@inproceedings{3c480e1e56374818893b9c6d353e5e37,
title = "Locally-adaptive detection algorithm for forward-looking ground-penetrating radar",
abstract = "This paper proposes an effective anomaly detection algorithm for a forward-looking ground-penetrating radar (FLGPR). One challenge for threat detection using FLGPR is its high dynamic range in response to different kinds of targets and clutter objects. The application of a fixed threshold for detection often yields a large number of false alarms. We propose a locally-adaptive detection method that adjusts the detection criteria automatically and dynamically across different spatial regions, which improves the detection of weak scattering targets. The paper also examines a spectrum-based classifier. This classifier rejects false alarms (FAs) by classifying each alarm location based on its spatial frequency-spectrum. Experimental results for the improved detection techniques are demonstrated by field data measurements from a US Army test site.",
keywords = "false alarm rejection, Forward-looking explosive hazards detection, ground-penetrating radar, one-class classifiers, spatial frequency",
author = "Havens, \{Timothy C.\} and Ho, \{K. C.\} and Justin Farrell and Keller, \{James M.\} and Mihail Popescu and Ton, \{Tuan T.\} and Wong, \{David C.\} and Mehrdad Soumekh",
year = "2010",
doi = "10.1117/12.851512",
language = "English",
isbn = "9780819481283",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
booktitle = "Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XV",
note = "Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XV ; Conference date: 05-04-2010 Through 09-04-2010",
}