TDoA Local Positioning System Auto-Calibration via Residual Error Minimization
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Solution Overview
Problem
Current Local Positioning Systems (LPS) based on time-difference-of-arrival (TDoA) measurements lack an efficient auto-calibration method, relying on manual and time-consuming calibration processes, which are error-prone and not applicable for TDoA systems, limiting their accuracy and usability.
Innovation Solution
A method for calibrating TDoA-based LPS involves collecting multiple sets of time-difference-of-arrival measurements, calculating residual error vectors, and determining optimal beacon positions that minimize an objective function defined by the root mean square of these vectors, with steps for outlier detection and iterative optimization to achieve precise beacon node positioning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual calibration methods are used for LPS, then the calibration can be performed, but the process is time-consuming and error-prone
Solution Approach 1:
The system performs self-calibration by using the mobile node and available beacon nodes to automatically determine optimal beacon positions through TDoA measurements and optimization algorithms, eliminating the need for manual calibration operations
Solution Approach 2:
The patent replaces manual mechanical calibration tools (theodolites) with an automated computational system that uses TDoA measurements and optimization algorithms to determine beacon node positions
2Productivity
If existing auto-calibration methods are used, then calibration time is reduced, but these methods are not applicable for TDoA systems
Solution Approach 1:
The patent adapts calibration methodology by changing the measurement parameter from ToA to TDoA, developing optimization algorithms specifically tailored for TDoA-based LPS calibration that account for the differences in measurement principles
3Measurement precision
If more TDoA measurements are collected for calibration, then position determination accuracy is improved, but the complexity of the calibration process increases
Solution Approach 1:
The system uses feedback from multiple TDoA measurements and residual error vectors to iteratively optimize beacon node positions, where each measurement cycle provides feedback that refines the calibration accuracy
Solution Approach 2:
The patent transforms the calibration problem by introducing an optimization dimension that minimizes an objective function based on residual errors, converting a complex multi-parameter calibration into a systematic optimization process
Data Source
AI summary
A method for calibrating a time difference of arrival-based local positioning system for k−D localization, k=2 or 3, includes collecting N sets of time difference of arrival measurements related to a mobile node, N≥2, each nth set of measurements being performed by Bn beacon nodes among B beacon nodes of the positioning system while the mobile node is located is a nth position within a region covered by the positioning system, Bn≥k+2, and determining optimal beacon positions that minimize an objective function depending on N residual error vectors, the calculation of each nth position of the mobile node using beacon positions and the nth set of measurements, the calculation allowing the calculation of the nth residual error vector.