Wireless Sensor Network Positioning Edge Accuracy
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Solution Overview
Problem
The general wireless centroid localization (WCL) algorithm in wireless sensor networks experiences increased localization errors near the edge and corner regions of the network, where the positioning accuracy is compromised due to the assumption of equal weights for anchor nodes within and outside the reception circle.
Innovation Solution
The proposed method involves setting test nodes at regular intervals to pre-map and store the number and position information of anchor nodes within a predetermined distance, detecting matching test nodes, and estimating the unknown node's position by calculating the average coordinate value of the detected test nodes, thereby reducing localization errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the general WCL algorithm uses equal weights for all anchor nodes within the reception circle, then the positioning operation is simple and fast, but the localization error increases in edge and corner regions
Solution Approach 1:
The patent applies local quality by assigning different weights to anchor nodes based on their spatial location relative to the unknown node. Specifically, anchor nodes are classified into three regions (first, second, and third regions) with progressively decreasing weights, allowing the algorithm to account for the reduced reliability of anchor nodes in edge and corner areas while maintaining computational efficiency
Solution Approach 2:
The reception circle is segmented into multiple regions (first region with weight w1, second region with weight w2, third region with weight w3) based on distance from the unknown node. This segmentation allows the algorithm to apply different weighting strategies to different spatial zones, improving localization accuracy without significantly increasing computational complexity
2Device complexity
If anchor nodes are weighted equally within the reception circle, then the algorithm structure remains simple, but positioning accuracy deteriorates near network edges and corners
Solution Approach 1:
The patent introduces local quality by implementing a weighted centroid algorithm where weights vary based on the anchor node's position relative to the unknown node. The reception circle is divided into regions with different weight assignments (w1 > w2 > w3), enabling the algorithm to adapt to local spatial characteristics and improve accuracy in edge and corner regions while maintaining relatively simple computational structure
Solution Approach 2:
The patent applies preliminary action by pre-calculating and storing the weighted centroid positions for various anchor node configurations. This pre-computation allows the algorithm to quickly retrieve and use pre-determined weights during positioning operations, reducing real-time computational complexity while maintaining improved accuracy through the weighted approach
Data Source
AI summary
Provided is a wireless positioning method using a wireless sensor network, for estimating a position of an unknown node that is a positioning target by using a plurality of anchor nodes arranged at regular intervals, the wireless positioning method including: setting a plurality of test nodes at regular intervals on a space formed by some of the plurality of anchor nodes; obtaining a number and position information of anchor nodes within a predetermined distance from the unknown node; detecting at least one test node matching the obtained number and position information; and estimating a position of the unknown node by calculating an average coordinate value of the detected at least one test node.