Back projection algorithm based on linear estimation of refraction point position for subsurface imaging in layered scenes

Zihan Xu; Fulin Su; Guodong Xu

doi:10.1117/12.2648155

23 January 2023 Back projection algorithm based on linear estimation of refraction point position for subsurface imaging in layered scenes

Zihan Xu, Fulin Su, Guodong Xu

Author Affiliations +

Proceedings Volume 12557, AOPC 2022: Optical Sensing, Imaging, and Display Technology; 125570S (2023) https://doi.org/10.1117/12.2648155
Event: Applied Optics and Photonics China 2022 (AOPC2022), 2022, Beijing, China

Abstract

Back projection (BP) algorithm is widely used for ground penetrating radar (GPR) imaging of layered scenes. Considering the inevitable refraction phenomenon in the layered scenes, the BP algorithm necessitates repeatedly solving quartic equations all over the imaging scene to determine the positions of refraction points. However, the existing algorithms calculate the quartic equation of the refraction point through iterative approximations, especially when the relative permittivity of the scene gradually increases. These algorithms rely on the manual setting of the iteration threshold and are time consuming. Therefore, this paper proposes a BP algorithm based on linear estimation of refraction point position (LERP) for the layered scene with decreasing permittivity. We propose a two-step LERP algorithm that rewrites the quartic equation of the refraction point and directly estimates the refraction point position. The LERP algorithm consists of the coarse estimation inspired by the scene features and the precise estimation guaranteed by the quartic equation. The LERP algorithm reduces the quartic equation to a linear algebraic form. Following this, the LERP-based BP algorithm promotes efficient imaging in the case of decreasing permittivity. Comprehensive experiments verify that the proposed LERP algorithm meets the resolution requirements of GPR exploration. Compared with the existing algorithms, the proposed algorithm avoids manually setting iteration thresholds, and improves the efficiency of estimating refraction point positions and thus the BP algorithm.

Citation Download Citation

Zihan Xu, Fulin Su, and Guodong Xu "Back projection algorithm based on linear estimation of refraction point position for subsurface imaging in layered scenes", Proc. SPIE 12557, AOPC 2022: Optical Sensing, Imaging, and Display Technology, 125570S (23 January 2023); https://doi.org/10.1117/12.2648155

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

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
6 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Refraction

Ground penetrating radar

Antennas

Radar imaging

Iterative methods

Remote sensing

Roads

Keywords/Phrases

Search In:

Publication Years