A Hybrid Algorithm Solution for GPS Antenna Array Cynthia Junqueira 1,2 , Moisés V. Ribeiro 1 , João Marcos T. Romano 1 , Clodoaldo Lima 1 , João Batista Destro-Filho 1 State University of Campinas (UNICAMP) 1 - Campinas – SP- Brazil Aerospace Technical Center – Aeronautical and Space Institute 2 (CTA/IAE) – São José dos Campos -Brazil {Cynthia, mribeiro, romano, destro}@decom.fee.unicamp.br, moraes@dca.fee.unicamp.br BIOGRAPHY Cynthia Junqueira received the B.S. degree in Electrical Engineering from Faculty of Technology and Sciences and the M.Sc. degree from Aeronautic Technological Institute (ITA), Brazil, 1996. She is a researcher in Aerospace Technical Center (CTA/IAE), Brazil and since 1999, a Ph.D. student at UNICAMP. Her research interests include adaptive signal processing and antennas. Moisés Vidal Ribeiro received the B.S. degree in Electrical Engineering from the Federal University of Juiz de Fora (UFJF), 1999. Since August 1999 Moisés is a M.Sc. student at UNICAMP. His interests are Linear and non-linear adaptive signal processing, Sub-band Signal Processing, neural networks, multimedia signal processing and DSP implementations. João Marcos T. Romano received the B.S. and M.Sc. degree from UNICAMP and Ph.D. degree from University of Paris-XI in 1987. Since 1988, Dr. Romano joined the Communications Department of the Faculty of Electrical and Computer Engineering - UNICAMP, where he is now a full professor. He is the president of the Brazilian Communications Society for the 2000-2002 period. Clodoaldo Lima received the M.Sc. degree in Electrical Engineering from UNICAMP in 2000. Now he is a Ph.D. student at UNICAMP. His research interests concern neural network and genetic algorithms. J.B. Destro-Filho received the B. Eng. degree in 1991 and the M.Sc. degree in 1994 from the School of Electrical and Computer Engineering (FEEC), UNICAMP, Campinas, Brazil. He received the Ph.D. degree from the I3S Laboratory-CNRS, University of Nice-Sophia Antipolis, France, in 1998. Since 1999 he has been working as a postdoctoral researcher at the Communications Department, FEEC, UNICAMP, teaching undergraduate and postgraduate courses. His research interests include adaptive signal processing, high-order statistics, education and neuroscience. ABSTRACT This work addresses the applications of adaptive antenna arrays for GPS, in order to achieve a more accurate estimation of user position, as well as signal enhancement and interference cancellation. A hybrid algorithm solution for adaptive antenna array is proposed, which is based on a constrained adaptive algorithm, associated with a multilayer perceptron neural network. Two hybrid algorithms, using two kinds of constrained algorithms, are compared to each other and to the classical solutions. Simulations consider different realistic GPS situations, pointing out the effectiveness of the hybrid approach, in terms of lower computational burden, lower stead- state error and better radiation patterns with respect to the classical solutions. INTRODUCTION The Global Positioning System is important for a great variety of applications, including civil or military users. It enables real-time position, time and velocity accurate estimation, and possibility to use on a variety of platforms, 24 hours a day [1]. GPS signals are subject to several impairments, such as multipath, fading, tropospheric and ionospheric delays, power flutuactions due to scintillation, doppler effects, clock and receiver errors. On the other hand, adaptive antennas may be considered as emerging techniques, which play an