Using matrix norms to estimate the direction of arrival of planar waves on an ULA |
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| Authors: | Rodrigo P Lemos Jonas A Kunzler Diego F Burgos B Mário J de Souza Hugo VL e Silva Yroá R Ferreira Edna L Flôres Oliver Sander |
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| Institution: | 1. Escola de Engenharia Elétrica, Mecânica e de Computação, UFG, Av. Universitária, Nº 1488, Goiânia, Goiás 74605-010, Brazil;2. Instituto de Matemática e Estatística, UFG - Campus Samambaia, Goiânia, Goiás 74001-970, Brazil;3. Instituto Federal de Educ. Ciência e Tecnol. de Goiás, IFG, Av. Pedro Ludovico s/n, Loteamento Reny Cury, Anápolis, Goiás 75131-500, Brazil;4. Agencia Nacional de Telecomunicações, ANATEL, Distrito Federal, Brasília 70070-940 Brazil;5. Faculdade de Engenharia Elétrica, UFU, Av. João Naves de Ávila, Nº 2121, Campus Santa Mônica, Uberlândia, Minas Gerais, Brazil;6. Institut fur Prozessdatenverarbeitung und Elektronik, KIT, Hermann-von-Helmholtz-Platz 1, Eggenstein-Leopoldshafen, Baden-Württemberg 76344, Germany |
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| Abstract: | SEAD method estimates the direction-of-arrival angles on an uniform linear array based on the difference between the two largest singular values, what is called differential spectrum. Although it presented an outstanding performance, the ability to indicate the source positions was not elucidated yet. Inspired by the differential spectrum formulation we derived a total differential spectrum and found out that the matrix norm induced by the vector 2-norm of a modified spatial covariance matrix can be used to estimate the direction-of-arrival of multiple plane waves. Indeed we show that matrix norms are estimators and we propose their use instead of the singular value decomposition in SEAD-based methods. We present a general mathematical expression in order to explicit the operating principles of the proposed methods. Consequently, we were able to explain how the relation between the arriving and the search angles produces the larger peaks on the differential spectrum. To evaluate the important role played by matrix norms, a thousand experiments were carried out. They showed that the proposed approach proved to be as accurate as the previous SEAD-based methods, while providing a significant reduction on runtime. It also outperformed well-established methods like MODEX regarding the estimation error. |
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| Keywords: | Corresponding author |
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