Contributions to radio frequency indoorpositioning and through-the-wall mapping
Ano de defesa: | 2017 |
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Autor(a) principal: | |
Orientador(a): | |
Banca de defesa: | |
Tipo de documento: | Tese |
Tipo de acesso: | Acesso aberto |
Idioma: | eng |
Instituição de defesa: |
Universidade Federal do Rio de Janeiro
Brasil Instituto Alberto Luiz Coimbra de Pós-Graduação e Pesquisa de Engenharia Programa de Pós-Graduação em Engenharia Elétrica UFRJ |
Programa de Pós-Graduação: |
Não Informado pela instituição
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Departamento: |
Não Informado pela instituição
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País: |
Não Informado pela instituição
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Palavras-chave em Português: | |
Link de acesso: | http://hdl.handle.net/11422/6081 |
Resumo: | The first part of this work introduces a novel machine-learning based location engine aiming at improving floor identification accuracy in radio frequency (RF) multi-floor indoor positioning while preserving a low two-dimensional positioning error. The location engine also reduces the position fix computational complexity. A large database of RF samples was collected in a 13-storey building to evaluate the proposal. The second part of this work studies in detail radio tomographic imaging, also referred to as RF-based through-the-wall mapping (TWM). Four different reconstruction algorithms – two projective and two algebraic – are compared using a path-loss model corrupted by Rayleigh noise in a parallel-beam acquisition geometry. After that, the thesis proposes applying the Finite Element Method (FEM) to simulate several parallel-beam geometry RF TWM setups, providing a more accurate simulation model. The meshing parameters of the FEM model geometry have been optimized, enabling a significant computational cost reduction while preserving accuracy. Reconstruction of two floor maps is carried out using the FEM model with different sampling rates, operational frequencies, and antenna models. Finally, a multi-sensor circular acquisition geometry (MCG) is defined to reduce the time required to acquire the RF samples in comparison to the parallel-beam geometry. The MCG scheme is evaluated using the proposed FEM framework. |