Adaptive spatial domain forward-backward predictors for bearing estimation

Adaptive algorithms are proposed for computing the coefficients of spatial domain predictors. The method presented uses the least-mean-squares approach to compute the coefficients of the predictors realized by using the tapped-delay-line and the escalator structures. The predictors presented differ from the conventional ones in that the relevant weights are updated such that the sum of the mean-squared values of the forward and the backward prediction errors is minimized. Using the coefficients of such spatial domain predictors yields improved linear predictive spatial spectrums. The algorithms are applied to the problem of estimating incident angles of multiple narrowband signals received by a linear array of sensors. Simulation results demonstrating the performances of the proposed methods are presented