Single-Camera Aircraft Position Refinement for Aerial Refueling
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Solution Overview
Problem
Aerial refueling currently relies on human operators, which is costly and requires additional equipment like stereoscopic vision systems or LIDAR, increasing operational expenses.
Innovation Solution
The system receives a video stream from a single camera, determines initial aircraft position estimates, refines these estimates temporally using known flight path trajectories, and controls an aerial refueling boom to engage the fuel receptacle based on the refined position.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If human operators are used for aerial refueling, then operational flexibility and decision-making capability are improved, but operational costs and equipment requirements increase
Solution Approach 1:
The aerial refueling system performs self-service through autonomous operation. The single camera captures video frames, the processor determines aircraft position estimates, refines them temporally, and controls the boom engagement without human intervention. This eliminates the need for human operators and expensive supplemental systems while maintaining refueling capability.
Solution Approach 2:
The patent replaces mechanical/optical measurement systems (stereoscopic vision, LIDAR, radar) with a computational approach using a single camera and processor. The system substitutes physical measurement hardware with image processing and temporal refinement algorithms to achieve accurate position estimation.
2Measurement precision
If stereoscopic vision with dual cameras is used, then position estimation accuracy is improved, but system cost and complexity increase
Solution Approach 1:
The patent extracts the essential function of position estimation from complex multi-camera or LIDAR systems and implements it using a single camera combined with temporal refinement processing. The system takes out the measurement function from expensive hardware and relocates it to computational processing.
Solution Approach 2:
The system uses a single, relatively simple camera instead of expensive, complex supplemental systems. The processor compensates for the simpler hardware through sophisticated temporal refinement algorithms, achieving accurate position estimation with less expensive equipment.
3Measurement precision
If LIDAR or radar is used for range measurements, then measurement precision is improved, but system cost and complexity increase
Solution Approach 1:
The patent replaces physical range measurement systems (LIDAR, radar) with an optical system (single camera) combined with computational processing. The processor derives position information from video frames and refines it temporally, substituting active sensing hardware with passive optical sensing and computational analysis.
4Device complexity
If automated position estimation is used, then operational cost is reduced, but measurement precision may worsen
Solution Approach 1:
The system maintains continuous position estimation through temporal refinement using multiple video frames. The processor determines initial position estimates for each frame, then refines them by considering the sequence of frames and expected aircraft motion. This continuous processing maintains accuracy while enabling automated operation.
Solution Approach 2:
The temporal refinement process uses feedback from previous frame estimates and aircraft motion models to improve current position estimates. The system compares initial estimates with expected trajectories and adjusts accordingly, maintaining precision through iterative refinement based on temporal consistency.
Data Source
AI summary
Aspects of the disclosure provide fuel receptacle position estimation for aerial refueling (derived from aircraft position estimation). A video stream comprising a plurality of video frames each showing an aircraft to be refueled, is received from a single camera. An initial position estimate is determined for the aircraft for the plurality of video frames, generating an estimated flight history for the aircraft. The estimated flight history for the aircraft is used to determine a temporally consistent refined position estimate, based on known aircraft flight path trajectories in an aerial refueling setting. The position of a fuel receptacle on the aircraft is determined, based on the refined position estimate for the aircraft, and an aerial refueling boom may be controlled to engage the fuel receptacle. Examples may use a deep learning neural network (NN) or optimization (e.g., bundle adjustment) to determine the refined position estimate from the estimated flight history.