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Recent Advances in Electrical & Electronic Engineering

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ISSN (Print): 2352-0965
ISSN (Online): 2352-0973

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General Research Article

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

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

Volume 13, Issue 2, 2020

Page: [295 - 301] Pages: 7

DOI: 10.2174/2352096512666191024170807

Price: $65

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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