Study of four-dimensional DOA and polarisation estimation with crossed-dipole and tripole arrays

Electromagnetic (EM) vector sensor arrays can track both the polarisation and direction of arrival (DOA) of the impinging signals. For linear crossed-dipole arrays, as shown by our analysis, due to inherent limitation of the structure, it can only track one DOA parameter and two polarisation parameters. For full four-dimensional (4-D, 2 DOA and 2 polarization parameters) estimation, we could extend the linear crossed-dipole array to the planar case. In this paper, instead of extending the array geometry, we replace the crossed-dipoles by tripoles and construct a linear tripole array. It is proved that such a structure can estimate the 2-D DOA and 2-D polarisation information effectively in general and a dimension-reduction based MUSIC algorithm is developed so that the 4-D estimation problem can be simplified into two separate 2-D estimation problems, significantly reducing the computational complexity of the solution. The Cramr-Rao Bound (CRB) is also derived as a reference for algorithm performance. A brief comparison between the planar crossed-dipole array and the linear tripole array is performed at last, showing that although the planar structure has a better performance, it is achieved at the cost of increased physical size

Joint 4-D DOA and polarization estimation based on linear tripole arrays

Electromagnetic (EM) vector sensor arrays can track both the polarisation and direction of arrival (DOA) parameters of the impinging signals. For crossed-dipole linear arrays, due to inherent limitation of the structure, it can only track one DOA parameter and two polarisation parameters. This problem could be solved by extending the geometry to a two-dimensional (2-D) rectangular array so that both the azimuth and elevation angles of the signal can be estimated. In this paper, instead of extending the array to a higher dimension, we replace the crossed-dipoles by tripoles and construct a linear tripole array. It will be shown that such a structure can estimate the 2-D DOA and 2-D polarisation information effectively and a dimension-reduction based MUSIC algorithm is developed so that the 4-D estimation problem can be simplified to two separate 2-D estimation problems, significantly reducing the computational complexity of the solution