Duisburg, Universiẗat, Habil.-Schr., 2000.

The 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.

Zugl.: Braunschweig, Techn. Univ., Diss., 2007

Braunschweig, Techn. University, Diss., 2007.

No description available.

Denna rapport presenterar en metod som möjliggör bestämning av bredbandiga signalers infallsvinklar. Studien är gjord i Matlab där infallande signaler samplades med ett antal sensorer utplacerade ekvidistant på en rätlinje. Den samplade informationen viktades sedan med konstanter framtagna med en konvex optimeringsrutin för att bilda en vinkelberoende utsignal. Rutinerna testades för insignaler med ett få antal frekvenser och gav för alla testade insgnaler en mycket bra bestämmning av infallsvinklen. Studien visar även att det är möjligt att göra systemet mer robust mot störningar i sensorernas positioner genom att ställa kriterier på den konvexa optimerings rutinen.

Zugl.: Tübingen, Univ., Diss., 2009

This thesis summarizes ongoing work to develop low-cost, wireless, resonant sensor array that can be used to monitor corrosion in infrastructure systems. A magnetically coupled sensor array is presented and analyzed using circuit model. The array acts as a magneto-inductive waveguide and the impedance discontinuities caused by corrosion (or other defects) lead to reflection. The relationship between the relative position of defects and pass band characteristics is investigated, providing a technique to determine the location of targets. A configuration for increased sensitivity and a method for defect localization are presented. / text

Zugl.: Erlangen, Nürnberg, Universiẗat, Diss., 2009.

Techn. Universiẗat, Diss., 2003--Berlin.