UAV Collision Avoidance Using Image Scale and Tracking Filter
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Solution Overview
Problem
Current collision avoidance systems for UAVs face challenges in accurately estimating Time To Collision (TTC) due to high uncertainty at long distances and limited applicability when intruding aircraft are far away, with existing methods either being unreliable at distance or lacking certainty when close.
Innovation Solution
A collision avoidance system that combines electro-optical sensors for estimating TTC based on scale change and tracking filters, using TTC estimates from image processing units as input to improve the accuracy and reduce uncertainty of TTC calculations, thereby enhancing decision-making for autonomous maneuvers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If scale change in target points between consecutive images is used to estimate TTC, then measurement precision is improved when the intruding aircraft is close, but the method is only applicable when the intruding aircraft is very close to the own aircraft
Solution Approach 1:
The patent combines two different TTC estimation methods: scale change estimation from image processing (accurate for close targets) and tracking filter estimation (effective for distant targets). By merging these methods and using their respective strengths in different distance ranges, the system achieves both high precision for close aircraft and broad applicability for distant aircraft, resolving the contradiction between measurement precision and adaptability
2Adaptability or versatility
If tracking filter is used to estimate TTC from sequence of observations, then adaptability is improved for distant aircraft, but the uncertainty in TTC estimates is high
Solution Approach 1:
The patent implements feedback by using the TTC estimate from scale change analysis as an input parameter to the tracking filter. This feedback mechanism allows the tracking filter to incorporate high-precision close-range TTC information into its estimation process, thereby reducing the inherent uncertainty of tracking filter estimates while maintaining its adaptability for distant aircraft
3Reliability
If safety value is added to TTC to calculate TTM, then reliability of collision avoidance decision is improved, but the time available for manoeuvre is reduced
Solution Approach 1:
The patent changes the parameter of TTC estimation by combining multiple estimation methods (scale change and tracking filter) to produce a more accurate and certain TTC value. This improved TTC estimation reduces the uncertainty component that normally requires a larger safety margin, thereby allowing for a smaller safety value in TTM calculation while maintaining high reliability of collision avoidance decisions
Data Source
AI summary
A collision avoidance system for deciding whether an autonomous avoidance maneuver should be performed in order to avoid a mid-air collision between a host aerial vehicle equipped with the system and an intruding aerial vehicle. At least one electro-optical sensor captures consecutive images of an intruding vehicle such that the vehicle manifests itself as a target point in the images. An image processor estimates the azimuth angle, elevation angle and a first time-to-collision estimate of the time to collision between the host vehicle and the intruding vehicle. The first time-to-collision estimate is estimated based on scale change in the target point between at least two of said consecutive images. A tracking filter is arranged to estimate a second time-to-collision estimate using the azimuth angle, the elevation angle and the first time-to-collision estimate estimated by the image processor as input parameters. A collision avoidance module is arranged to decide whether or not an avoidance maneuver should be performed based on any of at least one parameter, of which at least one is indicative of said second time-to-collision estimate.