NDLI: Rectangular array of electromagnetic vector sensors: tensor modelling/decomposition and DOA-polarisation estimation

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Rectangular array of electromagnetic vector sensors: tensor modelling/decomposition and DOA-polarisation estimation

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IET Wireless Sensor Systems

Micro & Nano Letters

The Journal of Engineering

Rectangular array of electromagnetic vector sensors: tensor modelling/decomposition and DOA-polarisation estimation

Content Provider	IET Digital Library
Author	Ahmed, Tanveer Xiaofei, Zhang Wang, Zheng Gong, Pan
Abstract	In this study, the authors propose a fast quadrilinear decomposition algorithm for estimation of the directions-of-arrival and polarisations of the incident sources via a uniform rectangular array of electromagnetic vector sensors (EMVSs). Conventional quadrilinear alternating least squares (QALS), involves computationally intensive Khatri-Rao products in each iteration, to update the parameter matrices (factors). Moreover, QALS is more likely to fall in a local minimum and tends to take more steps before an acceptable solution, which further slows down the convergence and often mis-converges, thereby yielding meaningless results. To preserve the quadrilinearity, they arrange the measurements as a four-dimensional (4D) data (fourth-order tensor), from which a third-order sub-tensor (3D slice) can be obtained by fixing one index along any dimension. These slices are used to create new cost functions that are alternately minimised while updating the factors until convergence. They show that the rows of parameter matrices form the diagonal elements of a tensor, which capture the internal quadrilinearity of data and significantly reduce the cost function in few iterations only. Simulation results verify that the authors’ algorithm holds faster convergence, does not mis-converge, provides parameter estimation accuracy similarly to the QALS and superior of the Estimation of Signal Parameters via Rotational Invariance Technique and propagator method.
Starting Page	689
Ending Page	699
Page Count	11
ISSN	17519675
Volume Number	13
e-ISSN	17519683
Issue Number	Issue 7, Sep (2019)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-spr/13/7
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-spr.2018.5512
Journal	IET Signal Processing
Publisher Date	2019-06-21
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	3D Slice Acceptable Solution Array Signal Processing Cost Function Digital Signal Processing Direction of Arrival Estimation Directions-of-arrival DOA-polarisation Estimation Electromagnetic Vector Sensor Fast Quadrilinear Decomposition Algorithm Four-dimensional Data Fourth-order Tensor Incident Source Intensive Khatri-Rao Product Internal Quadrilinearity Interpolation And Function Approximation Iterative Method Least Squares Approximation Linear Algebra Local Minimum Matrix Algebra Numerical Analysis Parameter Estimation Parameter Estimation Accuracy Parameter Matrix Polarisation QALS Signal Parameter Signal Processing And Detection Tensors Third-order Sub-tensor Uniform Rectangular Array
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering

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