Print Email Facebook Twitter Self-Calibration of Acoustic Scalar and Vector Sensor Arrays Title Self-Calibration of Acoustic Scalar and Vector Sensor Arrays Author Ramamohan, Krishnaprasad Nambur (Microflown Technologies, Arnhem) Chepuri, Sundeep Prabhakar (Indian Institute of Science India) Comesana, Daniel Fernandez (Microflown Technologies, Arnhem) Leus, G.J.T. (TU Delft Signal Processing Systems) Date 2023 Abstract In this work, we consider the self-calibration problem of joint calibration and direction-of-Arrival (DOA) estimation using acoustic sensor arrays. Unlike many previous iterative approaches, we propose solvers that can be readily used for both linear and non-linear arrays for jointly estimating the sensor gain, phase errors, and the source DOAs. We derive these algorithms for both the conventional element-space and covariance data models. We focus on sparse and regular arrays formed using scalar sensors as well as vector sensors. The developed algorithms are obtained by transforming the underlying non-linear calibration model into a linear model, and subsequently by using convex relaxation techniques to estimate the unknown parameters. We also derive identifiability conditions for the existence of a unique solution to the self-calibration problem. To demonstrate the effectiveness of the developed techniques, numerical experiments, and comparisons to the state-of-The-Art methods are provided. Finally, the results from an experiment that was performed in an anechoic chamber using an acoustic vector sensor array are presented to demonstrate the usefulness of the proposed self-calibration techniques. Subject AcousticsCalibrationDirection-of-arrival estimationManifoldsMeasurement uncertaintySensor arraysSignal processing algorithms To reference this document use: http://resolver.tudelft.nl/uuid:5b2a7880-d105-49df-9e84-e40bbb942bf6 DOI https://doi.org/10.1109/TSP.2022.3214383 Embargo date 2023-04-24 ISSN 1053-587X Source IEEE Transactions on Signal Processing, 71, 61-75 Bibliographical note Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public. Part of collection Institutional Repository Document type journal article Rights © 2023 Krishnaprasad Nambur Ramamohan, Sundeep Prabhakar Chepuri, Daniel Fernandez Comesana, G.J.T. Leus Files PDF Self_Calibration_of_Acous ... Arrays.pdf 2.27 MB Close viewer /islandora/object/uuid:5b2a7880-d105-49df-9e84-e40bbb942bf6/datastream/OBJ/view