NDLI: Optimal weighted K-nearest neighbour algorithm for wireless sensor network fingerprint localisation in noisy environment

Content Provider	IET Digital Library
Author	Fang, Xuming Jiang, Zonghua Nan, Lei Chen, Lijun
Abstract	The weighted K-nearest neighbour (WKNN) algorithm is widely applied to fingerprint positioning. However, the node position estimated by the WKNN algorithm is not optimal in a noisy environment. To obtain the optimised node location estimate, the authors propose an optimal WKNN (OWKNN) algorithm for wireless sensor network (WSN) fingerprint localisation in a noisy environment. The proposed OWKNN algorithm is composed of an adaptive Kalman filter (AKF) and a memetic algorithm (MA). First, the AKF is utilised to reduce the measurement noise of the received signal strength indication (RSSI) between the nodes in the WSN. Then, the MA is employed to optimise the calibration point weight for estimating the position of a target node in the WSN according to the filtered RSSI and a calibrated radio map. Finally, an optimal node location estimate is achieved based on the optimised weight. The extensive experimental results reveal that the localisation accuracy of the proposed algorithm is at least ∼50% higher than those of the state-of-the-art fingerprint localisation algorithms regardless of the placement of the target node, number of beacon nodes, and size of the calibration cell.
Starting Page	1171
Ending Page	1177
Page Count	7
ISSN	17518628
Volume Number	12
e-ISSN	17518636
Issue Number	Issue 10, Jun (2018)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-com/12/10
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-com.2017.0515
Journal	IET Communications
Publisher Date	2018-03-08
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Adaptive Filter Adaptive Kalman Filter AKF Calibrated Radio Map Calibration Point Weight Optimization Filtering Method in Signal Processing Fingerprint Localisation Algorithm Fingerprint Positioning Kalman Filter Measurement Noise Reduction Memetic Algorithm Nearest Neighbour Method Node Position Estimation Noisy Environment Optimal Weighted K-nearest Neighbour Algorithm Optimised Node Location Estimate OWKNN Algorithm Received Signal Strength Indication RSSI Sensor Placement Statistics Target Node Position Estimation Wireless Sensor Network WKNN Algorithm WSN
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering Computer Science Applications

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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