THEORY OF SIGNAL SEPARATION USING ADAPTIVE ARRAYS

Signal separation using adaptive arrays is a new technique in array data processing. The model considered in this paper is that the array consists of N sensors and the number of signal sources, which are separated in spatial location, is M and M≤N. In the case of narrow band signal, the incident signal have the form
x(t)=u(t)cos2πf₀t-v(t)sin2πf₀t
By using the Hilbert transform, we obtain
\widehat x(t)=u(t)cos2πf₀t-v(t)sin2πf₀t
In terms of the conventional beamforming system, the directional bearing-angle matrix G is formed. And then by using a special implementation the inverse matrix G^-1 is derived. At last a matrix transform operate on the received signal such that the output signal is separable, i.e. each output channel have only one incident signal. In the case of wide band signal, the DFT of input signal or heterodyne are required. The block diagram of signal separation technique is given. Some important results of this technique is derived. The results of system simulation experiment in digital computer prove that this theory is effective.