Platform-mounted artificial vision system for rotorcraft DVE navigation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Rotorcraft pilots face significant challenges navigating in degraded visual environments (DVE) due to conditions like brownout, whiteout, smoke, rain, mist, fog, darkness, and helicopter rotor blade obstruction, which obscure their vision and increase the risk of crashes.
Innovation Solution
A platform-mounted artificial vision system that includes a self-contained image system with a forward-looking infrared video source, inertial measurement unit, and image processing system to capture and stabilize sequential images, calculate situational awareness data, and convert them into visible images for display, enhancing navigation by identifying obstacles and overcoming environment-based occlusion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If pilots navigate in degraded visual environments (brownout, whiteout, smoke, rain, mist, fog, darkness, rotor blade obstruction), then the risk of crashes increases due to obscured vision, but using conventional visual navigation methods cannot provide sufficient situational awareness
Solution Approach 1:
The patent introduces an artificial vision system as an intermediary between the pilot and the degraded environment. The system uses infrared video sources to capture thermal radiation from objects in the environment, processes these images to enhance visibility, and displays them to the pilot. This intermediary system allows pilots to see through conditions that would otherwise obscure their natural vision, directly addressing the harmful effects of degraded visual environments while maintaining navigation safety.
2Reliability
If an artificial vision system is implemented to provide situational awareness in DVE conditions, then navigation safety improves, but the system complexity increases due to multiple sensors and processing requirements
Solution Approach 1:
The patent merges multiple functions into a single integrated artificial vision system. The system combines infrared video capture, image stabilization using inertial measurement unit data, situational awareness calculation, and visible image conversion into one cohesive system mounted on the platform. This integration reduces the overall system complexity compared to having separate systems for each function, while still providing comprehensive navigation safety improvements.
Solution Approach 2:
The artificial vision system is designed with multi-functionality to address various degraded visual conditions simultaneously. The infrared video sources and image processing system can operate effectively in brownout, whiteout, smoke, rain, mist, fog, darkness, and rotor blade obstruction conditions. This universal approach allows a single system to handle multiple types of visual degradation without requiring separate specialized systems for each condition, thereby managing complexity while improving reliability.
3Measurement precision
If sequential images are captured and processed to calculate situational awareness data and convert to visible images, then obstacle identification improves, but the processing time and computational load increase
Solution Approach 1:
The system performs preliminary actions by capturing sequential infrared images and stabilizing them using inertial measurement unit data before full processing. This preliminary stabilization and alignment of sequential frames prepares the data in advance, reducing the computational load during the actual situational awareness calculation and visible image conversion phases. By pre-processing the images to correct for platform motion, the system reduces overall processing time while maintaining obstacle identification accuracy.
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 pilots with enhanced situational awareness and obstacle identification, improving navigation safety during take-off and landing in DVE conditions by stabilizing images and highlighting critical objects, thereby reducing the risk of accidents.
Implementation Method 1
a forward-looking infrared video source, inertial measurement unit, and image processing system to capture and stabilize sequential images
Implementation Method 2
an inertial measurement unit configured to generate inertial data associated with the moving platform
Data Source
AI summary
One embodiment includes an artificial vision system mounted on a platform. The system includes an image system comprising a video source that is configured to capture a plurality of sequential images. The image system also includes an image processing system configured, via at least one processor, to process the plurality of sequential images to calculate situational awareness (SA) data with respect to each of the plurality of sequential images and to convert the processed plurality of sequential images to visible images. The system further includes a video display system configured to display the visible images associated with the processed plurality of sequential images and to visibly identify the SA data relative to the platform.