Title :
Sustainable Kalman Filteing of Nonlinear Population Dynamics with Applications to GPS Residual Evaluation
Author_Institution :
Fac. of Inf. Sci. & Technol., Osaka Inst. of Technol., Hirakata
Abstract :
Being intended for in situ adaptation of self-location processes by using GPS, a mathematical model of pointing residual is considered from the view point of electro-chemical complexity in the ionosphere. The model is implemented by sustainable Kalman filter generating admissible estimate under noisy observations. Guided by the Volterra´s principle, the estimatable model is adapted to observed positioning residual. Through experimental studies, adaptation scheme was verified to restore ionospheric term of positioning residual
Keywords :
Gaussian processes; Global Positioning System; Kalman filters; Markov processes; geophysical signal processing; ionospheric techniques; GPS residual evaluation; GPS signal processing; Volterra principle; ionosphere electro-chemical complexity; mathematical model; nonlinear population dynamics; sustainable Kalman filtering; Filtering; Fluctuations; Global Positioning System; Ionization; Ionosphere; Kalman filters; Layout; Signal analysis; Signal processing; Vehicle dynamics; Estimatable Model; GPS Residual; Ionosphere Instability; Sustainable Kalman Filtering;
Conference_Titel :
SICE-ICASE, 2006. International Joint Conference
Conference_Location :
Busan
Print_ISBN :
89-950038-4-7
Electronic_ISBN :
89-950038-5-5
DOI :
10.1109/SICE.2006.315215
