Synthetic Vision Image Enhancement via Point Cloud Merging
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Solution Overview
Problem
Traditional Synthetic Vision Systems (SVS) in aircraft struggle to accurately represent external scenes due to low-resolution terrain data, which fails to individually render discrete structures, leading to incomplete and inaccurate images for pilots.
Innovation Solution
A system and method that combines first and second image data to generate a point cloud-based image, using an image processing unit to integrate data from Synthetic Vision Systems and Point Cloud Vision Systems, enhancing situational awareness by overlaying point cloud information onto synthetic images, providing meaningful height, range, and landing suitability information through color maps and highlighters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If low-resolution terrain data is employed in the SVS, then the system complexity is reduced, but the manufacturing precision of the synthetic image deteriorates because individual discrete structures cannot be individually rendered
Solution Approach 1:
The patent combines SVS synthetic image data with EVS point cloud image data to create an enhanced composite image. The EVS high-resolution point cloud data compensates for the low resolution of SVS terrain data, allowing individual discrete structures to be rendered accurately while maintaining system feasibility.
Solution Approach 2:
The patent creates a composite imaging system that integrates two different data sources (SVS and EVS) with complementary characteristics. The SVS provides broad coverage synthetic imagery while the EVS provides high-resolution point cloud data, and their combination produces an enhanced image with superior detail and accuracy.
2Manufacturing precision
If high-resolution terrain data is employed in the SVS, then the manufacturing precision of the synthetic image is improved, but the device complexity increases
Solution Approach 1:
Instead of using complex high-resolution SVS terrain data, the patent merges SVS synthetic imagery with EVS point cloud data. This approach achieves high-resolution rendering of discrete structures through the EVS component while keeping the overall system complexity manageable by leveraging existing SVS capabilities.
Solution Approach 2:
The EVS point cloud system acts as an intermediary that bridges the resolution gap in SVS imagery. The image processing unit processes and integrates the EVS high-resolution data with SVS data, providing detailed structure rendering without requiring the SVS system itself to be overly complex.
3Device complexity
If traditional SVS is used, then the device complexity is reduced, but the loss of information occurs because multiple elevations within one terrain cell cannot be generated meaningfully
Solution Approach 1:
The patent merges SVS synthetic image data with EVS point cloud image data to preserve multiple elevation information within terrain cells. The EVS point cloud captures discrete structures at their actual elevations, preventing information loss about individual structures while maintaining system simplicity.
Solution Approach 2:
The composite imaging approach combines SVS and EVS data sources, where the EVS point cloud component preserves detailed elevation information about discrete structures that would otherwise be lost in low-resolution SVS terrain cells. This composite approach maintains information completeness without excessive complexity.
4Reliability
If radar or LIDAR systems are used to capture real-time external scene data, then the reliability of the external scene representation is improved, but the use of energy increases due to beam transmission and reception operations
Solution Approach 1:
The EVS system performs multiple functions: it captures point cloud data for high-resolution imagery, provides real-time external scene representation, and supplies data for the enhanced composite image. This multi-functionality justifies the energy consumption by delivering reliable scene data with multiple uses.
Solution Approach 2:
The radar/LIDAR systems transmit beams and receive reflections to continuously update the external scene representation. This feedback mechanism ensures reliability by constantly monitoring and updating the scene data, with the energy consumption being necessary for maintaining accurate real-time representation.
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 enables pilots to gain enhanced situational awareness by presenting detailed, accurate, and real-time external scene information, improving the representation of discrete objects and landing suitability, thereby enhancing safety and operational effectiveness.
Implementation Method 1
Radar systems may control the direction of an electromagnetic beam... When the beam strikes or reflects off an object, part of the energy is reflected back and received by the active sensors
Implementation Method 2
When the beam strikes or reflects off an object, part of the energy is reflected back and received by the active sensors
Implementation Method 3
LIDAR systems may control the direction of a photonic beam... When the beam strikes or reflects off an object, part of the energy is reflected back and received by the active sensors
Implementation Method 4
The IPU may receive first image data representative of a first external scene, receive second image data, and combine the first image data with the second image data to produce third image data representative of a third image of the first external scene
Data Source
AI summary
Present novel and non-trivial system, device, and method for enhancing a three-dimensional synthetic image are disclosed. The image generating system is comprised of a first image data source, a second image data source, an image processing unit (“IPU”), and a display system. The IPU may be configured to receive first image data of a first image of a first external scene produced from object data; receive second image data of a second image of a second external scene produced from point cloud data acquired by one or more image capturing devices or object data augmented with point cloud data; combine the first image data with the second image data to produce third image data of a third image of the first external scene; and provide the third image data set to the display system. Fourth image data could be received and included in the production of the three image data.