Multispectral Synthetic Vision Database for All-Weather Aircraft Positioning
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current autonomous aircraft systems lack the capability to accurately navigate and position themselves in various weather conditions due to reliance on visual displays that are ineffective in adverse weather, and they do not utilize multispectral data from diverse sensors for precise positioning.
Innovation Solution
A multispectral object identification system that integrates a suite of sensors including vision, RF RADAR, LIDAR, and avionics systems to create a multispectral database, allowing for the correlation of sensor data across different spectra to determine the position of an autonomous aircraft, enabling navigation through weather-independent data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If camera-based synthetic vision systems are used for object detection and positioning, then the system can provide visual information to pilots, but the system becomes unable to sense objects in adverse weather conditions
Solution Approach 1:
The patent combines multiple sensor types (camera, LIDAR, RADAR) into a unified sensor suite that operates across different spectral bands. This merging allows the system to maintain object detection capabilities in adverse weather by switching between or combining data from sensors that are sensitive to different types of electromagnetic radiation, thereby resolving the contradiction between reliable detection and weather adaptability.
Solution Approach 2:
The sensor suite is designed with multi-functionality to perform both visual surveillance in clear conditions and non-visual sensing in adverse weather. By incorporating sensors that operate in visible, near-infrared, and other spectral bands, the system achieves universal operation across varying weather conditions, eliminating the need for separate systems for different environmental scenarios.
2Ease of operation
If human-oriented visual displays are provided for manned aircraft, then pilots can visually navigate, but additional hardware weight and processing requirements increase
Solution Approach 1:
The sensor suite and processing system are designed to serve dual purposes: providing human-oriented visual displays for manned aircraft and generating precise positioning data for autonomous navigation. This multi-functionality eliminates the need for separate hardware systems, thereby reducing overall weight while maintaining ease of operation for visual navigation.
3Device complexity
If single-spectrum sensors are used for object detection, then the system structure remains simple, but the positioning precision deteriorates in adverse weather
Solution Approach 1:
The patent merges multiple sensors operating in different spectral bands into a coordinated system. This combination enables the system to maintain simple operational structure while achieving high positioning precision by selecting or combining data from the most appropriate sensor based on current weather conditions and target characteristics.
Solution Approach 2:
The system transitions from single-spectrum to multi-spectrum sensing, adding the spectral dimension to the detection capability. This dimensional expansion allows the system to detect objects across different spectral bands, thereby maintaining or improving positioning precision in adverse weather without significantly complicating the overall system structure through intelligent sensor fusion.
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 system enables autonomous aircraft to accurately navigate and position themselves at any airport, regardless of weather conditions, by utilizing multispectral data from diverse sensors, enhancing precision and robustness in positioning and navigation.
Implementation Method 1
a laser imaging detection and ranging (LIDAR) system
Implementation Method 2
a radio frequency (RF) radio detection and ranging (RADAR) system
Data Source
AI summary
A system 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 with a-priori information in databases to enhance system precision and robustness. Multiple diverse sensors 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 and confirms operation, navigation, precise position, and sensor fidelity to enable autonomous operation of an aircraft employing the system.