UAV ADS-B Conflict Detection for Autonomous Collision Avoidance
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Solution Overview
Problem
Current UAV control systems may not account for non-fleet aircraft in their operational region, leading to potential mid-air collisions, as they rely on centralized control that lacks information about other aircraft.
Innovation Solution
UAVs equipped with ADS-B receivers can autonomously receive and process messages from intruder aircraft, predict potential conflicts, and adjust their flight paths to avoid collisions by determining safe landing locations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If centralized control is used to manage UAV fleet routes, then route coordination between fleet UAVs is improved, but awareness of non-fleet aircraft (intruders) deteriorates
Solution Approach 1:
Each UAV is equipped with ADS-B receivers and conflict detection logic that enables it to independently receive broadcasts from intruder aircraft, predict potential conflicts, and execute avoidance maneuvers without requiring centralized system coordination. This self-service capability allows individual UAVs to maintain situational awareness and safety autonomously.
Solution Approach 2:
The system implements a feedback loop where ADS-B messages from intruder aircraft continuously update the UAV's situational awareness, triggering conflict detection and prompting avoidance actions when necessary. This closed-loop feedback ensures the UAV responds dynamically to changing airspace conditions.
2Reliability
If autonomous conflict detection and avoidance is implemented, then collision prevention with intruder aircraft is improved, but computational load and system complexity increase
Solution Approach 1:
The patent separates conflict detection and avoidance functions into a dedicated subsystem that operates independently from the primary flight control system. This extracted subsystem specifically handles ADS-B message processing, conflict prediction, and avoidance maneuver execution, reducing the computational burden on the main flight control architecture.
Solution Approach 2:
The system performs preliminary conflict detection by continuously analyzing ADS-B messages and predicting potential conflicts before they occur. By identifying and addressing potential conflicts in advance, the system prevents dangerous situations from developing, reducing the need for complex real-time emergency response algorithms.
3Loss of information
If ADS-B message processing is added to UAV systems, then awareness of surrounding aircraft is improved, but energy consumption and computational resources increase
Solution Approach 1:
The system processes ADS-B messages selectively, focusing computational resources on detecting and analyzing messages from intruder aircraft that pose potential conflict risks. Rather than processing all received messages equally, the system applies partial action by prioritizing relevant threat detection over comprehensive analysis of all airborne traffic.
Data Source
AI summary
In some embodiments, a non-transitory computer-readable medium having logic stored thereon is provided. The logic, in response to execution by one or more processors of an unmanned aerial vehicle (UAV), causes the UAV to perform actions comprising receiving at least one ADS-B message from an intruder aircraft; generating a intruder location prediction based on the at least one ADS-B message; comparing the intruder location prediction to an ownship location prediction to detect conflicts; and in response to detecting a conflict between the intruder location prediction and the ownship location prediction, determining a safe landing location along a planned route for the UAV and descending to land at the safe landing location.