3D LIDAR Aircraft Collision Avoidance System

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Solution Overview

Problem

Aircraft collision avoidance systems face challenges in detecting obstacles during ground operations due to limited pilot visibility and high false alarm rates from radar sensors, which lack sufficient resolution to discriminate object size and elevation.

Innovation Solution

A LIDAR-based aircraft collision avoidance system utilizing multiple 3D LIDAR sensors mounted on aircraft exterior lighting fixtures, processing sensor data to determine object locations and dimensions, and transmitting this data for fusion and alert generation to reduce false alarms and enhance obstacle detection.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Volume of moving object

If radar sensors are used for obstacle detection, then detection range is improved, but measurement precision deteriorates leading to false alarms

Engineering Contradiction:
Improvedetection rangeVSAvoidobject discrimination capability
Core Design Contradiction:
Volume of moving objectVSMeasurement precision

Solution Approach 1:

The patent replaces radar sensors with LIDAR (Light Detection and Ranging) sensors that use laser light instead of radio waves. This substitution enables precise measurement of object distance, size, and elevation through time-of-flight measurements of laser pulses, thereby eliminating false alarms while maintaining detection range.

Inventive Principle:
Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The patent changes the detection parameter from radio wave reflection (radar) to laser light time-of-flight measurement (LIDAR). This parameter change enables precise determination of object physical dimensions and elevation, allowing the system to discriminate between actual obstacles and non-threat objects, thus reducing false alarms.

Inventive Principle:
Principle #35Parameter changes

2Device complexity

If pilot field of view is limited, then aircraft design is simplified, but detection capability deteriorates in blind spots

Engineering Contradiction:
Improveaircraft design simplicityVSAvoidobstacle detection in blind spots
Core Design Contradiction:
Device complexityVSDifficulty of detecting and measuring

Solution Approach 1:

The patent divides the obstacle detection function into multiple LIDAR sensors positioned at different locations on the aircraft (wingtips, fuselage, etc.). Each sensor covers a specific field of view, collectively providing comprehensive coverage of all blind spots without requiring the pilot to manually scan all areas.

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

The patent introduces LIDAR sensors as intermediary devices between the pilot and obstacles in blind spots. These sensors automatically detect and track objects in areas the pilot cannot see, relaying information to the cockpit display system, thus eliminating the need for the pilot to directly observe all potential hazards.

Inventive Principle:
Principle #24Intermediary (Mediator)

3Area of stationary object

If multiple sensors are deployed to cover blind spots, then detection coverage is improved, but device complexity increases

Engineering Contradiction:
Improvedetection coverage areaVSAvoidsensor system complexity
Core Design Contradiction:
Area of stationary objectVSDevice complexity

Solution Approach 1:

The patent designs the LIDAR sensors to perform multiple functions: detecting obstacles, measuring distance, determining object size, and calculating elevation. This multi-functionality reduces the need for separate sensors for each measurement type, thereby limiting the increase in system complexity while maintaining comprehensive detection coverage.

Inventive Principle:
Principle #6Universality (Multi-functionality)

Solution Approach 2:

The patent combines data from multiple LIDAR sensors and integrates it with aircraft position and orientation information in a centralized processing system. This merging of data streams creates a unified three-dimensional representation of the environment, achieving comprehensive coverage without proportionally increasing system complexity.

Inventive Principle:
Principle #5Merging (Combining)

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 system provides enhanced obstacle detection and reduced false alarms by using multiple 3D LIDAR sensors to cover a wider area, process real-time 3D point cloud data, and generate accurate potential obstacle alerts, improving safety during ground operations.

Implementation Method 1

Each 3D LIDAR sensor is configured to sense objects within its field-of-view and supply sensor data

Methodology Applied
Scientific EffectTime of flight: Time of Flight

Implementation Method 2

a plurality of three-dimensional (3D) light detection and ranging (LIDAR) sensors

Methodology Applied
Scientific EffectLIDAR: LIDAR

Data Source

PatentUS11508247B2Lidar-based aircraft collision avoidance system
Publication Date: 2022.11.22 HONEYWELL INTERNATIONAL INC
  • US11508247B2 patent drawing
  • US11508247B2 patent drawing
  • US11508247B2 patent drawing

AI summary

An aircraft collision avoidance system includes a plurality of three-dimensional (3D) light detection and ranging (LIDAR) sensors, a plurality of sensor processors, a plurality of transmitters, and a display device. Each 3D LIDAR sensor is enclosed in an aircraft exterior lighting fixture that is configured for mounting on an aircraft, and is configured to sense objects within its field-of-view and supply sensor data. Each sensor processor receives sensor data and processes the received sensor data to determine locations and physical dimensions of the sensed objects. Each transmitter receives the object data, and is configured to transmit the received object data. The display device receives and fuses the object data transmitted from each transmitter, fuses the object data and selectively generates one or more potential obstacle alerts based on the fused object data.