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Your search keyword '"Zoubir, Abdelhak M."' showing total 412 results
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412 results on '"Zoubir, Abdelhak M."'

21. Robust Copula-Based Detection of Shallow-Buried Landmines With Forward-Looking Radar.

Author

Pambudi, Afief Dias, Ahmad, Fauzia, and Zoubir, Abdelhak M.

Subjects
GROUND penetrating radar, RADAR, LIKELIHOOD ratio tests, LAND mines, COPULA functions, LOCAL & light railroads
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. [ABSTRACT FROM AUTHOR]

Published
2022
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45. Doppler Radar for the Extraction of Biomechanical Parameters in Gait Analysis.

Author

Seifert, Ann-Kathrin, Grimmer, Martin, and Zoubir, Abdelhak M.

Subjects
DOPPLER radar, WALKING speed, MOTION capture (Human mechanics), LEG, REACTION forces, TIME measurements, HUMAN kinematics
Abstract

The applicability of Doppler radar for gait analysis is investigated by quantitatively comparing the measured biomechanical parameters to those obtained using motion capturing and ground reaction forces. Nineteen individuals walked on a treadmill at two different speeds, where a radar system was positioned in front of or behind the subject. The right knee angle was confined by an adjustable orthosis in five different degrees. Eleven gait parameters are extracted from radar micro-Doppler signatures. Here, new methods for obtaining the velocities of individual lower limb joints are proposed. Further, a new method to extract individual leg flight times from radar data is introduced. Based on radar data, five spatiotemporal parameters related to rhythm and pace could reliably be extracted. Further, for most of the considered conditions, three kinematic parameters could accurately be measured. The radar-based stance and flight time measurements rely on the correct detection of the time instant of maximal knee velocity during the gait cycle. This time instant is reliably detected when the radar has a back view, but is underestimated when the radar is positioned in front of the subject. The results validate the applicability of Doppler radar to accurately measure a variety of medically relevant gait parameters. Radar has the potential to unobtrusively diagnose changes in gait, e.g., to design training in prevention and rehabilitation. As contact-less and privacy-preserving sensor, radar presents a viable technology to supplement existing gait analysis tools for long-term in-home examinations. [ABSTRACT FROM AUTHOR]

Published
2021
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46. Minimax Robust Landmine Detection Using Forward-Looking Ground-Penetrating Radar.

Author

Pambudi, Afief D., FauB, Michael, Ahmad, Fauzia, and Zoubir, Abdelhak M.

Subjects
GROUND penetrating radar, CLUTTER (Noise), LIKELIHOOD ratio tests, LOCAL & light railroads, ELECTROMAGNETIC fields, FALSE alarms
Abstract

We propose a robust likelihood-ratio test (LRT) to detect landmines and unexploded ordnance using forward-looking ground-penetrating radar. Instead of modeling the distributions of the target and clutter returns with parametric families, we construct a band of feasible probability densities under each hypothesis. The LRT is then devised based on the least favorable densities within the bands. This detector is designed to maximize the worst case performance over all feasible density pairs and, hence, does not require strong assumptions about the clutter and noise distributions. The proposed technique is evaluated using electromagnetic field simulation data of shallow-buried targets. We show that, compared to detectors based on parametric models, robust detectors can lead to significantly reduced false alarm rates, particularly in cases where there is a mismatch between the assumed model and the true distributions. [ABSTRACT FROM AUTHOR]

Published
2020
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47. MMSE Bounds for Additive Noise Channels Under Kullback–Leibler Divergence Constraints on the Input Distribution.

Author

Dytso, Alex, Faus, Michael, Zoubir, Abdelhak M., and Poor, H. Vincent

Subjects
INFORMATION measurement, ESTIMATION theory, INFORMATION theory, MINI-Mental State Examination, COVARIANCE matrices, NOISE, GAUSSIAN distribution
Abstract

Upper and lower bounds on the minimum mean square error for additive noise channels are derived when the input distribution is constrained to be close to a Gaussian reference distribution in terms of the Kullback–Leibler divergence. The upper bound is tight and is attained by a Gaussian distribution whose mean is identical to that of the reference distribution and whose covariance matrix is defined implicitly via a system of non-linear equations. The estimator that attains the upper bound is identified as a minimax optimal estimator that is robust against deviations from the assumed prior. The lower bound provides an alternative to well-known inequalities in estimation and information theory—such as the Cramér–Rao lower bound, Stam's inequality, or the entropy power inequality—that is potentially tighter and defined for a larger class of input distributions. Several examples of applications in signal processing and information theory illustrate the usefulness of the proposed bounds in practice. [ABSTRACT FROM AUTHOR]

Published
2019
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