System error correction method and system based on ecef and q-type cluster analysis
The systematic error correction method using ECEF and Q-type clustering analysis solves the problem of systematic error in radar multi-source data fusion, improves the accuracy and consistency of the data, and enhances the effect of systematic error correction.
CN119535376BActive Publication Date: 2025-11-11THE 724TH RESEARCH INSTITUTE OF CHINA STATE SHIPBUILDING CORP LTD
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Patent Information
- Application Number
- CN202411399519.1
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2024-10-09
- Publication Date
- 2025-11-11
- Estimated Expiration
- 2044-10-09
AI Technical Summary
Technical Problem
Existing radar multi-source data fusion methods suffer from systematic errors, which affect the accuracy of the data and the fusion effect. Traditional correction methods also suffer from positioning errors and data inconsistencies.
Method used
A systematic error correction method based on ECEF and Q-type clustering analysis is adopted to identify and correct systematic errors through data preprocessing, multi-source data fusion, ECEF coordinate transformation and Q-type clustering analysis.
Benefits of technology
It improves the accuracy and consistency of multi-source data fusion, identifies potential patterns and regularities in the data, and enhances the effect of system error correction.
✦ Generated by Eureka AI based on patent content.
Abstract
This invention discloses a three-coordinate system error correction method based on ECEF and Q-type clustering analysis. Addressing the problem of multi-node inability to coordinate tracking due to sensor system errors in multi-sensor target tracking systems, this invention first collects multi-source data, preprocesses the data, then fuses the multi-source data, transfers the resulting system error information to the ECEF coordinate system for unified representation and processing, performs Q-type clustering analysis on the transformed system error data, and corrects the system error based on the Q-type clustering results, thereby improving data accuracy and consistency.
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