Parallel and adaptive high-resolution direction finding

Recently the new class of so-called subspace methods for high-resolution direction finding has received a great deal of attention in the literature. When a real-time implementation is aimed at, the computational complexity involved is known to represent a serious impediment. In this paper, an ESPRIT-type algorithm is developed, which is fully adaptive and therefore particularly suited for real-time processing. Furthermore, a systolic array is described, which allows the processing of incoming data at a rate which is independent of the problem size. The algorithm is based on orthogonal transformations only. Estimates are computed for the angles of arrival, as well as for the source signals. Our aim is not so much to develop yet another ESPRIT-type algorithm but rather to show that it is indeed possible to develop an algorithm that is fully parallel and adaptive. This is something that has not been done before