Performance of an Adaptive Array Processor Subjected to Time-Varying Interference

Abstract Array processors for passive detection of directional wide-band Signals are commonly used in sonar, seismic work, and radio astronomy. The performance of such processors is degraded by directional noise sources referred to as interferences and adaptive processors to eliminate the effect of interferences have been used for many years. The issue addressed in this paper is movement of the interference and the effect that this has on adaptive loop design. The processor considered in the paper is an array of adjustable FIR filters using the Widrow LMS algorithm to adjust the filter weights. Changes in interference patterns affect both the covariance matrix of the observed signal and the optimum weight vector. For the purposes of this paper the optimum weight vector is modelled as an independent-increment process. This model permits the rigorous derivation of the optimum adaptive-loop gain parameter and of worst-case performance. In general it is found. that interference movement results in two error components: a gradient-noise component and a tracking component. Increases in adaptive loop gain decrease the tracking component but increase the gradient-noise component. Thus for a given set of interference-motion statistics an optimum gain can be found.