@Article{SilvaKugaZana:2015:NoLeSq,
               author = "Silva, William Reis and Kuga, H{\'e}lio Koiti and Zanardi, Maria 
                         Cec{\'{\i}}lia Franca de Paula Santos",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Universidade Federal 
                         do ABC (UFABC)}",
                title = "Nonlinear least squares method for gyros bias and attitude 
                         estimation using satellite attitude and orbit toolbox for matlab",
              journal = "Journal of Physics: Conference Series",
                 year = "2015",
               volume = "641",
                pages = "012005",
             keywords = "Nonlinear Least Squares, Attitude Estimation, Gyros drift.",
             abstract = "The knowledge of the attitude determination is essential to the 
                         safety and control of the satellite and payload, and this involves 
                         approaches of nonlinear estimation techniques. Here one focuses on 
                         determining the attitude and the gyros drift of a real satellite 
                         CBERS-2 (China Brazil Earth Resources Satellite) using simulated 
                         measurements provided by propagator PROPAT Satellite Attitude and 
                         Orbit Toolbox for Matlab. The method used for the estimation was 
                         the Nonlinear Least Squares Estimation (NLSE). The attitude 
                         dynamical model is described by nonlinear equations involving the 
                         Euler angles. The attitude sensors available are two DSS (Digital 
                         Sun Sensor), two IRES (Infra-Red Earth Sensor), and one triad of 
                         mechanical gyros. The two IRES give direct measurements of roll 
                         and pitch angles with a certain level of error. The two DSS are 
                         nonlinear functions of roll, pitch, and yaw attitude angles. Gyros 
                         are very important sensors, as they provide direct incremental 
                         angles or angular velocities. However gyros present several 
                         sources of error of which the drift is the most troublesome. 
                         Results show that one can reach accuracies in attitude 
                         determination within the prescribed requirements, besides 
                         providing estimates of the gyro drifts which can be further used 
                         to enhance the gyro error model.",
                  doi = "10.1088/1742-6596/641/1/012005",
                  url = "http://dx.doi.org/10.1088/1742-6596/641/1/012005",
                 issn = "1742-6588",
                label = "lattes: 7752228013890691 1 SilvaKugaZana:2015:NoLeSq",
             language = "en",
           targetfile = "1_silva5.pdf",
                  url = "http://dx.doi.org/10.1088/1742-6596/641/1/012005",
        urlaccessdate = "27 abr. 2024"
}