Fast subspace methods for radar applications
Ulrich R. O. Nickel · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1997
Some problems of subspace methods are demonstrated by the two principle radar applications: resolution enhancement and interference suppression. We show that for real data a critical problem of subspace methods is the definition of the signal subspace. Channel errors result in a leakage of signal power into the noise eigenvalues. For resolution enhancement the optimum signal subspace dimension is close to the dimension without errors, because by this choice error effects can be reduced. A performance comparison of some current criteria to determine the subspace dimension is given. For interference suppression the error/leakage subspace must be included in the subspace. Real data experiments show, that projection methods are sensitive to the choice of the dimension of the jammer subspace. For this application 'weighted projections' show a much better performance. These 'weighted projections' can be effectively constructed from eigenvector-free subspace estimation methods.