Wearable Sensor Localization Considering Mixed Distributed Sources in Health Monitoring Systems

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.

[1]  Yang Hao,et al.  Wireless body sensor networks for health-monitoring applications , 2008, Physiological measurement.

[2]  Björn E. Ottersten,et al.  Estimation of nominal direction of arrival and angular spread using an array of sensors , 1996, Signal Process..

[3]  Eric Moreau,et al.  A generalization of joint-diagonalization criteria for source separation , 2001, IEEE Trans. Signal Process..

[4]  Raviv Raich,et al.  Bearing estimation for a distributed source: modeling, inherent accuracy limitations and algorithms , 2000, IEEE Trans. Signal Process..

[5]  Hatem Boujemaa.  Signal Processing Extension of COMET algorithm to multiple diffuse source localization in azimuth and elevation , 2005, Eur. Trans. Telecommun..

[6]  H. S. Wolff,et al.  iRun: Horizontal and Vertical Shape of a Region-Based Graph Compression , 2022, Sensors.

[7]  Xiansheng Guo,et al.  Low-complexity parameters estimator for multiple 2D domain incoherently distributed sources , 2011 .

[8]  Lin Tian,et al.  A Novel AWSF Algorithm for DOA Estimation in Virtual MIMO Systems , 2013, IEEE Journal on Selected Areas in Communications.

[9]  Qun Wan,et al.  Parameters localisation of coherently distributed sources based on sparse signal representation , 2007 .

[10]  Jiming Chen,et al.  Data gathering optimization by dynamic sensing and routing in rechargeable sensor networks , 2013, 2013 IEEE International Conference on Sensing, Communications and Networking (SECON).

[11]  Guangjun Li,et al.  2D DOA Estimator for Multiple Coherently Distributed Sources Using Modified Propagator , 2012, Circuits Syst. Signal Process..

[12]  Ingrid Moerman,et al.  A Comprehensive Survey of Wireless Body Area Networks , 2012, Journal of Medical Systems.

[13]  Guangjie Han,et al.  Analysis of Energy-Efficient Connected Target Coverage Algorithms for Industrial Wireless Sensor Networks , 2017, IEEE Transactions on Industrial Informatics.

[14]  Iickho Song,et al.  Low-complexity estimation of 2D DOA for coherently distributed sources , 2003, Signal Process..

[15]  Guangjie Han,et al.  The Critical Patients Localization Algorithm Using Sparse Representation for Mixed Signals in Emergency Healthcare System , 2018, IEEE Systems Journal.

[16]  Iickho Song,et al.  Distributed source modeling and direction-of-arrival estimation techniques , 1997, IEEE Trans. Signal Process..

[17]  Xiao-Ye Xu,et al.  Two-dimensional direction of arrival estimation by exploiting the symmetric configuration of uniform rectangular array , 2012 .

[18]  Tiejun Lv,et al.  An ESPRIT-Based Approach for 2-D Localization of Incoherently Distributed Sources in Massive MIMO Systems , 2014, IEEE Journal of Selected Topics in Signal Processing.

[19]  P. Stoica,et al.  Decoupled estimation of DOA and angular spread for spatially distributed sources , 1999 .

[20]  Guangjie Han,et al.  PD Source Diagnosis and Localization in Industrial High-Voltage Insulation System via Multimodal Joint Sparse Representation , 2016, IEEE Transactions on Industrial Electronics.

[21]  Guangjie Han,et al.  Two Novel DOA Estimation Approaches for Real-Time Assistant Calibration Systems in Future Vehicle Industrial , 2017, IEEE Systems Journal.

[22]  Thomas L. Marzetta,et al.  Noncooperative Cellular Wireless with Unlimited Numbers of Base Station Antennas , 2010, IEEE Transactions on Wireless Communications.

[23]  Eric Moulines,et al.  A blind source separation technique using second-order statistics , 1997, IEEE Trans. Signal Process..

[24]  L. Gatzoulis,et al.  Wearable and Portable eHealth Systems , 2007, IEEE Engineering in Medicine and Biology Magazine.

[25]  Yide Wang,et al.  A modified COMET-EXIP method for estimating a scattered source , 2006, Signal Process..

[26]  Per Hjalmar Lehne,et al.  An Overview of Smart Antenna Technology for Mobile Communications Systems , 1999, IEEE Commun. Surv. Tutorials.

[27]  Shahram Shahbazpanahi,et al.  A generalized capon estimator for localization of multiple spread sources , 2004, IEEE Trans. Signal Process..

[28]  Petre Stoica,et al.  Approximate maximum likelihood estimators for array processing in multiplicative noise environments , 2000, IEEE Trans. Signal Process..

[29]  Guangjie Han,et al.  An energy efficient DOA estimation algorithm for uncorrelated and coherent signals in virtual MIMO systems , 2015, Telecommun. Syst..

[30]  H. Vincent Poor,et al.  Estimation of the number of sources in unbalanced arrays via information theoretic criteria , 2005, IEEE Transactions on Signal Processing.

[31]  Guangjie Han,et al.  DOA Estimation for Coherently Distributed Sources Considering Circular and Noncircular Signals in Massive MIMO Systems , 2017, IEEE Systems Journal.

[32]  Jeffrey G. Andrews,et al.  What Will 5G Be? , 2014, IEEE Journal on Selected Areas in Communications.

[33]  Tiejun Lv,et al.  A beamspace approach for 2-D localization of incoherently distributed sources in massive MIMO systems , 2016, Signal Process..

[34]  Yide Wang,et al.  Efficient Subspace-Based Estimator for Localization of Multiple Incoherently Distributed Sources , 2008, IEEE Transactions on Signal Processing.