Autonomous aircraft sensor-based positioning and navigation system using markers
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Solution Overview
Problem
Current systems lack an effective method for an autonomous aircraft to safely land without visual reference, as they rely on human-oriented infrastructure and traditional sensor systems that are not optimized for autonomous flight, requiring complex processing and maintenance.
Innovation Solution
A multispectral sensor suite onboard an autonomous aircraft, comprising a vision system, RF RADAR, LIDAR, and mapping system, with an object identification and positioning system that processes data to determine position and trajectory using historical object data and sensor attributes, enabling precise positioning and trajectory verification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional sensor systems and human-oriented infrastructure are used for autonomous aircraft landing, then the system can operate with existing infrastructure, but the system complexity and processing requirements increase significantly
Solution Approach 1:
The system segments the landing guidance function into multiple specialized sensors (vision system, RF radar, LIDAR, mapping system) that each handle specific aspects of navigation. This segmentation allows the system to process information in manageable modules rather than requiring a single complex processing system, thereby reducing overall system complexity while maintaining adaptability to existing infrastructure.
Solution Approach 2:
The patent applies universality by designing a multi-functional sensor suite that can operate with various existing infrastructure elements (runway lights, terrain features, navigation aids). The sensor system is configured to detect and process multiple types of objects and signals, allowing it to adapt to different landing environments without requiring specialized infrastructure for each scenario.
2Reliability
If human-oriented visual infrastructure (ALS, ILS, radio towers) is used, then the infrastructure is well-established, but it requires expensive maintenance and is not optimized for autonomous sensing
Solution Approach 1:
The autonomous aircraft performs self-positioning and self-navigation by detecting and identifying objects in its environment using its sensor suite. The system independently determines its position, trajectory, and alignment with the runway without requiring active guidance signals from external infrastructure. This self-service capability reduces dependence on maintained infrastructure while maintaining reliable operation.
Solution Approach 2:
The patent replaces mechanical and optical infrastructure elements (approach lighting systems, radio towers with flashing lights) with an electronic sensor-based detection system. Instead of relying on physical infrastructure to provide visual and radio frequency signals, the autonomous aircraft uses electronic sensors to detect and process electromagnetic radiation from passive objects, eliminating the need for expensive maintenance of active infrastructure.
3Ease of operation
If natural-looking images are generated for pilot consumption, then the images are visually pleasant, but extensive processing power is required and information may be occluded
Solution Approach 1:
Instead of processing sensor data to create natural-looking images for human consumption, the system inverts the approach by directly processing raw sensor data to extract positioning and navigation information. The object identification and positioning system analyzes sensor attributes (brightness, shape, position) to determine aircraft position and trajectory without generating intermediate visual representations, thereby eliminating the need for extensive image processing while maintaining operational effectiveness.
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 safe and precise autonomous aircraft landing by accurately identifying and positioning relative to sensor-tuned objects, verifying flight paths, and commanding flight controls, reducing reliance on human visual references and traditional infrastructure.
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 are disclosed for design of a suite of multispectral (MS) sensors and processing of enhanced data streams produced by the sensors for autonomous aircraft flight. The onboard suite of MS sensors is specifically configured to sense and use a MS variety of sensor-tuned objects, either strategically placed objects and/or surveyed and sensor significant existing objects to determine a position and verify position accuracy. The received MS sensor data enables an autonomous aircraft object identification and positioning system to correlate MS sensor data output with a-priori information stored onboard to determine and verify position and trajectory of the autonomous aircraft. Once position and trajectory are known, the object identification and positioning system commands the autonomous aircraft flight management system and autopilot control of the autonomous aircraft.