UAV Target Tracking Mode Switching Under Atmospheric Turbulence
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Solution Overview
Problem
Existing target tracking systems face challenges in efficiently identifying and tracking unmanned aerial vehicles (UAVs) due to atmospheric turbulence, which affects image quality and requires high computation costs and long processing times, especially when clear images of vulnerable parts are not available.
Innovation Solution
A target tracking device and method that selects between precision and rough tracking modes based on atmospheric conditions and target position, using a weather observation device to determine the appropriate tracking mode without relying on image recognition, thereby reducing computation costs and increasing processing speed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If image recognition technology using AI is used to determine whether the target image is clear enough to recognize the vulnerable part, then the determination accuracy is improved, but the computation cost and processing time increase
Solution Approach 1:
The system changes the parameter of tracking mode (precision vs. rough) based on atmospheric conditions and target position rather than relying on computationally intensive image recognition. This parameter change allows the system to maintain determination accuracy while avoiding the high computation cost and long processing time associated with AI-based image analysis.
Solution Approach 2:
The patent introduces an intermediary mechanism (atmospheric condition monitoring and position-based determination) that mediates between the need for accurate vulnerable part identification and the constraint of computation time. Instead of directly analyzing images to determine clarity, the system uses atmospheric data and position information as intermediaries to select appropriate tracking modes.
2Measurement precision
If image recognition technology using AI is used to determine whether the target image is clear enough to recognize the vulnerable part, then the determination accuracy is improved, but the computation cost increases
Solution Approach 1:
The system changes the parameter of tracking mode (precision vs. rough) based on atmospheric conditions and target position rather than relying on computationally intensive image recognition. This parameter change allows the system to maintain determination accuracy while avoiding the high computation cost associated with AI-based image analysis.
Solution Approach 2:
The patent introduces an intermediary mechanism (atmospheric condition monitoring and position-based determination) that mediates between the need for accurate vulnerable part identification and the constraint of computation cost. Instead of directly analyzing images to determine clarity, the system uses atmospheric data and position information as intermediaries to select appropriate tracking modes.
3Reliability
If precision tracking mode is used to focus on the vulnerable part of the target, then the countermeasure effectiveness is improved, but the tracking complexity increases
Solution Approach 1:
The system dynamically switches between precision tracking mode and rough tracking mode based on atmospheric conditions and target position. This dynamic adaptation allows the system to use complex precision tracking only when necessary (when atmospheric conditions are good and vulnerable parts are visible), while using simpler rough tracking in other conditions, thereby balancing countermeasure effectiveness with tracking complexity.
Solution Approach 2:
The patent applies different tracking modes (different levels of precision and complexity) to different local conditions (atmospheric conditions and target positions). Precision tracking is applied locally when conditions permit, while rough tracking is used in other areas, optimizing the balance between effectiveness and complexity.
4Ease of operation
If rough tracking mode is used to focus on the center-of-gravity part of the target, then the tracking simplicity is improved, but the countermeasure effectiveness decreases
Solution Approach 1:
The system dynamically switches between precision tracking mode and rough tracking mode based on atmospheric conditions and target position. This dynamic adaptation allows the system to use complex precision tracking only when necessary (when atmospheric conditions are good and vulnerable parts are visible), while using simpler rough tracking in other conditions, thereby balancing countermeasure effectiveness with tracking complexity.
Solution Approach 2:
The patent applies different tracking modes (different levels of precision and complexity) to different local conditions (atmospheric conditions and target positions). Precision tracking is applied locally when conditions permit, while rough tracking is used in other areas, optimizing the balance between effectiveness and complexity.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Efficient tracking of UAVs is achieved by selectively using precision or rough tracking modes, significantly reducing computation costs and processing times while maintaining accurate target engagement.
Implementation Method 1
Atmospheric turbulence is one of causes of being unable to obtain a clear image of the target. In a case where a ground surface is warmed by sunlight, atmosphere near the ground surface is warmed by the ground surface, and the atmospheric turbulence may occur.
Implementation Method 2
the countermeasure can be performed in a short time by irradiating a vulnerable part of a target... performing a countermeasure by irradiating a focused part of the target with a laser beam
Data Source
AI summary
Provided are a target tracking device that efficiently tracks a target, a target tracking method, and a recording medium for storing a target tracking program. This target tracking device comprises a determination condition selector and a tracker. The determination condition selector selects a tracking mode for tracking a detected target from among a plurality of tracking modes on the basis of a group of determination conditions related to the position of the target. The tracker tracks the target in the selected tracking mode. The plurality of tracking modes include a first tracking mode that focuses on the vulnerable portion of the target and a second tracking mode that focuses on the center of gravity of the target. The target tracking device further comprises a coping device that irradiates the focused portion of the target with a laser beam to cope with the target.