Multi-Sensor Collision Avoidance for UAVs
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current collision avoidance systems, such as TCAS, are not error-proof and require human visual confirmation, which is impractical for unmanned aerial vehicles (UAVs), limiting their ability to safely operate in commercial airspace.
Innovation Solution
A multi-sensor collision avoidance system that correlates TCAS tracking data with optical tracking data to provide automated advisories, using a combination of sensors like IR, LIDAR, radar, and others to determine collision threats and generate appropriate maneuvers for UAVs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If TCAS tracking is used for collision avoidance, then collision detection capability is provided, but error-prone tracking data is generated requiring human visual confirmation
Solution Approach 1:
The patent combines TCAS tracking data with optical sensor tracking data into a unified collision avoidance system. The processor correlates data from both sensors to generate more reliable collision advisories, eliminating the need for human visual confirmation while maintaining high reliability through multi-source data fusion.
Solution Approach 2:
The system implements feedback by continuously monitoring both TCAS and optical sensor data, comparing the correlated tracking information, and automatically adjusting collision avoidance advisories based on the correlated data. This closed-loop feedback mechanism replaces human visual confirmation with automated sensor-based verification.
2Measurement precision
If human visual inspection is required to confirm TCAS advisories, then accuracy can be verified, but automation is reduced making UAV operation impossible
Solution Approach 1:
The system performs self-service by automatically verifying advisory accuracy through correlation of TCAS and optical sensor data. The processor autonomously compares tracking data from both sensors, confirms target identity, and validates advisories without human intervention, enabling full automation suitable for UAV operation.
Solution Approach 2:
The patent replaces the mechanical human visual inspection process with an automated optical sensor system. The optical sensor captures imagery, the processor analyzes the imagery to identify targets, and correlates this data with TCAS information, substituting human eyes and brain processing with automated sensor and algorithm processing.
3Extent of automation
If multiple sensors are employed for collision avoidance, then automated advisories can be provided for UAVs, but system complexity increases
Solution Approach 1:
The processor performs multiple functions using the same hardware components: it processes TCAS tracking data, processes optical sensor imagery, correlates the two data sources, generates collision advisories, and controls the UAV. This multi-functionality reduces the need for separate dedicated systems for each function, managing complexity while maintaining automation.
Data Source
AI summary
An embodiment of the present invention provides a collision avoidance system for a host aircraft comprising a plurality of sensors for providing data about other aircraft that may be employed to determine one or more parameters to calculate future positions of the other aircraft, a processor to determine whether any combinations of the calculated future positions of the other aircraft are correlated or uncorrelated, and a collision avoidance module that uses the correlated or uncorrelated calculated future positions to provide a signal instructing the performance of a collision avoidance maneuver when a collision threat exists between the host aircraft and at least one of the other aircraft.