Aircraft Autonomous Target Tracking via Image Analysis
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Solution Overview
Problem
Current methods for tracking mobile targets by aircraft, such as UAVs, require external radio control and are not efficient in minimizing uncertainty in target positioning, especially in dynamic environments.
Innovation Solution
A method that uses image analysis from onboard cameras to identify and track mobile targets by determining their coordinates in a Global Reference System, minimizing uncertainty through a pinhole camera model and eigenvalue calculations, allowing aircraft to autonomously adjust their position for optimal tracking without external control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If aircraft perform maneuvers following elliptical trajectories to track mobile targets, then tracking capability is improved, but device complexity and control difficulty increase
Solution Approach 1:
The aircraft is equipped with autonomous tracking capability through onboard cameras and image processing systems. The aircraft independently identifies mobile targets, calculates optimal positioning, and adjusts its own trajectory without requiring complex external radio control systems, thereby simplifying the control system while maintaining reliable tracking
Solution Approach 2:
The patent replaces complex mechanical control systems with optical and computational systems. By using onboard cameras to capture images and algorithms to process them, the system substitutes mechanical maneuver control with optical-field-based autonomous positioning, reducing mechanical complexity while improving tracking reliability
2Ease of operation
If external radio control is used to control aircraft positioning, then ease of operation is improved, but extent of automation deteriorates
Solution Approach 1:
The aircraft performs autonomous target identification and tracking using onboard cameras and image processing algorithms. The system independently determines its own positioning relative to mobile targets without requiring external radio control commands, achieving full automation while simplifying operation through autonomous decision-making
3Measurement precision
If aircraft maintain fixed position to monitor mobile targets, then measurement precision of target coordinates is improved, but productivity decreases due to limited field of view
Solution Approach 1:
The aircraft dynamically adjusts its position and orientation based on real-time image analysis. Instead of maintaining a fixed position, the aircraft moves autonomously to optimize its viewing angle and distance to the target, thereby maintaining measurement precision while expanding the effective field of view and monitoring efficiency
Solution Approach 2:
The system uses onboard cameras to continuously capture images of the target and surrounding environment. This visual feedback is processed to determine the aircraft's relative position to the target, and the information is fed back to adjust the aircraft's positioning in real-time, achieving both precision and efficiency
Data Source
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AI summary
A method for positioning aircrafts based on analyzing images of mobile targets, the method includes the following steps: a) identifying a mobile target by means of an image obtained by means of a camera mounted on an aircraft; b) determining the coordinates of the aircraft with respect to a Global Reference System; c) determining the coordinates of the mobile target with respect to the Global Reference System; d) determining an area of uncertainty associated to the determination of the coordinates of the mobile target with respect to the Global Reference System; e) determining an optimum position of the aircraft from which to monitor the mobile target in such a way that the area of uncertainty associated to the determination of the coordinates of the mobile target with respect to the Global Reference System is minimized, and; f) flying the aircraft towards the optimum position.