Weighted Centroid Localization Algorithm for RSSI Positioning
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Solution Overview
Problem
Existing location estimation systems in wireless environments face challenges in achieving accurate and robust position determination of mobile devices at low costs, particularly in environments with multipath fading and measurement errors, where RSSI-based methods require complex calibration and are prone to performance issues.
Innovation Solution
A weighted Centroid Localization (WCL) algorithm that uses Received Signal Strength Indication (RSSI) measurements from gateways to estimate the position of a mobile node, involving the selection of a central gateway, calculation of averaging gateway spacing, exclusion of distant gateways, sorting of RSSI values, and computation of weighting factors based on RSSI rank, combined with a Kalman filter for tracking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If RSSI-based localization algorithm is used, then location estimation can be achieved at low cost, but measurement precision deteriorates due to multipath fading and measurement errors
Solution Approach 1:
The patent implements an iterative feedback mechanism where the localization algorithm continuously refines position estimates by comparing predicted RSSI values with actual measurements. The system adjusts weighting factors and recalculates positions based on residual errors, creating a closed-loop feedback system that progressively improves measurement precision while maintaining the low-cost RSSI-based approach
Solution Approach 2:
The patent dynamically changes weighting parameters in the localization algorithm based on signal quality metrics. By adjusting the influence of different reference nodes' RSSI measurements according to their reliability, the system optimizes location estimation accuracy under varying multipath conditions without requiring additional hardware or increasing cost
2Measurement precision
If complex calibration is applied to improve RSSI-based methods, then measurement precision improves, but device complexity increases
Solution Approach 1:
The patent employs lightweight, computationally efficient calibration techniques that can be performed quickly and discarded or updated periodically, rather than implementing complex permanent calibration systems. The calibration data is used to adjust weighting factors in the localization algorithm, providing measurement precision improvements without significant device complexity
Solution Approach 2:
The system performs self-calibration using the existing network infrastructure and measured RSSI values. The calibration process automatically adjusts parameters based on observed signal characteristics without requiring external calibration equipment or complex manual procedures, thereby improving measurement precision while minimizing added complexity
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The WCL algorithm achieves robust and accurate location estimation with reduced complexity and cost, demonstrating resilience to channel fading and measurement errors, and maintains performance under various multipath conditions.
Implementation Method 1
it is required that an infrastructure be able to estimate the position of one or several wireless objects or target nodes... the target node makes radio transmission, which is received by the gateways (reference nodes) around it
Data Source
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AI summary
The present invention proposes a weighted Centroid Localisation (WCL) algorithm, which does the location estimation based only on the known positions of the gateways and the measurements of the Received Signal Strength Indication (RSSI) at the gateways. The algorithm computes the weight of the gateway based on their rank when the gateways are sorted by their relative RSSI (230, 240). Simulations have demonstrated the algorithm's robustness under different multipath/fading channel conditions and its good location performance.