Near-Field Pattern Synthesis for Sparse Focusing Antenna Arrays Based on Bayesian Compressive Sensing and Convex Optimization

• Published in: IEEE transactions on antennas and propagation Vol. 66; no. 10; pp. 5249 - 5257
• Main Authors: Huang, Zi Xuan, Cheng, Yu Jian
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.10.2018; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Antenna arrays; Antennas; Bayes methods; Bayesian analysis; Bayesian compressive sensing (BCS); Compressed sensing; Computational geometry; Computer simulation; Convex analysis; convex optimization; Convexity; Couplings; Excitation; Finite element analysis; Focusing; Layouts; Microwave antenna arrays; near-field beam shaping; Optimization; Sidelobes; sparse array; Synthesis
• ISSN: 0018-926X; 1558-2221
• DOI: 10.1109/TAP.2018.2860044

An effective method based on Bayesian compressive sensing (BCS) and convex optimization for near-field sparse array synthesis is presented in this paper. An algorithm to generate reference-shaped beams in the near-field region with controllable sidelobe levels is first proposed. Then, the multitask BC is modified and generalized to synthesize a near-field sparse array radiating a desired near-field pattern with the co-polarization component. After that, a postprocessing of the final array excitation is employed to put constraints on the minimum element spacing to make the sparse layout practicable. The degradation of the near-field pattern is mitigated through reestimating the array excitation by a convex optimization. Three numerical examples show the effectiveness of the proposed method with more than 50% of elements saved compared to the uniformly distributed layout. The comparison to the result obtained by a full-wave simulator FEKO is also presented to demonstrate the validity of this method considering strong antenna mutual couplings.