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The paper considers sparse array design for receive beamforming achievingmaximum signal-to-interference plus noise ratio (MaxSINR) for both single pointsource and multiple point sources, operating in an interference activeenvironment. Unlike existing sparse design methods which either deal withstructured environment-independent or non-structured environment-dependentarrays, our method is a hybrid approach and seeks a full augumentable arraythat optimizes beamformer performance. This approach proves important forlimited aperture that constrains the number of possible uniform grid points forsensor placements. The problem is formulated as quadratically constraintquadratic program (QCQP), with the cost function penalized with weightedl_1-norm squared of the beamformer weight vector. Simulation results arepresented to show the effectiveness of the proposed algorithms for arrayconfigurability in the case of both single and general rank signal correlationmatrices. Performance comparisons among the proposed sparse array, the commonlyused uniform arrays, arrays obtained by other design methods, and arraysdesigned without the augmentability constraint are provided.

Hybrid Sparse Array Beamforming Design for General Rank Signal Models