Vessel Field Awareness for Intuitive Radar Object Detection
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Solution Overview
Problem
Radar data interpretation is challenging for both novice and experienced operators, limiting the extraction of valuable information for navigation and collision avoidance, particularly in low visibility conditions.
Innovation Solution
A field of awareness (FOA) system that utilizes a machine-learned model to interpret radar data, classify objects, and provide intuitive visual and audible alerts based on object type, position, and movement, leveraging radar data combined with truth data for training and updating the model.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If radar data is presented in traditional plotted format, then the system provides basic detection capability, but the information is difficult to interpret and extract value from
Solution Approach 1:
The patent introduces an intermediary processing layer between the radar system and the operator. This layer includes automated algorithms that interpret radar data, identify objects, classify them by type, and present the information in an intuitive format. The intermediary transforms raw radar plots into meaningful situational awareness information, making it accessible to operators of all experience levels.
Solution Approach 2:
The patent replaces the manual mechanical process of interpreting radar plots with automated electronic processing systems. Instead of operators manually analyzing radar returns, the system uses computer-based algorithms to automatically detect, track, and classify objects, substituting human cognitive effort with automated computational analysis.
2Reliability
If traditional radar plotting is used, then the system maintains simple structure, but experienced operators cannot fully extract value from the captured information
Solution Approach 1:
The patent segments the radar data processing function into distinct modular components: signal processing module, object detection module, classification module, tracking module, and presentation module. Each module performs a specific function, allowing the system to be complex internally while maintaining manageable structure through functional separation.
Solution Approach 2:
The patent creates a multi-functional processing system that performs multiple operations on radar data simultaneously: detecting objects, classifying them by type, tracking their movement, determining collision risk, and presenting information in various formats. This universal processing core handles diverse navigation scenarios without requiring separate specialized systems.
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
Enhances situational awareness by providing easy-to-interpret object detection and tracking, improving navigation and collision avoidance capabilities through improved radar data processing and real-time object classification and tracking.
Implementation Method 1
Radar systems have become commonplace on many marine vessels of a certain size, and such systems have proven to be useful for detecting other objects on the water that are in the surrounding area of the vessel.
Implementation Method 2
The radar system may be disposed on the vessel and may be configured to generate radar data based on transmitted radar signals and received radar reflection signals.
Data Source
AI summary
A field of awareness (FOA) system provides an operator of a vessel with intuitive object detection and positioning information. The system may comprise an FOA cloud server and an FOA unit. The FOA cloud server may be configured to perform a machine learning training operation to modify an FOA model based on a location-based relationship between training radar data and truth data. The FOA unit may be disposed on the vessel and may comprise processing circuitry configured to apply radar data to the FOA model to perform a comparison to determine a matched model signature, an associated matched object type, and an icon representation for the object of interest. The processing circuitry also be configured to control the display device to render the icon representation of the object at a position relative to a representation of the vessel based on the relative object position.