UAV Target Tracking Using 3D Position Fusion for Fast Motion
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Solution Overview
Problem
Current tracking systems for unmanned aerial vehicles (UAVs) face challenges in accurately and efficiently tracking fast-moving targets due to the bulkiness and high power consumption of standalone GPS receivers, which also have slow refresh rates, leading to potential safety hazards when the UAV loses control.
Innovation Solution
A system that combines image data and location data to determine the three-dimensional location of a target using two-dimensional pixel coordinates and physical dimensions, employing a Kalman filter to enhance tracking accuracy and robustness, allowing the UAV to maintain a predetermined relative position and field of view while tracking high-speed targets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a standalone GPS receiver is used to track the target, then the target can provide three-dimensional position information, but the receiver is bulky and consumes high power
Solution Approach 1:
The patent combines image data processing with location data processing into a unified tracking system. The system integrates two-dimensional pixel coordinates from images with three-dimensional location coordinates from GPS to compute target position, eliminating the need for separate bulky GPS receivers at each target while maintaining tracking accuracy through data fusion.
2Measurement precision
If a standalone GPS receiver is used to track the target, then position information can be obtained, but the refresh rate is slow making it challenging to track fast-moving targets
Solution Approach 1:
The system merges high-speed image capture data with GPS location data to create a composite tracking solution. By processing two-dimensional pixel coordinates from rapid image sequences and combining them with three-dimensional location information, the system achieves high refresh rates suitable for fast-moving targets while maintaining positional accuracy through coordinate transformation and data fusion.
3Extent of automation
If the UAV controls its own movement autonomously based on tracking results, then the UAV can operate autonomously, but when the UAV fails to track the target, it may go out of control posing safety hazards
Solution Approach 1:
The system implements feedback mechanisms where the tracking results continuously inform UAV control decisions. By processing both image data and location data to determine target position, the system provides reliable feedback for autonomous navigation. The combination of visual tracking and GPS-based location tracking creates redundant feedback paths, improving system reliability and preventing loss of control when one tracking method fails.
Data Source
AI summary
A method of tracking a movement of a target by an unmanned aerial vehicle (UAV), the method includes receiving, from a mobile terminal collocating with the target, absolute location coordinate data of the target, acquiring, by a camera of the UAV, image data of the target, determining, based on the absolute location coordinate data and the image data of the target, 3D location coordinate data of the target with respect to the UAV, and controlling, based on the 3D location coordinate data of the target with respect to the UAV, at least one of a direction or a speed of the movement of the UAV, to maintain a constant relative 3D position of the UAV with respect to the target.