Sampling theorem of satellite gravimetry from the perspective of the Bender configuration

Author(s):  
Anshul Yadav ◽  
Balaji Devaraju ◽  
Matthias Weigelt ◽  
Nico Sneeuw

<p>Satellites in different orbital configurations acquire gravity signals differently. Thus, a difference in admissible spectral coefficients can be expected when the orbital geometry changes. A simple illustration of this phenomenon is seen in the Bender configuration of two GRACE-like satellite pairs - polar and inclined. In the Bender configuration, the polar pair covers the entire globe. In contrast, the inclined pair does not cover the higher latitudes leaving a local discontinuity around the poles in the acquired signal (better known as the <em>Polar Gap problem</em>). Similarly, due to its north-south orientation, the polar pair can capture the features that are predominantly oriented in the east-west direction. Trying to understand better the relationship between satellite geometry and signal acquisition led us to take our first steps in the direction of a unified sampling theory in satellite gravimetry. To this end, we employed the concepts behind the rotation of spherical harmonic coefficients built upon Inclination functions to express the geopotential functionals. Our work utilizes the Lomb-Scargle Periodogram based approach to ascertain limiting frequencies from the systemic quasi-regular sampling net formed on the satellite torus contrary to interpolation and FFT based techniques used in earlier such research endeavors. Through our work, we aim at improving our understanding of how the transformation of the geopotential occurs from the global to the spectral domain. We hope that this will help design future satellite missions with geometries best suited for their objective based on the precise determination of essential spectral coefficients.</p>

2020 ◽  
Author(s):  
Anshul Yadav ◽  
Balaji Devaraju ◽  
Matthias Weigelt ◽  
Nico Sneeuw

<p class="western" align="justify">The signal acquisition by the two different GRACE-like satellite pairs in a Bender configuration - polar and inclined, is dissimilar to each other. This difference is attributable to differing relative sampling geometry and global coverage. While the polar pair covers the entire globe, the inclined pair does not cover the higher latitudes leaving a local discontinuity around the poles in acquired signal (better known as the Polar Gap problem). Similarly, due to its north-south orientation, the polar pair can capture well the features that are predominantly oriented in the east-west direction. We simulated a Bender configuration using ESA's Earth System Model to see how the two satellite pairs contributed to the spherical harmonic coefficients. The general pattern was that the polar orbit contributed strongly to the zonal coefficients and the tesserals around it (near-zonal coefficients) while the inclined orbit contributed strongly to the other tesseral and the sectorial coefficients, which is well known. We also found out that the weak zonal and near-zonal inclined pair contributions lay inside a wedge in the spectral space, very similar to the polar gap error wedge. We want to discern how the satellites' relative geometry, particularly the polar gap issue in the inclined pair of a bender configuration, affects the solution's spectral resolution. In this study, we model the contribution coefficients of the polar and inclined pairs as a function of orbit geometries, employing the semi-analytical framework based on inclination functions. We hope that this will help <span lang="en-IN">in understanding the spectral resolution of the next generation gravity missions</span>.</p>


Author(s):  
Saeed MIAN QAISAR

This paper proposes a novel approach, based on the adaptive rate processing and analysis, for the isolated speech recognition. The idea is to smartly combine the event-driven signal acquisition and windowing along with adaptive rate processing, analysis and classification for realizing an effective isolated speech recognition. The incoming speech signal is digitized with an event-driven A/D converter (EDADC). The output of EDADC is windowed with an activity selection process. These windows are later on resampled uniformly with an adaptive rate interpolator. The resampled windows are de-noised with an adaptive rate filter and their spectrum are computed with an adaptive resolution short time Fourier transform (ARSTFT). Later on, the magnitude, Delta and Delta-Delta spectral coefficients are extracted. The Dynamic Time Warping (DTW) technique is employed to compare these extracted features with the reference templates. The comparison outcomes are used to make the classification decision. The system functionality is tested for a case study and results are presented. An 8.2 times reduction in acquired number of samples is achieved by the devised approach as compared to the classical one. It aptitudes a significant computational gain and power consumption reduction of the proposed system over the counter classical ones. An average subject dependent isolated speech recognition accuracy of 96.8% is achieved. It shows that the proposed approach is a potential candidate for the automatic speech recognition applications like rehabilitation centers, smart call centers, smart homes, etc.


2013 ◽  
Vol 2013 ◽  
pp. 1-12 ◽  
Author(s):  
Zangen Zhu ◽  
Khan Wahid ◽  
Paul Babyn ◽  
Ran Yang

Undersamplingk-space data is an efficient way to speed up the magnetic resonance imaging (MRI) process. As a newly developed mathematical framework of signal sampling and recovery, compressed sensing (CS) allows signal acquisition using fewer samples than what is specified by Nyquist-Shannon sampling theorem whenever the signal is sparse. As a result, CS has great potential in reducing data acquisition time in MRI. In traditional compressed sensing MRI methods, an image is reconstructed by enforcing its sparse representation with respect to a basis, usually wavelet transform or total variation. In this paper, we propose an improved compressed sensing-based reconstruction method using the complex double-density dual-tree discrete wavelet transform. Our experiments demonstrate that this method can reduce aliasing artifacts and achieve higher peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) index.


2010 ◽  
Vol 2010 ◽  
pp. 1-18
Author(s):  
Liu Zhanwei ◽  
Hu Guoen ◽  
Wu Guochang

We study the sampling theorem for frames in multiwavelet subspaces. Firstly, a sufficient condition under which the regular sampling theorem holds is established. Then, notice that irregular sampling is also useful in practice; we consider the general cases of the irregular sampling and establish a general irregular sampling theorem for multiwavelet subspaces. Finally, using this generalized irregular sampling theorem, we obtain an estimate for the perturbations of regular sampling in shift-invariant spaces.


1983 ◽  
Vol 130 (4) ◽  
pp. 101 ◽  
Author(s):  
M. Stanković ◽  
ž. Tošić ◽  
S. Nikolić

2005 ◽  
Vol 63 (5) ◽  
pp. 389-403 ◽  
Author(s):  
D. Djebouri ◽  
A. Djebbari ◽  
M. Djebbouri

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