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A new localization algorithm based on neural networks

Affiliation/Institute
Lübeck University of Applied Sciences
Pelka, Mathias;
Affiliation/Institute
Lübeck University of Applied Sciences
Constapel, Manfred;
Affiliation/Institute
Lübeck University of Applied Sciences
Le Anh, Duc Tu;
ORCID
0000-0001-7619-8015
Affiliation/Institute
Institute of Telematics, University of Lübeck
Hellbrück, Horst

Indoor localization plays a major role in a wide range of applications. To determine the location of a tag, localization algorithm is required. In the past, machine learning algorithms were difficult to implement in consumer hardware, but with the advent of tensor processing units, even smartphones are capable to use artificial intelligence to solve complex problems. In this paper, we investigate a machine learning algorithm based on neural networks and compare the result to a linear least squares estimator. We design and evaluate different neural networks. Based on our observation, the neural network delivers poor performance compared to the linear least squares estimator.

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