GPS Signal Tracking Using Maximum Likelihood Parameter Estimation

Donald E. Gustafson

Abstract:	This paper considers the use of maximum likelihood parameter estimation in GPS signal tracking. The specific problem considered is phase and frequency tracking in the presence of spurious modulation components. An example is GPS signal processing within a rotating reentry body with aft mounted antennas. The rotation induces unwanted modulation components on both signal amplitude and phase. The desire is to track and remove these components. The commonly used phaselock loop approach is not adequate since the disturbances are not specifically modeled. This is a nonlinear estimation problem, which is attacked here by posing it as a linear estimation problem with an unknown modulation parameter. The parameter is estimated using a maximum likelihood method in an architecture which uses two Kalman filters of similar structure, one for parameter estimation and one for state estimation. This architecture uncouples the state and parameter estimation processes and reduces the tendency to build up incorrect correlations in the estimator. The performance of the estimator is studied using a Monte Carlo simulation. Maximum likelihood results are superior to that of a second order phaselock loop and a non-adaptive fourth order Kalman filter.
Published in:	Proceedings of the 52nd Annual Meeting of The Institute of Navigation (1996) June 19 - 21, 1996 Royal Sonesta Hotel Cambridge, MA
Pages:	477 - 486
Cite this article:	Updated citation: Published in NAVIGATION: Journal of the Institute of Navigation
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