Near-field array shape calibration

• Published in: 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) pp. 2564 - 2567
• Main Authors: Wan, Shuang, Chung, Pei-Jung, Mulgrew, Bernard
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.05.2011
• Subjects: Arrays; Calibration; DDL; Loading; Near field; PSO; Sensors; Shape; Signal to noise ratio; Unified modeling language
• ISBN: 9781457705380; 1457705389
• ISSN: 1520-6149
• DOI: 10.1109/ICASSP.2011.5947008

In the important domain of array shape calibration, the near-field case poses a challenging problem due to the array response complexity induced by the range effect. In this paper, near-field calibration is carried out using an unconditional maximum likelihood (UML) estimator. Its objective function is optimized by the particle swarm optimization (PSO) algorithm. A new technique, decaying diagonal loading (DDL) is proposed to enhance the performance of PSO at high signal-to-noise ratio (SNR) by dynamically lowering it, based on the counter-intuitive observation that the global optimum of the UML objective function is more prominent at lower SNR. UML estimator offers Cramér-Rao bound (CRB)-attaining accuracy. The direct optimization by PSO without approximation makes the estimator applicable to the entire near-field. In addition, PSO is free of the initialization problem from which the local optimization algorithms suffer. Numerical simulations demonstrate the CRB-attaining results at SNR as high as 60 dB.