Target Tracking System Lag Correction Feed-Forward Vector
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Solution Overview
Problem
Conventional projection systems often deviate from tracked objects when they are in a moving state, leading to inaccuracies in projectile targeting.
Innovation Solution
A target tracking system and method that includes an observation module, a dynamic tracking module, and an aiming module, which capture and analyze frames to calculate lag correction and feed-forward vectors, allowing the aiming module to align with and lead the tracked object by generating and executing control commands to adjust the aiming point image.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a projection system projects a projectile towards a tracked object, then the projectile can be aimed at the target, but the projected object deviates from the tracked object when it is in a moving state
Solution Approach 1:
The system calculates a feed-forward correction vector based on the lag correction vector and distance to the tracked object, then applies this correction in advance before the projectile is projected. This preliminary action compensates for the object's motion during the projectile's flight time, ensuring the projectile accurately hits the moving target rather than deviating from it.
Solution Approach 2:
The system continuously monitors the position of the tracked object and dynamically adjusts the aiming point by applying both lag correction and feed-forward correction vectors. This feedback mechanism ensures that the aiming point remains accurately aligned with the moving object throughout the projection process, resolving the deviation problem.
2Measurement precision
If the aiming module continuously adjusts to track a moving object, then alignment precision is improved, but the system complexity increases
Solution Approach 1:
The correction process is segmented into two distinct vectors: lag correction vector (for real-time position alignment) and feed-forward correction vector (for predictive positioning). This segmentation allows each vector to handle specific aspects of the tracking problem independently, simplifying the overall control logic while maintaining high precision.
Solution Approach 2:
By pre-calculating the feed-forward correction vector based on current motion patterns, the system reduces the need for continuous complex calculations during real-time tracking. This preliminary computation simplifies the real-time control burden while maintaining alignment precision.
Data Source
AI summary
A target tracking system includes an observation module, a dynamic tracking module, a control module and an aiming module. The observation module captures an observation frame including a tracked-object image of a tracked-object and an aiming point image and detects a distance between the observation module and the tracked-object. The dynamic tracking module analyzes the observation frame to obtain a lag correction vector between the aiming point image and the tracked-object image, and obtains a feed-forward correction vector according to the lag correction vector and the distance. The control module generates a control command representing the lag correction vector and a control command representing the feed-forward correction vector. The aiming module moves according to the control commands to control the aiming point image to align with the tracked-object image and control the aiming point image to lead the tracked-object image.