Reduced-Rank Interference Suppression for GPS Systems based on Adaptive Basis-Function Approximation

In this paper, we develop a novel reduced-rank space-time adaptive processing (STAP) algorithm for interference suppression in GPS receivers. The proposed algorithm is based on the least-squares (LS) criterion and consists of a selected sets of basis functions and an adaptive reduced-rank filter. Compared to traditional reduced-rank techniques, which employ a statistical approach to design the projection matrix, the proposed scheme works on an instantaneous basis, selecting the best suited set of basis functions at each time instant to minimize the squared error. An adaptive algorithm based on recursive least-squares (RL) is derived for its efficient implementation. Simulations in a GPS system show that, compared to existing reduced-rank and full-rank algorithms, the proposed algorithm presents a much lower computational complexity and remarkably better performance.