Date of Award


Document Type


Degree Name

Doctor of Philosophy (PhD)


Department of Electrical and Computer Engineering

First Advisor

Meir Pachter, PhD


Multipath effects are a source of error degrading the accuracy of DGPS signal processing. The statistical models of multipath are determined by user location and, in addition are time varying. There is no unified statistical model for the multipath signal. Therefore the solution of the multipath problem using statistical models is difficult. This research introduces a new estimator that can detect the presence of multipath, can determine the unknown number of multipath components and can estimate multipath parameters in the GPS receiver (time delay and attenuation coefficients). Furthermore the multipath signal parameters are estimated at any instant of observation. The new estimator is based on maximum likelihood estimation applied to multiple observations of a linear model (regression form) of the received signal. In addition, the estimator is based on a recursive deployment of the multipath time delay. An improvement is achieved to the accuracy of multipath estimates at a low signal-to-noise level by applying Kalman filtering as a cascaded estimator. Kalman filtering application can be considered as an important tool for separating the direct path signal from multipath in noise. This dissertation also includes the design of new modified tracking loops endowed with the mentioned estimator: a modified Phase Lock Loop (PLL) for carrier tracking and a modified Delay Locked-Loop (DLL) in the code tracking. The modified loops can properly track the received direct signal in the presence of multipaths where the standard tracking loops are disabled. Simulations of the standard and the modified loops are presented. Tracking and performance in noise are investigated and a future work is suggested.

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