Dual-frequency oil spill detection algorithm

Hammoud, Bilal; Mazeh, F.; Jomaa, Kassem; Ayad, Hussam; Ndagijimana, Fabien; Faour, Ghaleb; Jomaah, J.

doi:10.1109/cem.2017.7991870

Cited by 4 publications

(5 citation statements)

References 2 publications

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“…However, the periodicity of such signals would again disrupt detection for higher thickness levels (for example at d = 7.8 mm at 11 GHz). Here comes the idea of using algorithms where a combination of frequencies for the oil detection is implemented as developed [11,12] . we notice that although at different thickness values there exists some noticeable difference in reflectivity values at the same frequency for different dielectric constants.…”

Section: B Simulation Results Analysismentioning

confidence: 99%

“…Furthermore, although at high frequencies (11 and 12 GHz) the experimental values present the highest error (1 dB) from the theoretical value, this will not move the data to the region where it could be misinterpreted as oil-free region. is possible to perform oil spill detection that can be implemented using different advanced algorithms as mentioned in [11] and 12] . In addition, this technique may be used to remotely estimate the oil dielectric constant for material characterization, but this is beyond the scope of this journal.…”

Section: Methodsmentioning

confidence: 99%

“…dual and multi-frequency advanced algorithms that target oil spill detection for unknown oil thicknesses based on the statistical distribution of the reflectivity values [11,12] . The effectiveness of the approach was tested numerically using Monte-Carlo simulations, but to be able to move forward to prototypes and real applications, the results needed to be validated experimentally.…”

Section: Introductionmentioning

confidence: 99%

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Reflection-coefficient experimental extraction from S21- parameter for radar oil-spill detection application

Hammoud

Ndagijimana

Faour

et al. 2018

som

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Oil spill in sea water is one of the main accidents that affect significantly the maritime environment over a long period of time. Knowing the severe influence of oil spills on the ecosystem, it is crucial to have oil spill detecting and monitoring systems for quick intervention and danger containment. In our project, we propose the usage of drones as an oil spill detection system. The drones will be implementing different previously developed multi-frequency approaches for the detection. The effectiveness of such techniques is based on the accuracy of the data collected and their match to the theory. This journal presents a method for the remote extraction of reflection coefficients from multilayer structure modeling an oil spill in sea water. The experimental results for the reflectivity extraction validate the theoretical calculations and allow the implementation of different algorithms based on the statistical information taken directly from the site.

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Section: B Simulation Results Analysismentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Reflection-coefficient experimental extraction from S21- parameter for radar oil-spill detection application

Hammoud

Ndagijimana

Faour

et al. 2018

som

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“…• Single observation at multiple frequencies [70]: a wide-band radar is used to scan a target scene once, and K measurements of reflectivity are sampled at K different frequencies.…”

Section: Reflectivity R (In Db) Versus Oil Thickness (In Mm) At Diffe...mentioning

confidence: 99%

Recent Advances in Oil-Spill Monitoring Using Drone-Based Radar Remote Sensing

Hammoud¹,

Wehn²

2023

Environmental Sciences

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Oil spills are regrettably common and have socioeconomic implications on communities and disastrous consequences on the marine ecosystem and maritime life. The European Space Agency (ESA) has stated that worldwide spillage exceeds 4.5 million tons of oil annually, where 45% of the amount is due to operative discharges from ships. To alleviate the severity of oil spills and promptly react to such incidents, it is crucial to have oil-spill monitoring systems, which enable an effective contingency plan to dictate the best actions for dealing with oil spills. A quick and efficient intervention requires the (1) detection of oil slicks, (2) thickness estimation, and (3) oil classification. The European Maritime Safety Agency (EMSA) highlighted in 2016 the need to use drones as complementary systems supporting satellite maritime surveillance. While multiple sensors could be used, active radars appear to be prominent for oil spill monitoring. In this chapter, we present recent advances in drone-based radar remote sensing as an effective oil spill monitoring system. It shows from the system-level perspective the capability of radar systems on drones, using high spectral resolution and parallel scanning, to perform the above-required functionalities (1, 2, and 3) and provide valuable information to contain the damage.

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“…We developed in [25,26] dual-and multi-frequency algorithms using only single observations for oil spill detection. The model adopted was a planar multi-layer structure.…”

Section: Introductionmentioning

confidence: 99%

Bayesian Statistics of Wide-Band Radar Reflections for Oil Spill Detection on Rough Ocean Surface

Hammoud

Ndagijimana

Faour

et al. 2019

JMSE

Self Cite

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In this paper, we present a probabilistic approach which uses nadir-looking wide-band radar to detect oil spills on rough ocean surface. The proposed approach combines a single-layer scattering model with Bayesian statistics to evaluate the probability of detection of oil slicks, within a plausible range of thicknesses, on seawater. The difference between several derived detection algorithms is defined in terms of the number of frequencies used (within C-to-X-band ranges), as well as of the number of radar observations. Performance analysis of all three types of detectors (single-, dual- and tri-frequency) is done under different surface-roughness scenarios. Results show that the probability of detecting an oil slick with a given thickness is sensitive to the radar frequency. Multi-frequency detectors prove their ability to overcome the performance of the single- and dual-frequency detectors. Higher probability of detection is obtained when using multiple observations. The roughness of the ocean surface leads to a loss in the reflectivity values, and therefore decreases the performance of the detectors. A possible way to make use of the drone systems in the contingency planning is also presented.

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Dual-frequency oil spill detection algorithm

Cited by 4 publications

References 2 publications

Reflection-coefficient experimental extraction from S21- parameter for radar oil-spill detection application

Reflection-coefficient experimental extraction from S21- parameter for radar oil-spill detection application

Recent Advances in Oil-Spill Monitoring Using Drone-Based Radar Remote Sensing

Bayesian Statistics of Wide-Band Radar Reflections for Oil Spill Detection on Rough Ocean Surface

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