Pambudi, Afief Dias ; Ahmad, Fauzia ; Zoubir, Abdelhak M. (2022)
Robust Copula-Based Detection of Shallow-Buried Landmines With Forward-Looking Radar.
In: IEEE Transactions on Aerospace and Electronic Systems, 58 (2)
doi: 10.1109/TAES.2021.3111851
Article, Bibliographie
Abstract
We propose a technique for landmine detection using forward-looking ground-penetrating radar. The detector is applied to radar images obtained from multiple viewpoints of the region of interest and is based on a robust version of the likelihood ratio test (LRT). We incorporate the statistical dependence between multiview images into the test via copula-based model. The test is designed to maximize the worst-case performance over all feasible pairs of target and clutter distributions, thereby eliminating the need for strong assumptions about the image statistics. We evaluate the detection performance of the proposed technique for different copula functions representing the dependence structure. Using electromagnetic modeled data of shallow-buried targets under varying ground surface roughness profiles, we demonstrate the superiority of the robust copula-based detector over existing parametric and robust LRT approaches designed under the assumption of statistical independence of multiview images.
| Item Type: | Article |
|---|---|
| Erschienen: | 2022 |
| Creators: | Pambudi, Afief Dias ; Ahmad, Fauzia ; Zoubir, Abdelhak M. |
| Type of entry: | Bibliographie |
| Title: | Robust Copula-Based Detection of Shallow-Buried Landmines With Forward-Looking Radar |
| Language: | English |
| Date: | April 2022 |
| Publisher: | IEEE |
| Journal or Publication Title: | IEEE Transactions on Aerospace and Electronic Systems |
| Volume of the journal: | 58 |
| Issue Number: | 2 |
| DOI: | 10.1109/TAES.2021.3111851 |
| URL / URN: | https://ieeexplore.ieee.org/xpl/aboutJournal.jsp?punumber=7 |
| Abstract: | We propose a technique for landmine detection using forward-looking ground-penetrating radar. The detector is applied to radar images obtained from multiple viewpoints of the region of interest and is based on a robust version of the likelihood ratio test (LRT). We incorporate the statistical dependence between multiview images into the test via copula-based model. The test is designed to maximize the worst-case performance over all feasible pairs of target and clutter distributions, thereby eliminating the need for strong assumptions about the image statistics. We evaluate the detection performance of the proposed technique for different copula functions representing the dependence structure. Using electromagnetic modeled data of shallow-buried targets under varying ground surface roughness profiles, we demonstrate the superiority of the robust copula-based detector over existing parametric and robust LRT approaches designed under the assumption of statistical independence of multiview images. |
| Divisions: | 18 Department of Electrical Engineering and Information Technology 18 Department of Electrical Engineering and Information Technology > Institute for Telecommunications 18 Department of Electrical Engineering and Information Technology > Institute for Telecommunications > Signal Processing Exzellenzinitiative Exzellenzinitiative > Graduate Schools Exzellenzinitiative > Graduate Schools > Graduate School of Computational Engineering (CE) |
| Date Deposited: | 15 Sep 2021 14:31 |
| Last Modified: | 22 Jul 2024 12:55 |
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