2014
DOI: 10.1109/access.2014.2313601
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ASIN-Based UWB Radar for Sludge Monitoring

Abstract: In this paper, we propose an application specific instrument (ASIN)-based ultrawideband (UWB) radar system for sludge monitoring from scattering signatures from the bottom of industrial oil tanks. The method is validated by successful estimation of sludge volume in oil tanks using simulated and real data. First, as a demonstration of the conventional system, image reconstruction algorithms are used for tankbottom sludge profile imaging for symmetrical and asymmetrical sludge profiles, where the setup is modele… Show more

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Cited by 9 publications
(4 citation statements)
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“…Secondly, this is a forward looking and non-coherent radar system which theoretically limits the amount of information it can capture. We hypothesize that these two problems can be solved using the application specific instrumentation framework [19,24]. This will be our future work, whereas in this paper we demonstrate the feasibility of the concept of sensing the environment from communication signals.…”
Section: Introductionmentioning
confidence: 87%
“…Secondly, this is a forward looking and non-coherent radar system which theoretically limits the amount of information it can capture. We hypothesize that these two problems can be solved using the application specific instrumentation framework [19,24]. This will be our future work, whereas in this paper we demonstrate the feasibility of the concept of sensing the environment from communication signals.…”
Section: Introductionmentioning
confidence: 87%
“…• The last challenge of getting a phenomenological knowledge is the toughest of all the listed challenges. In solving this we propose to use a bio-inspired scheme that combines compressive sensing and application specific instrumentation (ASIN) [13], [14]. The driving philosophy of this scheme lies in the fact that in stead of trying to estimate everything in the scene, we try to estimate one or a few anomalies only.…”
Section: Proposed Solutionsmentioning
confidence: 99%
“…Getting a proper phenomenological sense from this amount of data did not seem possible. Hence, we used the application specific instrumentation framework (ASIN) [13,16] which uses statistical machine learning to recognize 'events of interest'. The shaded region in Figure 1 is the major focus of the work presented here, which corresponds to the analysis of the data captured by the GSM-CommSense system.…”
Section: Introductionmentioning
confidence: 99%