  The paper considers sparse array design for receive beamforming achieving
maximum signal-to-interference plus noise ratio (MaxSINR) for both single point
source and multiple point sources, operating in an interference active
environment. Unlike existing sparse design methods which either deal with
structured environment-independent or non-structured environment-dependent
arrays, our method is a hybrid approach and seeks a full augumentable array
that optimizes beamformer performance. This approach proves important for
limited aperture that constrains the number of possible uniform grid points for
sensor placements. The problem is formulated as quadratically constraint
quadratic program (QCQP), with the cost function penalized with weighted
l_1-norm squared of the beamformer weight vector. Simulation results are
presented to show the effectiveness of the proposed algorithms for array
configurability in the case of both single and general rank signal correlation
matrices. Performance comparisons among the proposed sparse array, the commonly
used uniform arrays, arrays obtained by other design methods, and arrays
designed without the augmentability constraint are provided.
