Sensor fusion approaches for EMI and GPR-based subsurface threat identification

Peter Torrione; Kenneth Morton Jr.; Lance E. Besaw

doi:10.1117/12.884130

23 May 2011 Sensor fusion approaches for EMI and GPR-based subsurface threat identification

Peter Torrione, Kenneth Morton Jr., Lance E. Besaw

Proceedings Volume 8017, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XVI; 801720 (2011) https://doi.org/10.1117/12.884130
Event: SPIE Defense, Security, and Sensing, 2011, Orlando, Florida, United States

Abstract

Despite advances in both electromagnetic induction (EMI) and ground penetrating radar (GPR) sensing and related signal processing, neither sensor alone provides a perfect tool for detecting the myriad of possible buried objects that threaten the lives of Soldiers and civilians. However, while neither GPR nor EMI sensing alone can provide optimal detection across all target types, the two approaches are highly complementary. As a result, many landmine systems seek to make use of both sensing modalities simultaneously and fuse the results from both sensors to improve detection performance for targets with widely varying metal content and GPR responses. Despite this, little work has focused on large-scale comparisons of different approaches to sensor fusion and machine learning for combining data from these highly orthogonal phenomenologies. In this work we explore a wide array of pattern recognition techniques for algorithm development and sensor fusion. Results with the ARA Nemesis landmine detection system suggest that nonlinear and non-parametric classification algorithms provide significant performance benefits for single-sensor algorithm development, and that fusion of multiple algorithms can be performed satisfactorily using basic parametric approaches, such as logistic discriminant classification, for the targets under consideration in our data sets.

Citation Download Citation

Peter Torrione, Kenneth Morton Jr., and Lance E. Besaw "Sensor fusion approaches for EMI and GPR-based subsurface threat identification", Proc. SPIE 8017, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XVI, 801720 (23 May 2011); https://doi.org/10.1117/12.884130

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