Multidimensional Digital Signal Estimation Using Kalman’s Theory for Computer-Aided Applications
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Fecha
2004
Autores
Villalón-Turrubiates, Iván E.
Andrade-Lucio, José A.
Ibarra-Manzano, Óscar G.
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Editor
International Conference on Computing, Communications and Control Technologies (CCCT)
Resumen
Descripción
In this paper, we analyze the Multidimensional Kalman Algorithm to estimate a signal corrupted by white Gaussian noise. Because the theory provide a good solution to the problem with a large number of signals, we developed an algorithm for three-dimensional Kalman filtering applied to the positioning problem (latitude, altitude and longitude) of a stationary object based on GPS signals. This application was selected because the incoming signals of the GPS encounters some noise on its way to the receiver, which is originated from different types of sources, the consequences are that the received signals are noisy, therefore inaccurate. The signals are digitally processed, and the implementation may be carried out on a computer-aided system for a specific application.
Palabras clave
Signal Processing, Kalman Algorithm, Estimation Theory, Global Positioning System, Digital Filtering
Citación
Ivan E. Villalon-Turrubiates, Jose A. Andrade-Lucio, Oscar G. Ibarra-Manzano, “Multidimensional Digital Signal Estimation Using Kalman’s Theory for Computer-Aided Applications”, in Proceedings of the International Conference on Computing, Communications and Control Technologies (CCCT), Austin EE.UU., 2004, pp. 48-53.