Multispectral Object Identification for All-Weather Aircraft Positioning
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Solution Overview
Problem
Advanced autonomous aircraft require a system to navigate safely in all weather conditions, as existing visual-based synthetic vision systems are ineffective in adverse weather, and traditional navigation systems may be unreliable, necessitating a multispectral object identification and positioning solution.
Innovation Solution
A multispectral object identification and positioning system utilizing a suite of sensors including vision, RF RADAR, LIDAR, and avionics, with a processor and multispectral database to correlate sensor data across diverse spectra, enabling precise positioning and navigation by matching sensed attributes with historical data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If a camera-supported synthetic vision system is used, then visual display capability is provided for manned aircraft, but the system becomes unable to sense objects in adverse weather conditions
Solution Approach 1:
The patent combines multiple sensing systems operating in different spectral bands (visible spectrum cameras, infrared sensors, radar) into an integrated synthetic vision system. This merging allows the system to maintain object sensing capability across various weather conditions by switching between or combining data from different spectral modalities, thereby resolving the contradiction between visual display quality and reliability in adverse weather.
Solution Approach 2:
The synthetic vision system is designed to perform multiple functions across different spectral bands and weather conditions. The system can operate in visible spectrum for clear weather visual displays, switch to infrared for thermal imaging in poor visibility, and utilize radar for precipitation penetration, making it universally applicable across all weather scenarios while maintaining both visual display capability and object sensing reliability.
2Illumination intensity
If human-oriented visual displays are provided for manned aircraft, then pilot visibility is improved, but additional hardware weight and processing requirements increase
Solution Approach 1:
The sensor suite is designed with multi-functionality, where sensors operating in different spectral bands serve dual purposes: they capture data for both human-oriented visual displays and machine processing for autonomous navigation. This eliminates the need for separate hardware systems, reducing overall weight while maintaining display visibility and processing capabilities.
3Device complexity
If traditional single-spectrum navigation systems are used, then system simplicity is maintained, but positioning accuracy and reliability in all weather conditions deteriorates
Solution Approach 1:
The patent merges multiple sensing systems operating in different spectral bands into an integrated navigation system. By combining visible spectrum, infrared, and radar sensors, the system achieves superior positioning accuracy and all-weather reliability while managing complexity through integrated processing architecture that correlates data across spectral modalities.
Solution Approach 2:
The system transitions from single-spectrum to multi-spectral sensing by adding spectral dimensionality. This allows the navigation system to extract positioning information from multiple spectral bands simultaneously, improving measurement precision and reliability without fundamentally increasing operational complexity, as the additional dimensional data is processed through correlated fusion algorithms.
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
Enables autonomous aircraft to accurately determine its position and navigate safely at any airport regardless of weather conditions by integrating multispectral sensor data, enhancing system precision and robustness.
Implementation Method 1
a laser imaging detection and ranging (LIDAR) system
Implementation Method 2
a laser imaging detection and ranging (LIDAR) system
Implementation Method 3
a radio frequency (RF) radio detection and ranging (RADAR) system
Data Source
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AI summary
A system (100) and method for augmenting synthetic vision system (SVS) databases with spectrum diverse features that are matched to the observations of natural scenes derived from non-visible band sensors. The system correlates sensor output (130) with a-priori information in databases (254) to enhance system precision and robustness. Multiple diverse sensors (132, 134, 136, 138) image naturally occurring, or artificial features (towers buildings etc.) and store the multi-spectral attributes of those features within the enhanced multi-spectral database and share the information with other systems. The system, upon "live" observation of those features and attributes, correlates current observations with expected fiducial observations in the multi-spectral database (254) and confirms operation, navigation, precise position, and sensor fidelity to enable autonomous operation of an aircraft (120) employing the system.