Electro-Optical Sighting System Automatic Target Tracing
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Solution Overview
Problem
Existing sighting systems face challenges in accuracy and convenience, particularly for beginners, due to incorrect sighting gestures and the difficulty in tracking moving targets within a limited field of view, requiring frequent adjustments and recalibration.
Innovation Solution
An automatic target point tracing method for electro-optical sighting systems using image processing techniques, including feature extraction, ridge regression classification, and sliding window methods to mark, trace, and re-detect target points within and outside the field of view, enhancing tracking performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a mechanical sight or optical sight is used, then the sighting system can be mounted and used, but the shooting accuracy is influenced by incorrect sighting gestures and poor shooting experience, especially for beginners
Solution Approach 1:
The system automatically performs target recognition and tracking without requiring manual adjustment or user expertise. The electro-optical sighting system self-adjusts to maintain accurate targeting by automatically detecting and following the target's position, eliminating the need for beginner users to master complex sighting gestures.
Solution Approach 2:
The patent replaces manual mechanical sighting operations with an automated electro-optical system that uses image processing algorithms. The system substitutes human judgment and manual adjustment with electronic detection and automatic tracking, thereby improving both ease of operation and shooting accuracy simultaneously.
2Reliability
If manual adjustment and calibration are performed multiple times during shooting, then the sighting system can adapt to different conditions, but the shooting process becomes time-consuming and inefficient
Solution Approach 1:
The system performs preliminary target recognition and feature extraction before actual shooting occurs. By pre-processing images to identify target characteristics and prepare tracking parameters, the system eliminates the need for repeated manual calibration during the shooting process, thereby reducing time loss while maintaining adaptability.
Solution Approach 2:
The electro-optical system continuously tracks the target throughout the shooting process without interruption. The automatic tracking algorithm maintains constant monitoring and adjustment, ensuring continuous adaptability to target movement without requiring periodic manual re-calibration, thus eliminating time losses associated with repeated adjustments.
3Measurement precision
If the field of view of the sight is kept small for detailed viewing, then the sighting precision is improved, but when the target moves or is jittered, the target becomes extremely difficult to find and re-acquire
Solution Approach 1:
The system dynamically adjusts its tracking capabilities based on target movement. When the target moves out of the current field of view, the system automatically re-acquires the target by expanding the search area and using motion prediction algorithms. This dynamic adaptation allows the system to maintain both precision (when target is in view) and ease of re-acquisition (when target moves), resolving the contradiction between fixed field of view limitations and dynamic target tracking needs.
Data Source
AI summary
An automatic target point tracing method, marking a target object in an image acquired by the sighting system to obtain a target point, performing feature extraction and feature description on the image with the target point, and establishing a ridge regression classifier and performing learning training on the classifier according to the extracted features; calculating a regression score of the features of the real-time acquired image in the trained ridge regression classifier, determining that the target point is automatically recognized when the regression score reaches a requirement, and displaying an orientation of the target point in a display unit area; and determining that the target object disappears when the regress core does not reach the requirement, and performing searching near a position where the target object disappears.