Wearable Sensor Localization Considering Mixed Distributed Sources in Health Monitoring Systems

Liangtian Wan; Guangjie Han; Hao Wang; Lei Shu; Nanxing Feng; Bao Peng

doi:10.3390/s16030368

Wearable Sensor Localization Considering Mixed Distributed Sources in Health Monitoring Systems

Sensors (Basel). 2016 Mar 12;16(3):368. doi: 10.3390/s16030368.

Authors

Liangtian Wan¹, Guangjie Han², Hao Wang³, Lei Shu⁴, Nanxing Feng⁵, Bao Peng⁶

Affiliations

¹ Department of Information and Communication Systems, Hohai University, Changzhou 213022, China. wanliangtian1@163.com.
² Department of Information and Communication Systems, Hohai University, Changzhou 213022, China. hanguangjie@hhu.edu.cn.
³ Department of Information and Communication Systems, Hohai University, Changzhou 213022, China. wanghaohhu@outlook.com.
⁴ Guangdong Petrochemical Equipment Fault Diagnosis Key Laboratory, Guangdong University of Petrochemical Technology, Guangdong 525000, China. lei.shu@ieee.org.
⁵ Institute of Electromagnetics and Acoustics, Xiamen University, Xiamen 361005, China. fengnaixing@gmail.com.
⁶ School of Electronic and Communication, Shenzhen Institute of Information Technology, Shenzhen 518172, China. pengb@sziit.com.cn.

Abstract

In health monitoring systems, the base station (BS) and the wearable sensors communicate with each other to construct a virtual multiple input and multiple output (VMIMO) system. In real applications, the signal that the BS received is a distributed source because of the scattering, reflection, diffraction and refraction in the propagation path. In this paper, a 2D direction-of-arrival (DOA) estimation algorithm for incoherently-distributed (ID) and coherently-distributed (CD) sources is proposed based on multiple VMIMO systems. ID and CD sources are separated through the second-order blind identification (SOBI) algorithm. The traditional estimating signal parameters via the rotational invariance technique (ESPRIT)-based algorithm is valid only for one-dimensional (1D) DOA estimation for the ID source. By constructing the signal subspace, two rotational invariant relationships are constructed. Then, we extend the ESPRIT to estimate 2D DOAs for ID sources. For DOA estimation of CD sources, two rational invariance relationships are constructed based on the application of generalized steering vectors (GSVs). Then, the ESPRIT-based algorithm is used for estimating the eigenvalues of two rational invariance matrices, which contain the angular parameters. The expressions of azimuth and elevation for ID and CD sources have closed forms, which means that the spectrum peak searching is avoided. Therefore, compared to the traditional 2D DOA estimation algorithms, the proposed algorithm imposes significantly low computational complexity. The intersecting point of two rays, which come from two different directions measured by two uniform rectangle arrays (URA), can be regarded as the location of the biosensor (wearable sensor). Three BSs adopting the smart antenna (SA) technique cooperate with each other to locate the wearable sensors using the angulation positioning method. Simulation results demonstrate the effectiveness of the proposed algorithm.

Keywords: direction-of-arrival (DOA) estimation; health monitoring systems; incoherently-distributed (ID) and coherently-distributed (CD) sources; virtual multiple input and multiple output (VMIMO).

Publication types

Research Support, Non-U.S. Gov't