scholarly journals Multipole Theory and Algorithms for Target Support Estimation

2013 ◽  
Vol 2013 ◽  
pp. 1-15 ◽  
Author(s):  
Edwin A. Marengo
Keyword(s):  
Inverse Problem ◽  
Helmholtz Equation ◽  
Inverse Scattering ◽  
Scattered Field ◽  
Source Region ◽  
Multipole Expansion ◽  
Source Regions ◽  
Support Estimation

The inverse problem of estimating the smallest region of localization (minimum source region) of a source or scatterer that can produce a given radiation or scattered field is investigated with the help of the multipole expansion. The results are derived in the framework of the scalar Helmholtz equation. The proposed approach allows the estimation of possibly nonconvex minimum source regions. The derived method is illustrated with an example relevant to inverse scattering.

scholarly journals Inverse Diffraction Theory and Computation of Minimum Source Regions of Far Fields

2014 ◽  
Vol 2014 ◽  
pp. 1-18 ◽  
Author(s):  
Edwin A. Marengo
Keyword(s):  
Electromagnetic Waves ◽  
Source Region ◽  
Diffraction Theory ◽  
Multipole Expansion ◽  
Transverse Magnetic ◽  
Far Field ◽  
Scattering Problems ◽  
Source Regions ◽  
Inverse Diffraction ◽  
The Given

A methodology based on the multipole expansion is developed to estimate the minimum source region of a given far field. The support of any source that produces the given far field must contain this minimum source region. The results are derived in the framework of the scalar Helmholtz equation in two-dimensional free space, which is relevant to transverse magnetic electromagnetic waves. The proposed approach consists of two steps. First we address, via an exterior inverse diffraction framework, the estimation of the minimum convex source region, which is the convex hull of the minimum source region. Next we compute, via a complementary interior inverse diffraction approach, nonconvex bounds for the minimum source region. This allows, in theory, the estimation of the minimum source region which can be nonconvex. The derived approach is illustrated with analytical and numerical examples relevant to inverse source and scattering problems.

scholarly journals Melt segregation from partially molten source regions: The importance of melt density and source region size

1981 ◽  
Vol 86 (B7) ◽  
pp. 6261-6271 ◽  
Author(s):  
Edward Stolper ◽  
David Walker ◽  
Bradford H. Hager ◽  
James F. Hays
Keyword(s):  
Source Region ◽  
Source Regions ◽  
Melt Density ◽  
Melt Segregation ◽  
Region Size

scholarly journals Annual variation in event-scale precipitation <i>δ</i><sup>2</sup>H at Barrow, AK, reflects vapor source region

2017 ◽  
Vol 17 (7) ◽  
pp. 4627-4639 ◽  
Author(s):  
Annie L. Putman ◽  
Xiahong Feng ◽  
Leslie J. Sonder ◽  
Eric S. Posmentier
Keyword(s):  
Source Region ◽  
Arctic Sea Ice ◽  
Dew Point ◽  
Precipitation Event ◽  
Boolean Variable ◽  
Deuterium Excess ◽  
Vapor Source ◽  
Source Regions ◽  
Circulation Cell ◽  
Transport Path

Abstract. In this study, precipitation isotopic variations at Barrow, AK, USA, are linked to conditions at the moisture source region, along the transport path, and at the precipitation site. Seventy precipitation events between January 2009 and March 2013 were analyzed for δ2H and deuterium excess. For each precipitation event, vapor source regions were identified with the hybrid single-particle Lagrangian integrated trajectory (HYSPLIT) air parcel tracking program in back-cast mode. The results show that the vapor source region migrated annually, with the most distal (proximal) and southerly (northerly) vapor source regions occurring during the winter (summer). This may be related to equatorial expansion and poleward contraction of the polar circulation cell and the extent of Arctic sea ice cover. Annual cycles of vapor source region latitude and δ2H in precipitation were in phase; depleted (enriched) δ2H values were associated with winter (summer) and distal (proximal) vapor source regions. Precipitation δ2H responded to variation in vapor source region as reflected by significant correlations between δ2H with the following three parameters: (1) total cooling between lifted condensation level (LCL) and precipitating cloud at Barrow, ΔTcool, (2) meteorological conditions at the evaporation site quantified by 2 m dew point, Td, and (3) whether the vapor transport path crossed the Brooks and/or Alaskan ranges, expressed as a Boolean variable, mtn. These three variables explained 54 % of the variance (p<0. 001) in precipitation δ2H with a sensitivity of −3.51 ± 0.55 ‰ °C−1 (p<0. 001) to ΔTcool, 3.23 ± 0.83 ‰ °C−1 (p<0. 001) to Td, and −32.11 ± 11.04 ‰ (p = 0. 0049) depletion when mtn is true. The magnitude of each effect on isotopic composition also varied with vapor source region proximity. For storms with proximal vapor source regions (where ΔTcool <7 °C), ΔTcool explained 3 % of the variance in δ2H, Td alone accounted for 43 %, while mtn explained 2 %. For storms with distal vapor sources (ΔTcool > 7°C), ΔTcool explained 22 %, Td explained only 1 %, and mtn explained 18 %. The deuterium excess annual cycle lagged by 2–3 months during the δ2H cycle, so the direct correlation between the two variables is weak. Vapor source region relative humidity with respect to the sea surface temperature, hss, explained 34 % of variance in deuterium excess, (−0.395 ± 0.067 ‰ %−1, p<0. 001). The patterns in our data suggest that on an annual scale, isotopic ratios of precipitation at Barrow may respond to changes in the southerly extent of the polar circulation cell, a relationship that may be applicable to interpretation of long-term climate change records like ice cores.

Azimuth estimation capabilities of the ARCESS regional seismic array

1993 ◽  
Vol 83 (4) ◽  
pp. 1213-1231
Author(s):  
Dorthe B. Carr
Keyword(s):  
Time Window ◽  
Source Region ◽  
Event Data ◽  
Small Aperture ◽  
Data Set ◽  
Low Frequencies ◽  
Source Regions ◽  
The Mean ◽  
Local Geology ◽  
Regional Arrays

Abstract The effect of local geology and noise conditions on the performance of a small regional array is investigated by comparing the regional Pn backazimuth estimation capabilities of the ARCESS array in northern Norway to the NORESS array. A broadband frequency-wavenumber estimator was used to calculate backazimuths from the Pn arrival for each of 203 regional events recorded at ARCESS while varying element spacing, frequency band, and time window. Most of the errors in backazimuth are less than 20° when appropriate parameter combinations are used, and mean backazimuth errors are close to zero. The best results are obtained using a 13-element configuration that has a 1.4 km aperture and a maximum station spacing of about 600 m. With the 13-element configuration and the data filtered to include frequencies between 3 and 10 Hz, the mean errors for the 203 event data set are less than 0.9°, and S.D. are as small as 16.9°. There are differences seen in the backazimuth estimation capabilities of ARCESS and NORESS with specific parameter combinations. The larger aperture configurations (10- and 17-elements) have smaller means at ARCESS, although the precision is about the same. The estimates using unfiltered data at ARCESS are poor, because of local noise conditions that increase the level of background noise at low frequencies. Overall the precision is better at NORESS, but both regional arrays have the best results using the 13-element configuration and filtering the data in the middle frequency range (3 to 10 Hz). Other factors investigated include SNR and source region. Backazimuth estimation statistics improve if only events with 5 dB of SNR are included in the data set at both ARCESS and NORESS. The mean errors move closer to zero and standard deviations decrease. The differences between the two arrays are not as pronounced. There are some path effects from different source regions around the ARCESS array. However, combinations of small aperture configurations and middle (3 to 10 Hz) frequency bands work well for events over the entire distance range of 30 to 1200 km. ARCESS and NORESS have similar backazimuth estimation capabilities even though there are differences in the local geology and noise conditions. Because a 13-element configuration produces reliable results for both arrays, it would be reasonable to reduce the number of elements in a regional array. This in turn will reduce the costs associated with building and deploying small regional arrays.

Determine the Physical Mechanism and Source Region of Beat Wave Modulation by Changing the Frequency of HF Waves

2021 ◽  
Author(s):  
Zhe Guo ◽  
Hanxian Fang ◽  
Farideh Honary
Keyword(s):  
Physical Mechanism ◽  
Source Region ◽  
Low Frequency ◽  
Signal Amplitude ◽  
New Approach ◽  
Wave Modulation ◽  
F Region ◽  
Source Regions ◽  
High Modulation ◽  
E Region

Abstract This paper introduces a new approach for the determination of the source region of BW (beat wave) modulation. This type of modulation is achieved by transmitting HF continuous waves with a frequency difference of f, where f is the frequency of modulated ELF/VLF (extremely low frequency/very low frequency) waves from two sub-arrays of a high power HF transmitter. Despite the advantages of BW modulation in terms of generating more stable ELF/VLF signal and high modulation efficiency, there exists a controversy on the physical mechanism of BW and its source region. In this paper, the two controversial theories, i.e. BW based on D-E region thermal nonlinearity and BW based on F region ponderomotive nonlinearity are examined for cases where each of these two theories exists exclusively or both of them exist simultaneously. According to the analysis and the simulation results presented in this paper, it is found that the generated VLF signal amplitude exhibits significant variation as a function of HF frequency in different source regions. Therefore, this characteristic can be utilised as a potential new approach to determine the physical mechanism and source location of BW.

Inverse scattering in multilayer inverse problem in the presence of damping

2006 ◽  
Vol 176 (2) ◽  
pp. 455-461
Author(s):  
F.D. Zaman ◽  
Khalid Masood ◽  
Z. Muhiameed
Keyword(s):  
Inverse Problem ◽  
Inverse Scattering
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