A Robust Copula Model for Radar-Based Landmine Detection
Afief D. Pambudi, Fauzia Ahmad, Abdelhak M. Zoubir
Abstract
We present a robust copula model for landmine detection based on a likelihood ratio test. The test is applied to radar-based imagery from multiple viewpoints of the interrogation area. Different copula density functions are investigated in terms of their effectiveness in incorporating the statistical dependence between multi-view images. The test is designed to maximize the worst-case performance over all feasible mine and clutter distributions. Using numerical radar data of shallow buried targets under varying surface roughness, we demonstrate that the robust copula-based detector outperforms existing approaches and provides a high detection performance for a wide range of false-alarm rates.
BibTeX
@inproceedings{icassp2021_arobustcopulamod,
title = {A Robust Copula Model for Radar-Based Landmine Detection},
author = {Afief D. Pambudi and Fauzia Ahmad and Abdelhak M. Zoubir},
booktitle = {ICASSP 2021},
year = {2021}
}