Hybrid Sparse Array Beamforming Design for General Rank Signal Models

• Published in: IEEE transactions on signal processing Vol. 67; no. 24; pp. 6215 - 6226
• Main Authors: Hamza, Syed Ali, Amin, Moeness G.
• Format: Journal Article
• Language: English
• Published: New York IEEE 15.12.2019; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Apertures; Array signal processing; Arrays; Beamforming; Computer simulation; Correlation analysis; Cost function; Fully augmentable array; Gain; Hybrid array; Interference; MaxSINR; Performance assessment; QCQP; Sensor arrays; Signal to noise ratio; Sparse arrays
• ISSN: 1053-587X; 1941-0476
• DOI: 10.1109/TSP.2019.2952052

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.