Object detection using high resolution near-field array processing

Şahin, Adnan; Miller, Eric L.

doi:10.1109/36.898675

Cited by 17 publications

(9 citation statements)

References 8 publications

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“…Approaches devoted to the localization and shaping of targets have also been reported. As an example, a technique belonging to this class has been presented in [57]- [59]. The positions of buried targets are detected by estimating the scattered field directions of arrival through subarrays processing followed by a statistical filtering and a triangularization technique.…”

Section: Qualitative Approaches and Sampling Methodsmentioning

confidence: 99%

Advanced Inversion Techniques for Ground Penetrating Radar

Fedeli¹,

Pastorino²,

Randazzo³

2017

JTIT

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Abstract-Ground Penetrating Radar (GPR) systems are nowadays standard inspection tools in several application areas, such as subsurface prospecting, civil engineering and cultural heritage monitoring. Usually, the raw output of GPR is provided as a B-scan, which has to be further processed in order to extract the needed information about the inspected scene. In this framework, inverse-scattering-based approaches are gaining an ever-increasing interest, thanks to their capabilities of directly providing images of the physical and dielectric properties of the investigated areas. In this paper, some advances in the development of such inversion techniques in the GPR field are revised and discussed.

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Section: Qualitative Approaches and Sampling Methodsmentioning

confidence: 99%

Advanced Inversion Techniques for Ground Penetrating Radar

Fedeli¹,

Pastorino²,

Randazzo³

2017

JTIT

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“…). The synergy between signal processing and electromagnetic areas was introduced several years ago in many works, as in Bruckstein and Kailath () and Şahin and Miller ().…”

Section: Introductionmentioning

confidence: 99%

“…In this paper, we present a statistical approach to process the data calculated by a forward scattering solver, in order to find an estimation for the position of an object using a sub‐array processing technique (Bouvet and Bienvenu ; Krim and Viberg ) similar to the one presented in Şahin and Miller (). Moreover, sub‐array processing techniques have been considered in order to achieve localization also for objects in the proximity of the array (Schmidt ).…”

Section: Introductionmentioning

confidence: 99%

Use of a sub‐array statistical approach for the detection of a buried object

Meschino

Pajewski

Schettini

2010

Near Surface Geophysics

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A hybrid electromagnetic-statistic approach for the detection and localization of a perfectly-conducting circular cylinder, buried in a lossless half-space, is presented. We use the results of a cylindrical wave approach forward solver as input data for our detection procedure. We use a sub-array processing structure and apply several algorithms for the direction of arrival estimation. By triangulating the found directions of arrival, a set of crossings, condensed around the object locations, is obtained. To process the crossing pattern, we developed a statistical model for the crossings distribution and employed hypothesis testing procedures to identify a collection of small windows containing the target. By defining a suitable threshold from a desired false alarm rate and dividing the region in small windows it is possible to ascribe each window to the ground or to the object. Numerical results are presented for a cylinder in a vacuum and in a dielectric half-space, both in a central and in a peripheral position with respect to the array centre. Different values of the cylinder radius and of the distance from the array are considered

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“…Starer and Nehorai [8] reduced the computational complexity of the bearing-range estimation by the use of path following, but this method is limited to uniform linear arrays (ULAs). Sahin and Miller [9] partitioned the receiver array into subarrays, where the scattered fields are assumed to be locally planar, and a classical MUSIC algorithm is then used to estimate the DOAs, the range being estimated by a triangulation method. Weiss and Friedlander [10] reduced the computational cost of bearing-range estimation by replacing the two-dimensional (2-D) minimization of the 2-D MUSIC cost function by a 2-D polynomial rooting (see [11] for the extension of the method to the three-dimensional case).…”

Section: Introductionmentioning

confidence: 99%

Simple robust bearing-range source's localization with curved wavefronts

Boyer

Férreol

Larzabal

2005

IEEE Signal Process. Lett.

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In array processing, the far-field assumption of planar wavefronts is widely used by direction of arrival (DOA) estimators but not always satisfied. In this letter, we introduce a new method for bearing-range estimation, which extends classical subspace-based bearing estimators to a curved wavefront context. The bearing estimation is provided by a one-dimensional procedure, and ranges are simply analytically deduced from the bearing estimates. The proposed approach is illustrated by the introduction of the music curved wavefront (MCW) algorithm.Index Terms-Curved wavefronts, direct of arrival (DOA) estimation, range estimation, subspace-based methods.

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Object detection using high resolution near-field array processing

Cited by 17 publications

References 8 publications

Advanced Inversion Techniques for Ground Penetrating Radar

Advanced Inversion Techniques for Ground Penetrating Radar

Use of a sub‐array statistical approach for the detection of a buried object

Simple robust bearing-range source's localization with curved wavefronts

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