Optimized Design for Sparse Arrays in 3-D Imaging Sonar Systems Based on Perturbed Bayesian Compressive Sensing

Sparse planar array designs significantly reduce the hardware complexity and computational overhead in phased array 3-D imaging sonar systems. Recently, Bayesian compressive sensing (BCS) theory has been applied for synthesizing maximally sparse arrays, in which case, the problem is formulated as a...

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Veröffentlicht in:	IEEE sensors journal 2020-05, Vol.20 (10), p.5554-5565
Hauptverfasser:	Lin, Zhenwei, Chen, Yaowu, Liu, Xuesong, Jiang, Rongxin, Shen, Binjian, Xin-Xin, Guo
Format:	Artikel
Sprache:	eng
Schlagworte:	Antenna arrays Bayes methods Bayesian analysis Bayesian compressed sensing Computational geometry convex optimization Convexity Design optimization element merging Imaging Merging Pattern matching phased array 3-D imaging sonar system Phased arrays position perturbation Sensor arrays Sonar sparse planar array Synthesis Taylor series Three dimensional imaging
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