Terrain Fusion Processor for Airborne Vehicle Displays
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Solution Overview
Problem
Conventional pilot assistance systems, such as synthetic vision systems and enhanced vision systems, primarily provide two-dimensional direct sensor image representation, which is inadequate for accurately displaying terrain and obstacles in adverse weather conditions, and lack effective fusion of database and sensor data to account for varying perspectives and measurement inaccuracies.
Innovation Solution
The integration of a synthetic vision system with a database and an enhanced vision system using a fusion processor that employs an error function to store height information in a two-dimensional grid network, combining 3D sensor data with existing terrain and obstacle data for real-time segmentation and adaptive grid representation, supporting the 'See & Remember' concept for accurate terrain visualization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If two-dimensional direct sensor image representation is used, then the system is simple to implement, but it is inadequate for accurately displaying terrain and obstacles in adverse weather conditions
Solution Approach 1:
The patent combines database terrain data with real-time sensor data into a unified three-dimensional representation. The fusion processor integrates information from multiple sources (database, LADAR, cameras) to create a comprehensive terrain model that overcomes the limitations of simple two-dimensional sensor images while maintaining operational feasibility through systematic data integration.
Solution Approach 2:
The patent transitions from two-dimensional sensor image representation to three-dimensional terrain visualization. By adding the vertical dimension and creating a three-dimensional grid network, the system achieves more accurate terrain and obstacle display, enabling pilots to perceive depth, elevation, and spatial relationships that are lost in flat two-dimensional images.
2Measurement precision
If database terrain data and sensor data are fused, then measurement accuracy improves, but processing complexity increases
Solution Approach 1:
The patent segments the terrain representation into a grid network structure, dividing the three-dimensional space into discrete cells. This segmentation allows the fusion processor to handle data systematically by processing individual cells rather than continuous data streams, reducing computational complexity while maintaining high measurement precision through cell-level detail.
Solution Approach 2:
The patent applies different processing qualities to different regions of the terrain data. The system uses adaptive refinement where areas requiring higher precision (such as regions with obstacles or terrain features of interest) receive more detailed processing, while other areas use coarser representation. This local quality approach optimizes the balance between accuracy and processing complexity.
3Reliability
If three-dimensional terrain visualization is implemented, then pilot assistance in adverse weather is enhanced, but data processing requirements increase
Solution Approach 1:
The patent implements a dynamic terrain representation system that adapts to changing flight conditions and sensor data availability. The three-dimensional grid network is updated in real-time, with the fusion processor dynamically adjusting which cells require processing based on aircraft position, altitude, and detected features. This dynamic approach maintains high reliability for pilot assistance while optimizing computational power usage by focusing processing on relevant regions.
Data Source
AI summary
An apparatus for displaying terrain on a display apparatus of an airborne vehicle is provided. The apparatus includes a synthetic vision system having a terrain and obstruction database, an enhanced vision system with sensors for recording terrain data, a height and position sensor for determining the flight state data, a display apparatus, a processor for fusion of the data from the synthetic vision system and from the enhanced vision system. The height information that is produced by the synthetic vision system and the enhanced vision system is stored as pixels in a two-dimensional grid network. The fusion processor uses an error function for insertion of a pixel into the two-dimensional grid network. The error function provides an estimate of the size of the respective cell in which the pixel is stored, from the distance between the pixel and the sensor position.