Model-based approach to the detection, classification, and characterization of subsurface targets from forward-looking ground penetrating radar data

Jie Cheng; Eric L. Miller

doi:10.1117/12.479102

13 August 2002 Model-based approach to the detection, classification, and characterization of subsurface targets from forward-looking ground penetrating radar data

Jie Cheng, Eric L. Miller

Author Affiliations +

Proceedings Volume 4742, Detection and Remediation Technologies for Mines and Minelike Targets VII; (2002) https://doi.org/10.1117/12.479102
Event: AeroSense 2002, 2002, Orlando, FL, United States

Abstract

Here we consider the use of model-based methods for the detection of buried objects from a sequence of synthetic aperture images obtained by a radar sensor moving linearly down a track. The scattering physics of the underlying sensing modality cause the relevant target signatures to change in a complex yet predictable manner as new images are obtained. To arrive at a tractable processing scheme which exploits these motion-induced changes, we develop a flexible parametric model capable of capturing the full variation of these signatures. A detection method based on a principal components analysis of estimated model vectors is then derived. Results are demonstrated using field data from a forward-looking sensor designed for landmine remediation.

Citation Download Citation

Jie Cheng and Eric L. Miller "Model-based approach to the detection, classification, and characterization of subsurface targets from forward-looking ground penetrating radar data", Proc. SPIE 4742, Detection and Remediation Technologies for Mines and Minelike Targets VII, (13 August 2002); https://doi.org/10.1117/12.479102

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