Satellite Radar Vessel Traffic Map Generation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods for monitoring vessel traffic in marine areas are limited by their reliance on automatic identification systems (AIS), which do not account for vessels without AIS or provide comprehensive spatial and temporal analysis suitable for environmental and societal impact assessments.
Innovation Solution
A method utilizing satellite radar images to generate a spatial and temporal map of estimated vessel traffic, including vessels without AIS, by acquiring and analyzing multiple satellite radar images over a period, validating the data, and creating a map with vessel density values by time period.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If satellite radar images are acquired at high frequency to improve temporal resolution of vessel traffic monitoring, then the ability to detect and track vessel movements is improved, but the cost and data processing complexity increase significantly
Solution Approach 1:
The patent segments the maritime area into multiple zones and processes satellite radar images in a systematic sequence. By dividing the large-scale monitoring area into smaller manageable segments, the system can process high-frequency satellite data more efficiently, reducing the overall computational complexity while maintaining high temporal resolution for vessel traffic monitoring.
Solution Approach 2:
The patent applies preliminary processing steps to satellite radar images before full analysis, including noise filtering, clutter removal, and preliminary vessel detection. This preliminary action reduces the complexity of subsequent processing steps by pre-processing the data to remove known interference patterns and identify potential targets of interest.
2Measurement precision
If satellite radar images with high resolution are used to improve vessel detection accuracy, then the ability to identify individual vessels is improved, but the data processing time and computational resources increase
Solution Approach 1:
The patent applies local quality processing by using high-resolution satellite radar image processing focused on specific areas or zones of interest rather than uniformly processing entire large-scale maritime areas at maximum resolution. This allows the system to maintain high vessel detection accuracy in critical zones while reducing processing time in less critical areas.
Solution Approach 2:
The patent implements partial processing by first identifying potential vessel locations using lower-resolution or preliminary analysis, then applying full high-resolution processing only to those specific locations where vessels are detected. This partial action approach maintains high detection accuracy for vessels while significantly reducing the overall processing time and computational resources required.
3Device complexity
If only AIS-equipped vessels are monitored to simplify data collection, then the system complexity is reduced, but the comprehensive coverage of all vessel traffic is lost
Solution Approach 1:
The patent merges multiple data sources including AIS data with satellite radar image data to create a comprehensive vessel monitoring system. By combining these different data sources, the system achieves complete vessel traffic coverage while managing complexity through integrated processing that cross-validates information from both AIS transmissions and passive radar detection.
Solution Approach 2:
The patent uses satellite radar imagery as an intermediary data source that can detect vessels regardless of AIS equipment status. The radar images serve as a mediator that provides backup and supplementary information to AIS data, ensuring comprehensive vessel traffic coverage while the system maintains manageable complexity through selective use of each data source based on their respective strengths.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach provides a comprehensive statistical picture of maritime traffic over time, detecting all vessels within the satellite's spatial resolution, including those without AIS, and allows for accurate prediction and identification of traffic patterns and disturbances.
Implementation Method 1
satellite-based radar imagery, usually gathered by synthetic aperture radar (SAR)
Implementation Method 2
synthetic aperture radar (SAR), is becoming increasingly widespread for maritime surveillance. In SAR, an active microwave sensor can illuminate a target with a focused, directional beam of energy, producing unique scattering effect depending on the orientation of the sensed objects.
Implementation Method 3
The backscattering response of surface materials to illumination by microwave energy, also referred to a 'backscattering signal', is very different from spectral reflectance of the visible sunlight of the same material.
Data Source
AI summary
The invention relates to a computing device or a method of generating a spatial and temporal map (50) of an estimated vessels traffic in an area (51), said method comprising the following steps: Acquisition (110) of a plurality of satellite radar images of the area (51), said plurality of satellite radar images having been generated over a period of at least twelve months at a median frequency lower than ten images per week; Analysis (120) of the plurality of satellite radar images to generate data on vessels forming an historical vessel traffic; Correction (130) of the generated data based on the plurality of satellite radar images frequency; and Generation (180), from the corrected data, of at least one spatial and temporal distribution map of vessels forming the estimated vessel traffic in the area, said spatial and temporal distribution map comprising vessel density values by time period.