Forwards-backwards averaging for adaptive beamforming and STAP

We investigate the use of forwards backwards (f/b) averaging for estimating the interference-only covariance matrix used for adaptive beamforming and space-time adaptive processing (STAP). We demonstrate that the estimation loss is reduced by the use of the extra samples available through f/b averaging, and in STAP a new type of f/b averaging can quadruple the number of samples available. Importantly, we present a new result which shows that unknown array manifold errors have little effect on the performance of f/b averaging. The gain from f/b averaging is demonstrated on data from the Mountaintop database