Digital Weapon Sight Image Registration for Hands-Free Zeroing
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Solution Overview
Problem
Current digital weapon sights lack a fast, hands-free method for aligning the sight with the weapon, requiring complex calculations and manual adjustments that are not feasible for small processors or tactical settings.
Innovation Solution
A digital weapon sight system that captures pre-shot and post-shot imagery data, automatically adjusts the reticle position based on image registration algorithms, and minimizes user intervention through image processing and sensor integration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual zeroing process is used with traditional telescopic sights, then aiming precision can be achieved, but the process is time-consuming and requires multiple manual adjustments
Solution Approach 1:
The patent replaces the manual mechanical zeroing process with an automated digital image processing system. The system captures images before and after shots, uses image registration algorithms to automatically calculate the translational offset between the reticle and actual impact point, and adjusts the reticle position digitally without manual knob adjustments.
Solution Approach 2:
The system performs self-calibration by automatically capturing pre-shot and post-shot images, processing them through image registration algorithms, and adjusting its own reticle positioning based on the calculated offset. This eliminates the need for external manual intervention in the zeroing process.
2Manufacturing precision
If complex image processing algorithms are used for aimpoint correction, then alignment accuracy is improved, but the computational complexity exceeds the capabilities of small processors in weapon sights
Solution Approach 1:
The patent extracts and implements only the essential image registration functionality needed for aimpoint correction, rather than using full-featured complex image processing algorithms. This selective approach reduces computational requirements to levels suitable for small embedded processors while maintaining sufficient alignment accuracy.
Solution Approach 2:
The system adjusts image processing parameters such as resolution, registration algorithm complexity, and processing thresholds to optimize the balance between alignment accuracy and computational load, making advanced image processing feasible on resource-constrained devices.
3Reliability
If traditional manual reticle adjustment is used, then the sight can be zeroed to the weapon, but the process requires user intervention and multiple steps
Solution Approach 1:
The patent replaces manual mechanical reticle adjustment with automated digital reticle repositioning. The system calculates the necessary adjustment based on image registration and automatically updates the reticle position on the display, eliminating manual knob turning and multiple adjustment steps.
Solution Approach 2:
The system implements a feedback loop where pre-shot and post-shot images are compared, the translational offset is calculated, and this information is used to automatically adjust the reticle position. This closed-loop approach ensures reliable alignment while simplifying user operation to merely triggering the zeroing process.
Data Source
AI summary
Systems and methods are disclosed to correct aimpoint of digital weapon sight. The method employs the components of a digital weapon sight configured together for a process of sensing of a ballistic event, storing of orientation data and digital imagery data before and after a shot or series of shots, and then performing an image registration algorithm using the imagery data stored. The image registration determines the translational offset between the images, and aimpoint of subsequent shooting is corrected through application of adjusted reticle symbology or adjusted image sensor windowing.