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Sensors 2018, 18(6), 1925; https://doi.org/10.3390/s18061925

A Direct Position-Determination Approach for Multiple Sources Based on Neural Network Computation

1,2
,
1,2,* , 1,2
and
1,2
1
National Digital Switching System Engineering and Technology Research Center, Zhengzhou 450002, China
2
Zhengzhou Information Science and Technology Institute, Zhengzhou 450002, China
*
Author to whom correspondence should be addressed.
Received: 24 April 2018 / Revised: 5 June 2018 / Accepted: 11 June 2018 / Published: 13 June 2018
(This article belongs to the Section Sensor Networks)

Abstract

The most widely used localization technology is the two-step method that localizes transmitters by measuring one or more specified positioning parameters. Direct position determination (DPD) is a promising technique that directly localizes transmitters from sensor outputs and can offer superior localization performance. However, existing DPD algorithms such as maximum likelihood (ML)-based and multiple signal classification (MUSIC)-based estimations are computationally expensive, making it difficult to satisfy real-time demands. To solve this problem, we propose the use of a modular neural network for multiple-source DPD. In this method, the area of interest is divided into multiple sub-areas. Multilayer perceptron (MLP) neural networks are employed to detect the presence of a source in a sub-area and filter sources in other sub-areas, and radial basis function (RBF) neural networks are utilized for position estimation. Simulation results show that a number of appropriately trained neural networks can be successfully used for DPD. The performance of the proposed MLP-MLP-RBF method is comparable to the performance of the conventional MUSIC-based DPD algorithm for various signal-to-noise ratios and signal power ratios. Furthermore, the MLP-MLP-RBF network is less computationally intensive than the classical DPD algorithm and is therefore an attractive choice for real-time applications. View Full-Text
Keywords: direct position determination (DPD); neural network; multiple signal classification algorithm; maximum likelihood estimator direct position determination (DPD); neural network; multiple signal classification algorithm; maximum likelihood estimator
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Chen, X.; Wang, D.; Yin, J.; Wu, Y. A Direct Position-Determination Approach for Multiple Sources Based on Neural Network Computation. Sensors 2018, 18, 1925.

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