@inproceedings{11832,
  abstract     = {{In this paper we propose an approach to retrieve the absolute geometry of an acoustic sensor network, consisting of spatially distributed microphone arrays, from reverberant speech input. The calibration relies on direction of arrival measurements of the individual arrays. The proposed calibration algorithm is derived from a maximum-likelihood approach employing circular statistics. Since a sensor node consists of a microphone array with known intra-array geometry, we are able to obtain an absolute geometry estimate, including angles and distances. Simulation results demonstrate the effectiveness of the approach.}},
  author       = {{Jacob, Florian and Schmalenstroeer, Joerg and Haeb-Umbach, Reinhold}},
  booktitle    = {{38th International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2013)}},
  issn         = {{1520-6149}},
  keywords     = {{Geometry calibration, microphone arrays, position self-calibration}},
  pages        = {{116--120}},
  title        = {{{DoA-Based Microphone Array Position Self-Calibration Using Circular Statistic}}},
  doi          = {{10.1109/ICASSP.2013.6637620}},
  year         = {{2013}},
}

@inproceedings{11833,
  abstract     = {{In this paper we propose an approach to retrieve the geometry of an acoustic sensor network consisting of spatially distributed microphone arrays from unconstrained speech input. The calibration relies on Direction of Arrival (DoA) measurements which do not require a clock synchronization among the sensor nodes. The calibration problem is formulated as a cost function optimization task, which minimizes the squared differences between measured and predicted observations and additionally avoids the existence of minima that correspond to mirrored versions of the actual sensor orientations. Further, outlier measurements caused by reverberation are mitigated by a Random Sample Consensus (RANSAC) approach. The experimental results show a mean positioning error of at most 25 cm even in highly reverberant environments.}},
  author       = {{Jacob, Florian and Schmalenstroeer, Joerg and Haeb-Umbach, Reinhold}},
  booktitle    = {{International Workshop on Acoustic Signal Enhancement (IWAENC 2012)}},
  keywords     = {{Unsupervised, geometry calibration, microphone arrays, position self-calibration}},
  title        = {{{Microphone Array Position Self-Calibration from Reverberant Speech Input}}},
  year         = {{2012}},
}