄子波 Zhuang Zibo ◽  
陈 星 Chen Xing ◽  
台宏达 Tai Hongda ◽  
宋德龙 Song Delong ◽  
徐丰田 Xu Fengtian ◽  
...  
Keyword(s):  
Wind Field ◽  
Estimation Method ◽  
Horizontal Wind ◽  
Field Estimation
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