NAFDTD - A Near-field Finite Difference Time Domain Solver

Dogaru, Traian

doi:10.21236/ada568936

Cited by 14 publications

(9 citation statements)

References 10 publications

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“…The uncertainty sets in ( 86) and ( 87) are indicated by the shaded areas. The numerical data used in this example were simulated using the Near-Field Finite-Difference Time-Domain software package, NAFDTD, developed by the U.S. Army Research Laboratory (ARL) [189]. Fig.…”

Section: A Current Application: Ground Penetrating Radarmentioning

confidence: 99%

Minimax Robust Detection: Classic Results and Recent Advances

Fauß

Zoubir

Poor

2021

IEEE Trans. Signal Process.

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This paper provides an overview of results and concepts in minimax robust hypothesis testing for two and multiple hypotheses. It starts with an introduction to the subject, highlighting its connection to other areas of robust statistics and giving a brief recount of the most prominent developments. Subsequently, the minimax principle is introduced and its strengths and limitations are discussed. The first part of the paper focuses on the two-hypothesis case. After briefly reviewing the basics of statistical hypothesis testing, uncertainty sets are introduced as a generic way of modeling distributional uncertainty. The design of minimax detectors is then shown to reduce to the problem of determining a pair of least favorable distributions, and different criteria for their characterization are discussed. Explicit expressions are given for least favorable distributions under three types of uncertainty: ε-contamination, probability density bands, and f -divergence balls. Using examples, it is shown how the properties of these least favorable distributions translate to properties of the corresponding minimax detectors. The second part of the paper deals with the problem of robustly testing multiple hypotheses, starting with a discussion of why this is fundamentally different from the binary problem. Sequential detection is then introduced as a technique that enables the design of strictly minimax optimal tests in the multi-hypothesis case. Finally, the usefulness of robust detectors in practice is showcased using the example of ground penetrating radar. The paper concludes with an outlook on robust detection beyond the minimax principle and a brief summary of the presented material.

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Section: A Current Application: Ground Penetrating Radarmentioning

confidence: 99%

Minimax Robust Detection: Classic Results and Recent Advances

Fauß

Zoubir

Poor

2021

IEEE Trans. Signal Process.

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“…Despite these difficulties, we derive the equation of the peak transmitted power for the case when the near-field radar scenario is simulated with the NAFDTD software (11), and the transmitter and receiver antennas are provided by infinitesimal dipoles. We first consider the narrowband case.…”

Section: Near-field Casementioning

confidence: 99%

Model-Based Radar Power Calculations for Ultra-Wideband (UWB) Synthetic Aperture Radar (SAR)

Dogaru¹

2013

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“…This results in two shortcomings, i.e., scanning a large interrogation area is time consuming, and the short distance between the radar system and the potential targets poses potential danger to the radar operator. Different from the conventional system is a forwardlooking ground penetrating radar (FL-GPR), which has gained significant research interest in the last few decades [6][7][8][9][10][11][12]. An FL-GPR system can be deployed on a moving platform, such as a vehicle, with antennas mounted on the roof top, and it interrogates the scene of interest using oblique incidence.…”

Section: Introductionmentioning

confidence: 99%

A Robust Copula Model for Radar-Based Landmine Detection

Pambudi

Ahmad

Zoubir

2021

ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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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.

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NAFDTD - A Near-field Finite Difference Time Domain Solver

Cited by 14 publications

References 10 publications

Minimax Robust Detection: Classic Results and Recent Advances

Minimax Robust Detection: Classic Results and Recent Advances

Model-Based Radar Power Calculations for Ultra-Wideband (UWB) Synthetic Aperture Radar (SAR)

A Robust Copula Model for Radar-Based Landmine Detection

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