An Improved Blind Adaptive Beamforming CAB Algorithm Based on Fireworks Algorithm is Presented

Abstract

Adaptive beamforming is the core of array signal processing and has been widely used. It is to extract the desired signal by the difference of spatial spectrum between the received useful signal and the noise signal. With the rapid development of communication technology, various kinds of intentional or unintentional electromagnetic interference are also intensifying. In order to enable communication equipment to receive and receive useful signals correctly in various environments, the development of effective anti-jamming technology has become the focus of current research. Based on the in-depth study of adaptive beamforming technology and the need to transmit reference signals, it can be divided into non-blind and blind adaptive beamforming technologies. In this paper, aiming at the existing problems of several typical blind algorithms, an improved method is proposed. In practical applications, the performance of CAB algorithms will be drastically reduced or invalidated due to cyclic frequency errors. In order to effectively improve this disadvantage, this paper proposes a method of solving this problem by using swarm intelligence optimization algorithm, that is, using the fireworks algorithm of explosive search to optimize CAB algorithms. In this paper, the basic principle of the fireworks algorithm is introduced. With the help of the global optimization ability of the fireworks algorithm, the effect of cyclic frequency error on the performance of the CAB algorithm can be effectively solved. The simulation results verify the practicability and effectiveness of the improved algorithm.