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Bayesian In-Situ Calibration of Multiport Antennas for DoA Estimation: Theory and Measurements

Pöhlmann, Robert and Zhang, Siwei and Staudinger, Emanuel and Caizzone, Stefano and Dammann, Armin and Hoeher, Peter A. (2022) Bayesian In-Situ Calibration of Multiport Antennas for DoA Estimation: Theory and Measurements. IEEE Access, 10, pp. 37967-37983. IEEE - Institute of Electrical and Electronics Engineers. doi: 10.1109/ACCESS.2022.3164520. ISSN 2169-3536.

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The direction-of-arrival (DoA) of radio waves is used for many applications, e.g. the localization of autonomous robots and smart vehicles. Estimating the DoA is possible with a multiport antenna, e.g. an antenna array or a multi-mode antenna (MMA). In practice, DoA estimation performance decisively depends on accurate knowledge of the antenna response, which makes antenna calibration vital. As the antenna surroundings influence its response, it is necessary to measure the entire device with installed antenna to obtain the installed antenna response. Antenna calibration is often done in a dedicated measurement chamber, which can be inconvenient and costly, especially for larger devices. Thus, auto- and in-situ calibration methods aim at making antenna calibration in a measurement chamber redundant. However, existing auto- and in-situ calibration methods are restricted to certain antenna types and certain calibrations. In this paper, we propose a Bayesian in-situ calibration algorithm based on a maximum a posteriori (MAP) estimator, which is suitable for arbitrary multiport antennas. The algorithm uses received signals from a transmitter, noisy external DoA observations, takes multipath propagation into account and does not require synchronization. Furthermore, we take an estimation theoretic perspective and provide an in-depth theoretical discussion of in-situ antenna calibration in unknown propagation conditions based on Bayesian information and the Bayesian Cramér-Rao bound (BCRB). Extensive simulations show that the proposed algorithm operates close to the BCRB and the achieved DoA estimation performance asymptotically approaches the case of a perfectly known antenna response. Finally, we provide an experimental validation, where we calibrate the antenna on a robotic rover and evaluate the DoA estimation performance using measurement data. With the proposed in-situ antenna calibration algorithm, DoA estimation performance is considerably improved compared to using an antenna response obtained by simulation or in a measurement chamber.

Item URL in elib:https://elib.dlr.de/186087/
Document Type:Article
Title:Bayesian In-Situ Calibration of Multiport Antennas for DoA Estimation: Theory and Measurements
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Pöhlmann, RobertUNSPECIFIEDhttps://orcid.org/0000-0001-7362-9406UNSPECIFIED
Zhang, SiweiUNSPECIFIEDhttps://orcid.org/0000-0003-4390-458XUNSPECIFIED
Staudinger, EmanuelUNSPECIFIEDhttps://orcid.org/0000-0002-9601-2887UNSPECIFIED
Caizzone, StefanoUNSPECIFIEDhttps://orcid.org/0000-0002-9434-7368UNSPECIFIED
Dammann, ArminUNSPECIFIEDhttps://orcid.org/0000-0002-7112-1833UNSPECIFIED
Hoeher, Peter A.University of Kiel, Germanyhttps://orcid.org/0000-0003-3475-1710UNSPECIFIED
Date:4 April 2022
Journal or Publication Title:IEEE Access
Refereed publication:Yes
Open Access:Yes
Gold Open Access:Yes
In ISI Web of Science:Yes
Page Range:pp. 37967-37983
Publisher:IEEE - Institute of Electrical and Electronics Engineers
Keywords:Antenna calibration, array calibration, Cramér-Rao bound, direction-of-arrival estimation, multi-mode antenna
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Communication, Navigation, Quantum Technology
DLR - Research area:Raumfahrt
DLR - Program:R KNQ - Communication, Navigation, Quantum Technology
DLR - Research theme (Project):R - Swarm navigation
Location: Oberpfaffenhofen
Institutes and Institutions:Institute of Communication and Navigation
Institute of Communication and Navigation > Communications Systems
Deposited By: Pöhlmann, Robert
Deposited On:21 Apr 2022 09:52
Last Modified:29 Mar 2023 00:01

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