GPS Anti-Jamming Technique Using Smart Antenna Systems

This paper presents a global positioning system (GPS) anti-jamming technique using a smart antenna system. In anti-jamming systems, adaptive array antennas are used to estimate the direction of signals arriving at the antenna and spatially filter the desired signal from the unwanted signals by adaptively controlling the direction of the maximum radiated beam.  In this study, the uniform linear array was used for the smart antenna configuration. The work compared the performance of non-blind adaptive algorithms with blind algorithms for adaptive beamforming. Non-blind adaptive algorithm using least mean square (LMS) algorithm and blind algorithm using constant modulus algorithm (CMA) was studied and implemented for adaptive beamforming while estimation of signal parameters via rotational invariance technique (ESPRIT) and multiple signal classification (MUSIC) algorithms were implemented for the direction of arrival (DOA) estimation. The effect of varying the number of elements in the antenna array and the required spacing between them was also investigated. Results of comparison carried out using numerical analysis showed that both algorithms performed well for the DOA estimation, with MUSIC algorithm producing a better direction of arrival spectrum with little or no minor peaks. For the beamforming, both LMS and CMA produced maximum radiation in the direction of the desired signal. LMS placed deeper nulls in the directions of interference with faster convergence and fewer errors as compared with CMA that presented errors and was able to suppress the interference to a minimal extent. It was also shown that as the number of elements in the array increases, a more directive beam and DOA spectrum is produced

Matrix Decomposition Methods for Efficient Hardware Implementation of DOA Estimation Algorithms: A Performance Comparison

Matrix operations form the core of array signal processing algorithms such as those required for direction of arrival (DOA) angle estimation of radio frequency signals incident on an antenna array. In this paper, we present a performance comparison of matrix decomposition methods for efficient FPGA hardware implementation of DOA estimation algorithms. These methods are very important in subspace-based DOA estimation algorithms as they are used for signal space extraction. DOA estimation algorithms employing LU, LDL, Cholesky, and QR decomposition methods are implemented on a Xilinx Virtex-5 FPGA. These DOA estimation algorithms are simulated in LabVIEW as well as experimentally validated in real-time on a prototype testbed constructed using Universal Software Radio Peripheral (USRP) Software Defined Radio (SDR) platform from National Instruments. Performance comparison of these algorithms is made in terms of resources consumption, computation speed, and estimation accuracy