Aircraft Landing Site Localization Using Terrain Relative Navigation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current aviation technologies rely heavily on GPS and ground infrastructure for aircraft navigation during landing, which can be unreliable or unavailable in certain conditions, and lack the ability to accurately align and control aircraft trajectory without human intervention.
Innovation Solution
A method utilizing onboard sensors such as LIDAR, RADAR, and time-of-flight sensors to detect and identify visual and geometric features of a landing site, enabling terrain relative navigation and autonomous control of aircraft to a predetermined landing site without GPS, by determining a confidence score and generating navigational instructions for alignment and go-around maneuvers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If GPS and ground infrastructure are used for aircraft navigation, then navigation reliability is improved, but the system becomes dependent on external infrastructure that may be unavailable in certain conditions
Solution Approach 1:
The patent introduces terrain relative navigation (TRN) as an intermediary system that mediates between GPS dependency and operational independence. TRN uses onboard sensors (LIDAR, RADAR, time-of-flight sensors) to detect and identify visual and geometric features of the landing site, enabling navigation without external GPS infrastructure. This intermediary system allows the aircraft to operate reliably in GPS-denied environments while maintaining navigation accuracy through sensor-based terrain feature recognition and confidence scoring.
2Productivity
If automated control systems are implemented, then operational efficiency is improved, but the complexity of the control system increases
Solution Approach 1:
The automated control system is segmented into distinct functional modules: sensor data acquisition (LIDAR, RADAR, time-of-flight sensors), feature detection and identification, confidence score calculation, and navigational instruction generation. Each module performs a specific function, reducing overall system complexity while enabling comprehensive automated control. The segmentation allows independent optimization and validation of each component, improving reliability without requiring excessive integration complexity.
Solution Approach 2:
The system implements feedback through confidence score determination, where the calculated confidence level feeds back into the control decision-making process. When confidence scores indicate sufficient accuracy in landing site identification and alignment, automated control is activated; otherwise, the system can transition to manual control or request additional sensor data. This feedback mechanism enables automated operation without requiring overly complex control logic, as the feedback loop provides clear decision boundaries.
3Adaptability or versatility
If sensor-based terrain relative navigation is used, then independence from GPS is achieved, but measurement precision requirements increase
Solution Approach 1:
The patent merges multiple sensor types (LIDAR, RADAR, time-of-flight sensors) into a unified terrain relative navigation system. By combining the measurements from these different sensor modalities, the system achieves the required measurement precision through data fusion. Each sensor type contributes different strengths (e.g., LIDAR for geometric features, RADAR for visual features in various weather conditions), and their merged output provides robust precision for landing site identification and aircraft alignment without relying on any single high-precision sensor.
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 automated and accurate aircraft landing sequences, improving alignment and reliability by using sensor data to validate the correct landing site and adjust flight paths, even in obstructed views or without human intervention, and can function as a replacement or aid for human pilots.
Implementation Method 1
A method utilizing onboard sensors such as LIDAR, RADAR, and time-of-flight sensors to detect and identify visual and geometric features of a landing site
Implementation Method 2
A method utilizing onboard sensors such as LIDAR, RADAR, and time-of-flight sensors to detect and identify visual and geometric features of a landing site
Implementation Method 3
A method utilizing onboard sensors such as LIDAR, RADAR, and time-of-flight sensors to detect and identify visual and geometric features of a landing site
Data Source
AI summary
The method can include: sampling sensor measurements, extracting features from the sensor measurements, identifying a landing site based on the extracted features, determining a confidence score based on the extracted features and landing site features, and controlling the aircraft. The method functions to provide terrain relative navigation during approach to be used for aircraft control; the method can additionally function to establish an aircraft position estimate to be used for controlling the aircraft.