title: Compressive Sensing Based Design of Sparse Tripole Arrays.
abstract: This paper considers the problem of designing sparse linear tripole arrays. In such arrays at each antenna location there are three orthogonal dipoles, allowing full measurement of both the horizontal and vertical components of the received waveform. We formulate this problem from the viewpoint of Compressive Sensing (CS). However, unlike for isotropic array elements (single antenna), we now have three complex valued weight coefficients associated with each potential location (due to the three dipoles), which have to be simultaneously minimised. If this is not done, we may only set the weight coefficients of individual dipoles to be zero valued, rather than complete tripoles, meaning some dipoles may remain at each location. Therefore, the contributions of this paper are to formulate the design of sparse tripole arrays as an optimisation problem, and then we obtain a solution based on the minimisation of a modified l1 norm or a series of iteratively solved reweighted minimisations, which ensure a truly sparse solution. Design examples are provided to verify the effectiveness of the proposed methods and show that a good approximation of a reference pattern can be achieved using fewer tripoles than a Uniform Linear Array (ULA) of equivalent length.
authors.affiliation: Department of Automatic Control and Systems Engineering, University of Sheffield, Sheffield S1 3JD, UK. m.hawes@sheffield.ac.uk.
authors.forename: Matthew
authors.initials: M
authors.lastname: Hawes
authors.affiliation: Department of Electronic and Electrical Engineering, University of Sheffield, Sheffield S1 3JD, UK. w.liu@sheffield.ac.uk.
authors.forename: Wei
authors.initials: W
authors.lastname: Liu
authors.affiliation: Department of Automatic Control and Systems Engineering, University of Sheffield, Sheffield S1 3JD, UK. l.s.mihaylova@sheffield.ac.uk.
authors.forename: Lyudmila
authors.initials: L
authors.lastname: Mihaylova
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D012815:Signal Processing, Computer-Assisted
keywords: compressive sensing; reweighted minimisation; sparse array; tripoles; vector sensors