Target Tracking Prediction Error Adjustment for Maneuver Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing target tracking systems face challenges in maintaining accuracy when detecting maneuvers, leading to increased velocity and course errors due to delays in following the target's movement, especially during turns and acceleration/deceleration.
Innovation Solution
A target tracking apparatus with a maneuver detection time point prediction error adjusting unit that calculates a prediction error adjustment value by rotating the maneuver error in the course direction of the predicted speed, adjusting the target specification data error predicted value to reduce delays and maintain velocity and course errors small.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the sampling interval is increased to reduce processing load, then productivity improves, but measurement precision deteriorates due to delayed maneuver detection
Solution Approach 1:
The system performs preliminary calculations of prediction errors in both course and velocity directions before maneuver detection, enabling rapid adjustment when maneuvers are detected. This pre-computation allows the system to maintain high processing speed while being prepared to quickly respond to maneuver events, thus resolving the contradiction between processing load and detection accuracy.
Solution Approach 2:
The sampling interval and prediction error adjustment are made dynamic based on detected maneuver states. During normal operation, the system uses standard processing intervals to maintain productivity. When maneuvers are detected, the system dynamically adjusts by applying prediction error correction in course and velocity directions, ensuring measurement precision is maintained during critical maneuver phases without permanently increasing processing load.
2Reliability
If the prediction error is increased to reduce following delay during maneuvers, then reliability improves, but manufacturing precision deteriorates due to increased velocity and course errors
Solution Approach 1:
The system applies different prediction error adjustments to different components of the tracking data. Specifically, it adjusts the course direction prediction error and velocity direction prediction error separately and differently based on the maneuver type detected. This localized adjustment ensures reliability during maneuvers while maintaining velocity and course accuracy, as each parameter is corrected according to its specific error characteristics during the maneuver.
Solution Approach 2:
The system changes the prediction error parameters dynamically based on the detected maneuver type (turning around vs. straight-line acceleration/deceleration). For turning maneuvers, it applies one set of prediction error adjustments, while for straight-line maneuvers, it applies a different set. This parameter adaptation allows the system to maintain both reliability and precision by matching the correction strategy to the specific maneuver characteristics.
Data Source
AI summary
On adjusting a target specification data error predicted value so as to become larger on detecting maneuver of a target, the target specification data error predicted value is adjusted, in consideration of type of the maneuver and a course of the target, so as to make a direction of varying specification data large and to make a direction of constant specification data small. It is therefore possible to quickly recover a delay of the following of the varying specification data and to avoid increasing an error of the constant specification data.