Anomaly detection of subsurface objects using handheld ground-penetrating radar

K. C. Ho; Samuel Harris; Alina Zare; Matthew Cook

doi:10.1117/12.2178584

21 May 2015 Anomaly detection of subsurface objects using handheld ground-penetrating radar

K. C. Ho, Samuel Harris, Alina Zare, Matthew Cook

Proceedings Volume 9454, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XX; 94541B (2015) https://doi.org/10.1117/12.2178584
Event: SPIE Defense + Security, 2015, Baltimore, MD, United States

Abstract

This paper develops an anomaly detection algorithm for subsurface object detection using the handheld ground penetrating radar. The algorithm is based on the Mahalanobis distance measure with adaptive update of the background statistics. It processes the data sequentially for each data sample in a causal manner to generate detection confidences. The algorithm is applied to process the data from two different radars, an impulse and a step-frequency, for performance evaluation.

Citation Download Citation

K. C. Ho, Samuel Harris, Alina Zare, and Matthew Cook "Anomaly detection of subsurface objects using handheld ground-penetrating radar", Proc. SPIE 9454, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XX, 94541B (21 May 2015); https://doi.org/10.1117/12.2178584

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available