We develop parametric modeling and estimation methods for STAP data based on the results of the 2-D Wold-like decomposition. It is shown that the same parametric model that results from the 2-D Wold-like orthogonal decomposition naturally arises as the physical model in the problem of space-time processing of airborne radar data. This correspondence is exploited to derive a computationally efficient parametric partially adaptive detection algorithm. We prove that it is sufficient to estimate only the spectral support parameters of each interference component in order to obtain a projection matrix onto the subspace orthogonal to the interference subspace. The proposed partially adaptive parametric processing algorithm employs this property. The proposed parametric interference mitigation procedure can be applied when only the information in a single range gate is available, thus achieving high performance gain when the data in the different range gates cannot be assumed stationary.
|Number of pages||4|
|Journal||Proceedings - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing|
|State||Published - 1 Jan 2002|