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MASTERS THESIS

Position Calibration of acoustic sensors and actuators on distributed general purpose computing platforms

Arrays of audio/video sensors and actuators (such as microphones, cameras, speakers and displays) along with array processing algorithms offer a rich set of new features for emerging multimedia applications. Until now, array processing was mostly out of reach for consumer applications perhaps due to significant costs of dedicated hardware and complexity of processing algorithms. On the other hand, several mobile computing and communication devices like laptops, PDAs and tablets are equipped with multiple audio/video sensors and actuators. An ad-hoc network of such devices can be used to form a distributed sensor network. A prerequisite for using distributed audio-visual I/O capabilities is to put the sensors and actuators into a common time and space.

This thesis focuses on providing a common space by automatically determining the relative 3D positions of audio sensors and actuators. A closed form approximate solution is derived, which is further refined by minimizing a non-linear error function. The formulation and solution accounts for the lack of temporal synchronization among different platforms. An approximate expression for the mean and covariance of the implicitly defined estimator is derived using the implicit function theorem and approximate Taylors' series expansion. The theoretical performance limits for the sensor positions are derived via the Cram\'{e}r-Rao bound and analyzed with respect to the number of sensors and actuators as well as their geometry. Extensive simulation results and the practical details of implementing our algorithms in a real-life system are discussed.