Signal separation theory using adaptive arrays

Abstract

AbstractThe signal separation technique using adaptive arrays is a new area in array data processing. The model considered in this paper is that of an array consisting of N elements; the number of signal sources, which are separated in spatial location, is M and M ≥ N. In the case of narrow band signals, the pre‐envelope form of the incident signal can be obtained from the original signal and its Hilbert transform. The directional bearing‐angle matix G is formed in terms of the conventional beam‐forming system. By using a special implementation, the inverse matrix of G is derived. Finally, a matrix transform is operated on the received signal so that the output signal is separable, i.e. each output channel has only one incident signal. In the case of wide band signals, the DFT of the input signal or heterodyne is required. The block diagrams of the signal separation technique are given and some important results of this technique are derived. The results of system simulation experiments in digital computers prove that this theory is effective for separating signals.