SPATIAL BLOCKING FILTER DERIVATIVE CONSTRAINTS FOR THE GENERALIZED SIDELOBE CANCELER AND MUSIC

This paper presents a new approach to spatial derivative constraints f or the generalized sidelobe canceller (GSC), Spatial derivative constr aints have been applied to linearly constrained minimum variance beamf ormers to reduce the sensitivity to steering error, Earlier approaches to this problem constrained derivatives of the beamformer power and p hase response, leading to beamformer performance that depended on the coordinate reference location of the array. Current approaches constra in only the beamformer power response, eliminating the problem with ph ase dependence. However, nonlinear minimization is required in order t o solve for the linear constraint equations. An alternative approach f or the GSC, which is presented in this paper, is to use derivative con straints to flatten the null of the spatial blocking filter power resp onse, Thus, for a small steering error, the desired signal is still bl ocked from the noise cancelling filter, and the GSC output is unaffect ed by the steering error, These derivative constraints can be used wit h wideband array calibration, leading to effective performance in the presence of array errors, This same approach to derivative constraints can be used in other applications involving spatial blocking filters, such as the constrained MUSIC direction finding algorithm to give rob ustness against direction error of the known signal subspace.