Analysis of multigroup and multichannel filtering properties in a ferroelectric-dielectric periodic multilayer

2016 ◽  
Vol 55 (24) ◽  
pp. 6630 ◽  
Author(s):  
Tzu-Chyang King ◽  
Ya-Wen Li ◽  
Yu-Huai Li ◽  
Chien-Jang Wu
1975 ◽  
Vol 65 (3) ◽  
pp. 637-650
Author(s):  
E. J. Douze ◽  
G. G. Sorrells

abstract The performance of long-period seismographs is often seriously degraded by atmospheric pressure variation; the problem is particularly severe at periods greater than 20 sec. The pressure variations associated with wind-generated turbulence and acoustic waves are sufficient to deform the surface of the Earth, thus adding to the background noise level recorded by the seismometer. If microbarographs are operated together with the seismograph system, a large percentage of the atmospherically generated noise can be eliminated by the use of optimum filters. The filters are designed based on the least-mean-squares criterion, with the seismograph time trace as the desired output and the microbarographs as the inputs. Single-channel filters, using only one microbarograph, located at the seismometer vault are used to attenuate wind-generated noise. In order to attenuate the noise on windless days from other pressure sources, multichannel filtering is usually necessary and therefore an array of microbarographs is required. The filters used to predict the wind-generated noise are shown to be stable despite the complicated source. The performance of the multichannel varies widely depending on the structure of pressure variations predominating in the atmosphere.


2000 ◽  
Vol 80 (2) ◽  
pp. 279-293 ◽  
Author(s):  
Rey-Sern Lin ◽  
Yung-Cheh Hsueh

Geophysics ◽  
1964 ◽  
Vol 29 (5) ◽  
pp. 672-692 ◽  
Author(s):  
Milo Backus ◽  
John Burg ◽  
Dick Baldwin ◽  
Ed Bryan

The spatial correlation characteristics of ambient short‐period (0.5 to 5 cps) noise at Ft. Sill, Oklahoma, and on the Cumberland Plateau in Tennessee were investigated on “permanent” arrays with 3–4 kilometer diameter. Dominant ambient noise at the two locations is spatially organized, and to first order may be treated as a combination of seismic propagating wave trains. At the Tennessee location noise energy above one cps is dominantly propagating with velocities from 3.5 to 4.5 km/sec, and must be carried in deeply trapped, high‐order modes. Generalized multichannel filtering (Burg) can be used to preserve a large class of mantle P‐wave signals, wide‐band, in a single output trace, while at the same time specifically rejecting ambient noise on the basis of its organization. Results of generalized multichannel filtering applied on‐line at the nineteen‐element array in Tennessee and applied off‐line are discussed.


Geophysics ◽  
2010 ◽  
Vol 75 (6) ◽  
pp. J43-J50 ◽  
Author(s):  
Stefan F. Carpentier ◽  
Heinrich Horstmeyer ◽  
Alan G. Green ◽  
Joseph Doetsch ◽  
Ilaria Coscia

Diffractions from above-surface objects can be a major problem in the processing and interpretation of ground-penetrating radar (GPR) data. Whereas methods to reduce random and many other types of source-generated noise are available, the efficient suppression of above-surface diffractions (ASDs) continues to be challenging. We have developed a scheme for semiautomatically detecting and suppressing ASDs. Initially, an accurate representation of ASDs is obtained by (1) Stolt [Formula: see text] migrating the GPR data using the air velocity to focus ASDs, (2) multichannel filtering to minimize other signals, (3) setting an amplitude threshold that targets the high-amplitude ASDs and effectively eliminates other signals, and (4) Stolt [Formula: see text] demigrating the ASDs using the air velocity, and remigrating them using the ground velocity. By excluding the obliquity correction in the Stolt algorithms and avoiding intermediate amplitude scaling, we preserve the ASDs’ amplitude and phase information. The final stepinvolves subtracting this image of ASDs from a standard migrated version of the original data. This scheme, which includes some important extensions to a previously proposed method, makes it possible to semiautomatically process large volumes of GPR data characterized by numerous highly clustered and overlapping ASDs. The user has control over the tradeoff between ASD suppression and undesired removal of useful signal. It achieves nearly complete removal of ASDs in synthetic data and significant suppression in field data. Once ASDs have been suppressed, their influence can be reduced further by applying relatively gentle multichannel filters. It is not possible to remove line diffractions that resemble subhorizontal reflections or retrieve subsurface signals from data saturated by ASDs, such that some blank regions may be left after applying the suppression scheme. Nevertheless, subsequent processing and interpretation of the GPR data benefit significantly from the suppression of ASDs, which otherwise would clutter the final images.


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