This paper presents a novel reduced-rank space–time adaptive processing (STAP) algorithm for interference suppression in global positioning system (GPS) receivers with low computational complexity for protection against the multipath and jamming interferences. The proposed STAP algorithm is based on the least-squares (LS) criterion to jointly optimize a projection matrix, which is used for dimensionality reduction, and the reduced-rank filter. The main novelties are the design of the projection matrix based on approximations of basis functions, the pattern matching between the projection matrix and the received data, and the derivation of a QR decomposition-based reduced-rank recursive LS algorithm for practical implementations. The proposed scheme works on an instantaneous basis, i.e. at each time instant, the most suitable pattern and the rank of the projection matrix are selected to reduce the dimensionality of the received data aiming at minimizing the squared error, while using an improved search algorithm to save the effort in finding the best projection matrix. Simulation results in a GPS system show that compared to existing reduced-rank and full-rank algorithms, the proposed algorithm has a much lower computational complexity, and remarkably better performance for interference suppression. Copyright © 2011 John Wiley & Sons, Ltd.
['Hui Xiao', 'Rodrigo C. de Lamare']
Reduced-rank space–time adaptive interference suppression for navigation systems based on QR decomposition and approximations of basis functions