The MVDR beamformer for circular arrays

Abstract

The problem of space-time adaptive processing (STAP) using a circular array is considered. A key part of STAP is the estimation of the space-time covariance matrix of the received data. The conventional method of doing this can be shown to cause performance degradation at short ranges. We present a method based on steering vector interpolation to remedy this problem. The method applied linear transformations to the data from adjacent range cells. the transformed data are then used to form the sample covariance matrix. Numerical examples illustrate significant performance improvement when using the transformed rather than the original data.