A flexible, numerically robust array processing algorithm and its relationship to the givens transformation

The development of systolic array processors is very important for real-time adaptive array processing applications. In this paper a numerically robust algorithm, based on the modified Gram-Schmidt (MGS) method, is presented. The algorithm can be efficiently realized using a systolic architecture and is capable of handling both exponential and finite memory windows in order to cope with time-varying data. Finally, the relation of these algorithms to similar schemes based on the Given´s transformation is investigated.