What is it about?
In this work we consider a coprime electromagnetic vector sensor array and apply parafac decomposition to the ULAs of the coprime array. We estimate parameters from the two arrays and chose the best estimate among all the measurements. The selection of this best estimate is based on the minimum distance, the estimate has from a convex set. Simulation results prove the efficacy of the proposed method.
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Why is it important?
We consider a coprime array of electromagnetic vector sensors that jointly provide the DOA and polarization estimation of the incident sources, thereby providing another dimension to diversity. This addition is extremely important in wireless communications for increased capacity. Because of the sparse antenna array, the available degrees of freedom are much higher than the conventional half wavelength spaced ULAs and also reduce mutual coupling effects. Likewise the considered scenario is most likely to occur in radars and sonars.
Perspectives
Writing this paper has been a great source of motivation for me as it’s my first ever article in any journal. This work provided my the opportunity to have compelling discussions with my co-authors, that effectively played its role in finalizing the manuscript. We hope our work serves as a good reference for academic research.
Tanveer Ahmed
Nanjing University of Aeronautics and Astronautics
Read the Original
This page is a summary of: Direction of arrival estimation for coprime electromagnetic vector sensor arrays via minimum distance criterion based on PARAFAC analysis , IET Radar Sonar & Navigation, September 2018, the Institution of Engineering and Technology (the IET),
DOI: 10.1049/iet-rsn.2018.5155.
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