Drone Collision Avoidance Using Passive Optical Detection
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Solution Overview
Problem
Aerial drones lack the ability to comply with air traffic rules, specifically the 'see-and-avoid' function, which prevents them from safely navigating in non-segregated civil airspace due to the absence of a pilot on board, making existing collision avoidance systems like TCAS II inappropriate and restrictive.
Innovation Solution
A method for an aerial drone to receive signals from intruding aircraft, calculate estimated distances and altitudes, capture images to determine bearing angles, and validate positioning data using passive sensors, allowing for safe navigation and prediction of evasive actions without the need for a transponder on the drone.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If a drone is equipped with automated systems and sensors to enable autonomous flight, then the degree of autonomy is improved, but the ability to perform see-and-avoid function deteriorates due to absence of pilot
Solution Approach 1:
The patent replaces the mechanical/pilot-based see-and-avoid system with an automated optical detection system. The drone uses cameras and image processing algorithms to detect intruding aircraft, calculate bearing angles, and determine collision risk automatically, substituting the human pilot's visual detection capability with machine-based optical sensing and computational analysis.
Solution Approach 2:
The drone performs self-navigation and self-protection by autonomously processing visual data from its own cameras to detect intruding aircraft. The system uses its onboard computational resources to calculate bearing angles, assess collision risk, and execute avoidance maneuvers without external assistance, enabling the drone to serve its own safety needs.
2Reliability
If TCAS II system is installed on piloted aircraft to detect intruding aircraft, then collision avoidance capability is improved, but the system becomes inappropriate and restrictive for drones
Solution Approach 1:
The patent employs inexpensive passive sensors (cameras) instead of expensive active transponders required by TCAS II. The system uses readily available visual detection technology that is cost-effective and suitable for budget-constrained drone applications, replacing the costly transponder-based architecture with affordable optical sensing.
Solution Approach 2:
The patent extracts only the essential collision avoidance function from the complex TCAS II system, implementing a simplified version that uses passive visual detection rather than active transponder interrogation. This extracted core functionality is adapted specifically for drone operations, removing the restrictive elements of the original TCAS II design while retaining the essential safety capability.
3Device complexity
If passive sensors are used on the drone to receive signals from intruding aircraft, then the device complexity is reduced, but the measurement precision of positioning data deteriorates
Solution Approach 1:
The patent introduces an intermediary computational process that uses bearing angle measurements from the drone's camera to calculate the position of intruding aircraft. Instead of directly receiving precise positioning signals, the system uses visual bearing data as an intermediary to infer the location and movement of other aircraft, enabling passive sensors to achieve adequate positioning accuracy through mathematical derivation.
Solution Approach 2:
The patent transitions from direct signal-based positioning (one-dimensional signal strength measurement) to angular-based positioning (two-dimensional bearing angle measurement). By using the camera's field of view and calculating bearing angles in multiple dimensions, the system compensates for the limitations of passive sensors and achieves sufficient positioning precision without requiring active transponders.
Data Source
AI summary
A method of navigation of an aerial drone in the presence of at least one intruding aircraft in an airspace zone surrounding the drone, wherein an estimated distance between the drone and the intruding aircraft is calculated based on a strength of the signal received and validated if an estimated value of an element of positioning data calculated by the drone using the estimated distance substantially corresponds to a measured value of the element of positioning data. An aerial drone designed for implementation of this method.