Study of synthetic aperture radar and automatic identification system for ship target detection

Chaturvedi, Sudhir Kumar

doi:10.1016/j.joes.2019.04.002

Cited by 52 publications

(20 citation statements)

References 20 publications

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“…Given the set (A v , B v ), the solution of the vth iteration of the APG procedure is to find the minimal solution for Equation (12) which can be decomposed as finding the minimization values for the P v and Q v (see the Equations (13) and 14, respectively). Following the rules in Reference [46], we obtained the solutions for each row of P and each column of Q in Equations (13) and 14with a closed form solution through Equations (15) and 16, respectively.…”

Section: Solving the Ship Tracking Modelmentioning

confidence: 99%

“…Indeed, a ship equipped with AIS facilities broadcasts the ship's position to neighboring ships and stations every ten seconds; thus, the ship's position in coastal areas is available at high resolution from the perspective of time scale (i.e., a ship's positions in inland waters can be accessed at higher accuracy compared to those obtained by LRIT). The radar-relevant techniques can be integrated to improve ship position accuracy (e.g., a ship's crew may intentionally deactivate their AIS facility when they are involved in illegal activities) [11][12][13][14]. With the help of human involvement, the abovementioned techniques can meet ship tracking demands in a traditional navigation period.…”

Section: Introductionmentioning

confidence: 99%

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Robust Visual Ship Tracking with an Ensemble Framework via Multi-View Learning and Wavelet Filter

Chen

et al. 2020

Sensors

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Maritime surveillance videos provide crucial on-spot kinematic traffic information (traffic volume, ship speeds, headings, etc.) for varied traffic participants (maritime regulation departments, ship crew, ship owners, etc.) which greatly benefits automated maritime situational awareness and maritime safety improvement. Conventional models heavily rely on visual ship features for the purpose of tracking ships from maritime image sequences which may contain arbitrary tracking oscillations. To address this issue, we propose an ensemble ship tracking framework with a multi-view learning algorithm and wavelet filter model. First, the proposed model samples ship candidates with a particle filter following the sequential importance sampling rule. Second, we propose a multi-view learning algorithm to obtain raw ship tracking results in two steps: extracting a group of distinct ship contour relevant features (i.e., Laplacian of Gaussian, local binary pattern, Gabor filter, histogram of oriented gradient, and canny descriptors) and learning high-level intrinsic ship features by jointly exploiting underlying relationships shared by each type of ship contour features. Third, with the help of the wavelet filter, we performed a data quality control procedure to identify abnormal oscillations in the ship positions which were further corrected to generate the final ship tracking results. We demonstrate the proposed ship tracker’s performance on typical maritime traffic scenarios through four maritime surveillance videos.

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Section: Solving the Ship Tracking Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Robust Visual Ship Tracking with an Ensemble Framework via Multi-View Learning and Wavelet Filter

Chen

et al. 2020

Sensors

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“…With this in mind, we have taken the concept of the Skill Score [4] from (2), used ostensibly in relation to drifter measurements, and adapted it to work with quantities that are readily determined from satellite imagery. Specifically, we propose the introduction of two new skill scores based on the centroid and area of the observed and simulated oil spill geometries, which are thus described.…”

Section: Details Of Newly Proposed Metricsmentioning

confidence: 99%

“…Satellites equipped with synthetic aperture radar (SAR) are able to detect oil spills floating on the sea surface [1], [2]. SAR instruments are available on board a number of satellite constellations, e.g., COSMO-SkyMed (CSK), ERS-2, EN-VISAT, RADARSAT, and, more recently, Sentinel-1.…”

Section: Introductionmentioning

confidence: 99%

Performance Measures for Validation of Oil Spill Dispersion Models Based on Satellite and Coastal Data

Dearden¹,

Culmer

Brooke

2022

IEEE J. Oceanic Eng.

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This article presents a set of performance metrics, whose purpose is to provide a quantitative measure of the ability of oil spill dispersion models to simulate real-world oil spills. The metrics are described in detail and are applied to the output from an existing oil spill model for two specific case studies. The metrics in question make use of both satellite imagery and coastal impact reports as the basis of the validation. Specifically, we recommend the 2-D measure of effectiveness as a means of quantifying model performance based on the extent of overlap between the observations and the model output. Additionally, we show that it is advantageous to supplement the 2-D measure of effectiveness with a newly proposed set of skill scores, based on the geometric area and centroid of a given oil spill. We also demonstrate how the metrics can be used to assess the sensitivity of a model to its input parameters and the impact this has on the accuracy of the resultant forecast. Finally, we offer a real-world interpretation for each metric introduced and suggest ways that they can be used to assist in cleanup operations of actual oil spills.

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“…Radar target enhancers in their many forms are currently used on life rafts [21][22][23], however, their efficiency is limited due to their low location on the raft and sea waves interference. Therefore, the proposed solution was to provide the shell of the life raft canopy reflecting radar signals [10,11].…”

Section: Increasing the Signature In The Radar Range-laboratory Testsmentioning

confidence: 99%

The Impact of the Improved Search Object Detection on the SAR Action Success Probability in Maritime Transport

Burciu

Abramowicz-Gerigk

Przybył

et al. 2020

Sensors

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This paper presents the investigations on the improvement of search object detection during search and rescue (SAR) action at sea using thermal imaging and radar sensors. The introduction of new materials in the construction of lifesaving appliances increasing their detectability has been studied for the selected example of a pneumatic life raft. The research was based on laboratory tests and open sea trials. The presented experimental investigations on the new materials that can be used for pneumatic life raft construction showed the enhancement of its thermal and radar signatures, which directly affect life raft detectability and influence reliability of SAR action and probability of success (POS). The improved detectability of a life raft related to the time to survive of a person in the water (PIW) allowed to present the modified search pattern for both PIW and life raft, significantly increasing POS.

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Study of synthetic aperture radar and automatic identification system for ship target detection

Cited by 52 publications

References 20 publications

Robust Visual Ship Tracking with an Ensemble Framework via Multi-View Learning and Wavelet Filter

Robust Visual Ship Tracking with an Ensemble Framework via Multi-View Learning and Wavelet Filter

Performance Measures for Validation of Oil Spill Dispersion Models Based on Satellite and Coastal Data

The Impact of the Improved Search Object Detection on the SAR Action Success Probability in Maritime Transport

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