UAV Collision Avoidance via Multi-Spectral Detection
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Solution Overview
Problem
Current aircraft collision avoidance systems are often heavy, expensive, and rely on active transponder interrogation, making them ineffective in busy and unpredictable low-altitude airspace where objects without transponders may be invisible, and they require human intervention for safe operation.
Innovation Solution
An unmanned aerial vehicle (UAV) system equipped with sensors, such as cameras and acoustic sensors, that detect and analyze objects using visual and acoustic signals to determine their type, trajectory, and likelihood of change, and dynamically updates its flight plan to avoid collisions through a peer-to-peer communication network extending detection limits and accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If active transponder interrogation systems are used for aircraft collision avoidance, then detection capability is improved, but system weight and cost increase
Solution Approach 1:
The patent replaces active transponder interrogation systems with passive acoustic and optical detection systems. The acoustic sensors detect engine sounds and propeller noises, while optical sensors capture visual information about other aircraft, eliminating the need for heavy active radar and transponder equipment while maintaining detection capability.
Solution Approach 2:
The system creates multiple copies of detection capabilities across a network of lightweight UAVs. Each UAV carries simplified sensors, and collectively they provide comprehensive surveillance coverage through data sharing, replacing the need for each individual UAV to have heavy standalone detection systems.
2Weight of moving object
If passive transponder information transmission is used, then system weight is reduced, but detection of objects without transponders is lost
Solution Approach 1:
The patent implements multi-functional sensor systems that can detect both transponder-equipped and transponder-less objects. Acoustic sensors detect engine sounds from any aircraft, optical sensors capture visual information, and the system processes multiple signal types to identify objects regardless of their transponder status, providing universal detection capability.
Solution Approach 2:
The system uses acoustic signals and optical information as intermediaries to detect objects without transponders. These passive detection methods serve as mediators that bridge the gap between the UAV and undetected objects, enabling identification through non-transponder means while maintaining system lightness.
3Reliability
If human intervention is used for aircraft separation, then operational safety is maintained, but automation level decreases
Solution Approach 1:
The patent implements closed-loop feedback systems where sensors continuously monitor the environment, the processor analyzes detected objects and calculates collision risks, and the control system automatically adjusts flight paths to maintain safe separation. This automated feedback loop replaces human intervention while maintaining safety through continuous real-time monitoring and response.
Solution Approach 2:
The UAV system performs its own collision avoidance functions autonomously without requiring human operators. The integrated sensor-processing-control system serves itself by automatically detecting objects, evaluating threats, and executing avoidance maneuvers, enabling independent safe operation in busy airspace.
4Measurement precision
If multiple sensors and communication networks are deployed for object detection, then detection precision is improved, but device complexity increases
Solution Approach 1:
The patent combines acoustic sensors, optical sensors, and communication systems into an integrated detection and control architecture. The processor unifiedly processes data from all sensor types, and the system merges multiple detection functions into a single coordinated framework, improving detection precision while managing complexity through integration rather than separate independent systems.
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 autonomous operation of UAVs in busy airspace by actively monitoring and avoiding objects, including those without transponders, by using sensor data and communication networks to update flight plans and minimize interaction risks.
Implementation Method 1
a multispectral sensor for the detection and autonomous avoidance of objects during the UAV's operation
Implementation Method 2
an acoustic sensor (e.g., a microphone, etc.)
Implementation Method 3
one or more cameras capable of capturing one or more wavelengths of electromagnetic energy including infrared and/or visual
Data Source
AI summary
This disclosure is directed to a detection and avoidance apparatus for an unmanned aerial vehicle (“UAV”) and systems, devices, and techniques pertaining to automated object detection and avoidance during UAV flight. The system may detect objects within the UAV's airspace through acoustic, visual, infrared, multispectral, hyperspectral, or object detectable signal emitted or reflected from an object. The system may identify the source of the object detectable signal by comparing features of the received signal with known sources signals in a database. The features may include, for example, a multispectral signature emitted or reflected by the object. Furthermore, a trajectory envelope for the object may be determined based on characteristic performance parameters for the object such as cursing speed, maneuverability, etc. The UAV may determine an optimized flight plan based on the trajectory envelopes of detected objects within the UAV's airspace.