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Interlaced Kalman Filter

Gasparri, A., Panzieri, S., Pascucci, R, Ulivi, G. (2009). An interlaced Kalman filter for sensors networks localization. International Journal of Sensor Networks, 5(3), 164-172. doi 10.1504/ IJSNET.2009.026364... [Pg.17]

As shown in Equations (8), (9), (10), and (11), the state transition and the observation models depend linearly (or affinely) on their arguments. When removing these assumptions, IKF can be applied on the linearized system. In this way, the obtained interlaced filter is no more linear and is known in the literature as Interlaced Extended Kalman Filter (Glielmo, Setola, Vasca, 1999), which is largely applied to solve SLAM (Panzieri, Pascucci, Setola, 2005). [Pg.9]

Glielmo, L., Setola, R., Vasca, F. (1999). An interlaced extended Kalman filter. IEEE Transactions on Automatic Control, 44(8), 1546-1549. doi 10.1109/9.780418... [Pg.17]

Panzieri, S., Pascucci, R, Setola, R. (2006). Multirobot localisation using interlaced extended Kalman filter. In Proceedings of the lEEE/RSJ IROS 2006. Beijing, China IEEE Press. [Pg.17]

See other pages where Interlaced Kalman Filter is mentioned: [Pg.3]    [Pg.7]    [Pg.3]    [Pg.7]    [Pg.1]    [Pg.2]    [Pg.7]   
See also in sourсe #XX -- [ Pg.3 , Pg.7 ]



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