Weighted K-nearest Neighbor Fast Localization Algorithm Based on RSSI for Wireless Sensor Systems

Author(s): Lu Bai*, Chenglie Du, Jinchao Chen

Journal Name: Recent Advances in Electrical & Electronic Engineering
Formerly Recent Patents on Electrical & Electronic Engineering

Volume 13 , Issue 2 , 2020

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Graphical Abstract:


Background: Wireless positioning is one of the most important technologies for realtime applications in wireless sensor systems. This paper mainly studies the indoor wireless positioning algorithm of robots.

Methods: The application of the K-nearest neighbor algorithm in Wi-Fi positioning is studied by analyzing the Wi-Fi fingerprint location algorithm based on Received Signal Strength Indication (RSSI) and K-Nearest Neighbor (KNN) algorithm in Wi-Fi positioning. The KNN algorithm is computationally intensive and time-consuming.

Results: In order to improve the positioning efficiency, improve the positioning accuracy and reduce the computation time, a fast weighted K-neighbor correlation algorithm based on RSSI is proposed based on the K-Means algorithm. Thereby achieving the purpose of reducing the calculation time, quickly estimating the position distance, and improving the positioning accuracy.

Conclusion: Simulation analysis shows that the algorithm can effectively shorten the positioning time and improve the positioning efficiency in robot Wi-Fi positioning.

Keywords: K-nearest neighbor, Wi-Fi positioning, RSSI, wireless sensor system, location fingerprint positioning, K-Means.

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Article Details

Year: 2020
Page: [295 - 301]
Pages: 7
DOI: 10.2174/2352096512666191024170807
Price: $25

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