Fechar
Metadados

@MastersThesis{Leite:2019:SiNaIn,
               author = "Leite, Leonardo Kameyama de Castro",
                title = "Sistema de navega{\c{c}}{\~a}o inercial baseado na 
                         integra{\c{c}}{\~a}o de uma IMU de classe t{\'a}tica com 
                         receptor GPS",
               school = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                 year = "2019",
              address = "S{\~a}o Jos{\'e} dos Campos",
                month = "2019-03-28",
             keywords = "Navega{\c{c}}{\~a}o auxiliada, navega{\c{c}}{\~a}o inercial, 
                         autoalinhamento grosseiro, filtro de kalman cubature, aided 
                         inertial navigation, inertial navigation, coarse self-alignment, 
                         cubature Kalman filter.",
             abstract = "Esta disserta{\c{c}}{\~a}o tem como objetivo apresentar um 
                         procedimento de integra{\c{c}}{\~a}o de informa{\c{c}}{\~o}es 
                         de acelera{\c{c}}{\~a}o e de taxa angular de uma unidade de 
                         medida inercial (UMI) de classe t{\'a}tica, {\`a}s medidas de 
                         uma massa de dados oriunda de um experimento real, emuladas como 
                         de um receptor GPS. Para tanto, foram aplicados m{\'e}todos de 
                         autoalinhamento grosseiro, algoritmo de navega{\c{c}}{\~a}o 
                         puramente inercial e filtro de kalman cubature. Esta 
                         constru{\c{c}}{\~a}o foi demonstrada atrav{\'e}s do 
                         detalhamento de equa{\c{c}}{\~o}es de navega{\c{c}}{\~a}o 
                         inercial utilizadas para integrar movimento e atitude de um 
                         sistema com sensores inerciais solid{\'a}rios (strapdown); 
                         m{\'e}todos de autoalinhamento grosseiro cl{\'a}ssico (TRIAD) e 
                         novo (ON-TRIAD); m{\'e}todos de filtragem de kalman cl{\'a}ssica 
                         e o chamado kalman cubature. Foi feita a compara{\c{c}}{\~a}o do 
                         resultado da implementa{\c{c}}{\~a}o da navega{\c{c}}{\~a}o 
                         puramente inercial utilizando o autoalinhamento TRIAD contra a o 
                         resultado da implementa{\c{c}}{\~a}o da navega{\c{c}}{\~a}o 
                         puramente inercial utilizando o autoalinhamento ON-TRIAD. 
                         Tamb{\'e}m foi feita a implementa{\c{c}}{\~a}odo algoritmo 
                         navega{\c{c}}{\~a}o inercial auxiliado por GPS utilizando filtro 
                         de kalman cubature. ABSTRACT: The objective of this work is to 
                         present a procedure for integration of information from 
                         acceleration and angular rates, stemming from a tactical grade 
                         inertial measurement unit (IMU), with the measurement from a real 
                         experiment data mass emulated as GPS receiver. For this purpose, 
                         there were applied methods of coarse self-alignment, inertial 
                         navigation and cubature kalman filter. This framework was 
                         demonstrated with the description of detailed inertial navigation 
                         equations used to integrate attitude and movement from a strapdown 
                         inertial system; classic TRIAD and new ON-TRIAD coarse 
                         self-alignment methods; and the stochastic method of kalman filter 
                         and cubature kalman filter. After development and implementation 
                         of the algorithms, it has been made the comparsion between a pure 
                         inertial navigation algorithm with coarse selfalignment performed 
                         by TRIAD and ON-TRIAD. Also, the algorithm of inertial navigation 
                         aided with GPS using cubature kalman filter has been made.",
            committee = "Ricci, Mario Cesar (presidente) and Kuga, H{\'e}lio Koiti 
                         (orientador) and Carrara, Valdemir and Santos, Davi Antonio dos",
         englishtitle = "Inertial navigation system based from tactical class IMU and GPS 
                         receptor integration",
             language = "pt",
                pages = "112",
                  ibi = "8JMKD3MGP3W34R/3T2LU62",
                  url = "http://urlib.net/rep/8JMKD3MGP3W34R/3T2LU62",
           targetfile = "publicacao.pdf",
        urlaccessdate = "30 nov. 2020"
}


Fechar