The object of adaptive filtering is to devise weights which will extract useful statistics when applied to the received voltages. Assuming that the sources are in the far field, a linear phase front is present due to the target. Since the geometry of the receiving array is known, we can subtract out any desired signal component from the received voltages. The remainder would consist of just noise and interference. This will be minimized, giving us the correct adaptive weights.
Matrix computations are highly parallelizable and can lead to real time applications.
With a direct data domain approach, the problems of statistical approaches have been bypassed. Non-homegeneities in the surrounding range cells are no longer an issue, since there is no need to estimate covariance matrices. Also, since there are no assumptions about the independence of the incoming signals, coherent repeat jammers and multipath scan also be handled. In Image And Signal Processing introduction Illustration of Adaptive Nulling for an airborne platform. All rights reserved.