A pragmatic approach to adaptive antennas and space-time adaptive processing (STAP)

Summary form only given. In the conventional adaptive beamforming methodology typically weights are connected to each one of the antenna element in the array and the processing information is generated over time, as the correlation matrix of the data needs to be formed. Some of the problems associated with this procedure is that because of the formation of the covariance matrix and evaluation of its inverse it is difficult to carry it out in real time and its inverse may be computationally unstable if the signal to noise ratio is large. It is difficult to handle coherent multipaths in this methodology unless some additional processing is carried out. This article presents a novel methodology utilizing the direct data domain approach based on the spatial samples for the efficient computation of the adaptive weights in a phased array system. In this approach, the adaptive analysis is done on a snapshot-by-snapshot basis and therefore nonstationary environments can be handled quite easily including the coherent multipath environment. This is in contrast to conventional adaptive techniques where processing is done by taking the time averages as opposed to spatial averages. This approach is unlike the conventional statistical based techniques by eliminating the requirement of an interference covariance matrix and representing a rethinking of the entire conventional approach to adaptive processing. This approach provides greater flexibility in solving a wider class of problems at the expense of a slightly reduced number of degrees of freedom. Also in most adaptive processing the assumption that the target signal is coming from an exactly known direction will probably never be met in any real array. Or the adaptive array may be surveyed into location with small errors and thus the angle to the transmitter from the broadside of the array will be in error. Other applications of adaptive arrays will also have at least small errors in the direction of arrival of the desired s- gnal. This article presents methodologies to treat this signal cancellation problem through the main beam constraints. Examples are presented to illustrate the applicability of this methodology to a wide class of problems. Finally, it is shown how to extend this methodology to two-dimensions, namely space-time adaptive processing (STAP). An example is presented to illustrate the detection of a saberliner tracked by an airborne forward looking radar in the presence of land, urban and sea-clutter.