| Satellite-based navigation systems, especially Global Positioning System (GPS), havebeen widely used both in civilian and military field for positioning, navigation or otherposition related applications. However the GPS signal reaching to the users’ antennas isvery weak and easy to be jammed. Thus, the performance of location-based servicesprovided by GPS can be severely compromised by interference which can vary fromunintentional distortion due to multipath propagation to intentional noise sources(Jammer).It is primordial to develop proper mitigation techniques for robust, accurate andtrustworthy positioning. In this context, interference mitigation techniques utilizingantenna arrays has drawn more attention recently. Various adaptive array processingalgorithms have been reported in the literature. These algorithms, in a general view,exhibit a trade-off between performance and required computational complexity.This thesis presents on the one hand, the development of array processing algorithms forinterference mitigation. Two basic algorithms, Sample Matrix Inversion (SMI) andRecursive Least Squares (RLS) algorithms have been studied based on the number ofinterfering signals received, their power level as well as the direction thereof. Moreover,an idea based on the regularization technique has been use to develop a Robust RecursiveLeast Squares (R-RLS). It has been shown that, R-RLS algorithm provides betterperformance (higher output SINR, Deeper nulls, faster convergence time etc.) thanstandard RLS.On the other hand, the GPS link simulation has been constructed using Matlab in theinterest of verification of the validity of the improved algorithm. R-RLS successfullymitigated interference and the simulated GPS signal has been detected by the Acquisitionmodule of the GPS receiver. Furthermore, the proposed R-RLS algorithm is applied tothe real data (real GPS environment). Once more, interferences have been successfullymitigated and signal acquired. |
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