A cumulant-based lattice algorithm for multichannel adaptive filtering is proposed in this paper. Proposed algorithm takes into account the advantages of higer-order statistics, that is, improvement of estimation accuracy, blindness to colored Gaussian noise and the possibility to estimate the nonminimum-phase system etc. Without invoking the Instrumental Variable () method as used in other papers [1], [2], the algorithm is derived directly from the recursive pseudo-inverse matrix. The behavior of the algorithm is illustrated by numerical examples.

A high resolution iterative algorithm for estimating the direction-of-arrival of multiple wide band sources is proposed in this paper. For equally spaced array structure, two Unitary Transform based approaches are proposed in frequency domain for signal subspace processing in both coherent multipath and incoherent environment. Given a priori knowledge of the initial estimates of DOA, with proper spatial prefiltering to separate multiple groups of closely spaced sources, our proposed algorithm is shown to have high resolution capability even in coherent multipath environment without reducing the angular resolution, compared with the use of subarray. Compared with the conventional algorithm, the performance by the proposed algorithm is shown by the simulations to be improved under low Signal to Noise Ratio (SNR) while the performance is not degraded under high SNR. Moreover the computation burden involved in the eigencomputation is largely reduced by introducing the Pesudo-Hermitian matrix approximation.