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• W2214874670 abstract "We have applied an automatic interpretation method of potential data called AN-EUL in unexploded ordnance (UXO) prospective which is indeed a combination of the analytic signal and the Euler deconvolution approaches. The method can be applied for both magnetic and gravity data as well for gradient surveys based upon the concept of the structural index (SI) of a potential anomaly which is related to the geometry of the anomaly sources. With AN-EUL method, both the depth and the approximate geometry (or SI) of the causative sources can be deduced. A realistic model for UXO to be simulated by a simple shape body is a prolate spheroid. The method is applied for both synthetic potential data assuming a collection of causative UXO sources replicating various sizes placed at different depths. In both cases, the estimated depth and the SI of the synthetic UXOs approximately correspond to the synthetic model parameters. The location detection of the causative sources is based upon the Blakely automatic picking algorithm. For both data sets, since the anomaly responses of the small UXOs are affected by noise, the estimated SI is a bit disturbed but the locations correspond to the real ones. The Blakely algorithm also identifies weak anomalies that are due to noise in data; thus, a post-processing of the estimated SI of the automatically detected sources may be needed to prevent false alarm sources in UXO exploration. Two field data sets have been provided to demonstrate the capability of the applied methods in UXO detection." @default.
• W2214874670 created "2016-06-24" @default.
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• W2214874670 date "2014-07-01" @default.
• W2214874670 modified "2023-09-23" @default.
• W2214874670 title "AN-EUL method for automatic interpretation of potential field data in unexploded ordnances (UXO) detection" @default.
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• W2214874670 doi "https://doi.org/10.22044/jme.2014.323" @default.
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