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dc.contributor.advisorChung, Pei-Jung
dc.contributor.advisorMulgrew, Bernard
dc.contributor.authorWan, Shuang
dc.date.accessioned2011-05-30T15:33:14Z
dc.date.available2011-05-30T15:33:14Z
dc.date.issued2011
dc.identifier.urihttp://hdl.handle.net/1842/4902
dc.description.abstractThe subject of this thesis is the development of parametric methods for the calibration of array shape errors. Two physical scenarios are considered, the online calibration (self-calibration) using far-field sources and the offline calibration using near-field sources. The maximum likelihood (ML) estimators are employed to estimate the errors. However, the well-known computational complexity in objective function optimization for the ML estimators demands effective and efficient optimization algorithms. A novel space-alternating generalized expectation-maximization (SAGE)-based algorithm is developed to optimize the objective function of the conditional maximum likelihood (CML) estimator for the far-field online calibration. Through data augmentation, joint direction of arrival (DOA) estimation and array calibration can be carried out by a computationally simple search procedure. Numerical experiments show that the proposed method outperforms the existing method for closely located signal sources and is robust to large shape errors. In addition, the accuracy of the proposed procedure attains the Cram´er-Rao bound (CRB). A global optimization algorithm, particle swarm optimization (PSO) is employed to optimize the objective function of the unconditional maximum likelihood (UML) estimator for the farfield online calibration and the near-field offline calibration. 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. Numerical simulations demonstrate that the UML estimator optimized by PSO with DDL is optimally accurate, robust to large shape errors, and free of the initialization problem. In addition, the DDL technique is applicable to a wide range of array processing problems where the UML estimator is employed and can be coupled with different global optimization algorithms.en
dc.language.isoenen
dc.publisherThe University of Edinburghen
dc.relation.hasversionP.-J. Chung and S. Wan, “Array self-calibration using sage algorithm,” in proc. 5th IEEE Sensor Array and Multichannel Signal Processing Workshop, SAM 2008, Darmstadt, Germany, July 2008, pp. 165 – 169.en
dc.subjectsensor arrayen
dc.subjectcalibrationen
dc.titleParametric array calibrationen
dc.typeThesis or Dissertationen
dc.type.qualificationlevelDoctoralen
dc.type.qualificationnamePhD Doctor of Philosophyen


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