Experimental Antenna Array Calibration with ADAptive LInear Neuron (ADALINE) Network
Hugo Bertrand, Dominic Grenier, Sébastien Roy · 2006
It is well known that to perform accurate Direction of Arrival (DOA) estimation using algorithms like MUSIC (MUltiple SIgnals Classification), antenna array data must be calibrated to match the theoretical model upon wich DOA algorithms are based. This paper presents experimental measurements obtained with a linear antenna array and proposes a novel calibration technique based on artificial neural networks trained with experimental and theoretical steering vectors. In this context, the performance of a type of neural network - ADAptive LInear Neuron (ADALINE) network - is assessed and then compared with another calibration technique, thus demonstrating that the proposed technique works well while being very simple to implement.