LIDAR Plausibility Testing for Marine Person-Overboard Detection
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Solution Overview
Problem
LIDAR devices used for object detection, particularly in marine environments, suffer from high false positive rates when detecting falling objects, as they tend to detect various objects and structures, leading to unnecessary alarms and reducing the reliability of legitimate 'man overboard' event detection.
Innovation Solution
Implementing sophisticated filtering techniques and improved detection field configurations, including plausibility testing based on parameters such as object size, velocity, and trajectory, to differentiate between human bodies and other objects, thereby reducing false positives and enhancing the detection of actual person-overboard events.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If LIDAR device detects all objects in detection field, then detection coverage is improved, but false positive rate increases
Solution Approach 1:
The system changes detection parameters by evaluating multiple characteristics of detected objects including size, shape, velocity, acceleration, and trajectory. By analyzing combinations of these parameters rather than relying on a single threshold, the system distinguishes between legitimate falling objects and false positive targets, thereby maintaining high detection accuracy while reducing false positive rate.
2Measurement precision
If LIDAR device increases detection sensitivity, then detection precision is improved, but false alarm rate increases
Solution Approach 1:
The system implements feedback mechanisms by continuously monitoring detected objects and adjusting detection thresholds based on historical data and current environmental conditions. The processor evaluates detected objects against established patterns and adjusts sensitivity dynamically, maintaining high detection precision while minimizing false alarms through adaptive feedback control.
Solution Approach 2:
The system dynamically adjusts detection parameters such as velocity thresholds, acceleration limits, and size ranges based on environmental context and historical detection patterns. By changing these parameters adaptively rather than using fixed thresholds, the system maintains high measurement precision while reducing false alarm rates.
3Reliability
If LIDAR device scans entire detection field, then detection completeness is improved, but detection time increases
Solution Approach 1:
The detection field is segmented into multiple zones with different scanning frequencies and priorities. High-priority zones near the vessel receive more frequent scanning, while distant low-priority zones are scanned less frequently. This segmentation maintains detection completeness for critical areas while reducing overall detection time and computational load.
Solution Approach 2:
The scanning pattern is made dynamic by adjusting scan frequency and resolution based on detected activity levels. When objects are detected or suspected activity occurs, the system increases scanning intensity in those specific regions. During periods of low activity, scanning intensity is reduced, thereby maintaining detection completeness while minimizing detection time.
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
The proposed solution significantly reduces false positive alarms, improving the accuracy and reliability of falling object detection, ensuring timely and appropriate responses to legitimate person-overboard events while maintaining a low false positive rate.
Implementation Method 1
LIDAR devices emit light and then detect objects based on the return reflections of the emitted light
Data Source
AI summary
In an aspect, a processing apparatus receives detection signaling indicating a field incursion in a detection field of a LIDAR device mounted to a marine vessel and oriented to detect objects within a free space alongside the marine vessel. The processing apparatus applies plausibility testing to the field incursion, including determining whether parameters derived from the detection signaling are characteristic of a human body falling from the marine vessel through the detection field. The processing apparatus outputs signaling indicating a person overboard event to an alarm or control system onboard the marine vessel, in response to the field incursion passing the plausibility testing.