DocumentCode :
3861833
Title :
Object detection using high resolution near-field array processing
Author :
A. Sahin;E.L. Miller
Author_Institution :
Center for Electromagn. Res., Northeastern Univ., Boston, MA, USA
Volume :
39
Issue :
1
fYear :
2001
Firstpage :
136
Lastpage :
141
Abstract :
The authors present an algorithm for the detection and localization of an unknown number of objects buried in a halfspace and present in the near field of a linear receiver array. To overcome the nonplanar nature of the wavefield over the array, the full array is divided into a collection of subarrays such that the scattered fields from objects are locally planar at each subarray. Using the multiple signal classification (MUSIC) algorithm, directions of arrival (DOA) of locally planar waves at each subarray are found. By triangulating these DOAs, a set of crossings, condensed around expected object locations, are obtained. To process this spatial crossing pattern, the authors develop a statistical model for the distribution of these crossings and employ hypotheses testing techniques to identify a collection of small windows likely to contain targets. Finally, the results of the hypothesis tests are used to estimate the number and locations of the targets. Using simulated data, they demonstrate the usefulness and performance of this approach for typical background electrical properties and signal to noise ratios.
Keywords :
"Object detection","Array signal processing","Testing","Geometry","Multiple signal classification","Electromagnetic scattering","Buried object detection","Classification algorithms","Signal to noise ratio","Antenna arrays"
Journal_Title :
IEEE Transactions on Geoscience and Remote Sensing
Publisher :
ieee
ISSN :
0196-2892
Type :
jour
DOI :
10.1109/36.898675
Filename :
898675
Link To Document :
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