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In this paper, we propose an active calibration algorithm to tackle both gain-phase errors and position perturbations. Unlike many other active calibration methods, which fix the array while changing the location of the source, our approach rotates the array but does not change the location of the source, and knowledge of the direction-of-arrival (DOA) of the far-field calibration source is not required. The superiority of the proposed method lies in the fact that measurement of the direction of a far-field calibration source is not easy to carry out, while measurement of the rotation angle via the proposed calibration strategy is convenient and accurate. To obtain the receiving data from different directions, the sensor array is rotated to three different positions with known rotation angles. Based on the eigen-decomposition of the data covariance matrices, we can use the direction of the auxiliary source to represent the gain-phase errors and position perturbations. After that, we estimate the DOA of the calibration source by a one-dimensional search. Finally, the sensor gain-phase errors and position perturbations are calculated by using the estimated direction of the calibration source. Simulations verify the effectiveness and performance of the algorithm.

- Publication
- IEICE TRANSACTIONS on Communications Vol.E104-B No.6 pp.639-646

- Publication Date
- 2021/06/01

- Publicized
- 2020/12/03

- Online ISSN
- 1745-1345

- DOI
- 10.1587/transcom.2020EBP3119

- Type of Manuscript
- PAPER

- Category
- Antennas and Propagation

Zheng DAI

Nanjing University of Science and Technology

Weimin SU

Nanjing University of Science and Technology

Hong GU

Nanjing University of Science and Technology

The copyright of the original papers published on this site belongs to IEICE. Unauthorized use of the original or translated papers is prohibited. See IEICE Provisions on Copyright for details.

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Zheng DAI, Weimin SU, Hong GU, "Sensor Gain-Phase Error and Position Perturbation Estimation Using an Auxiliary Source in an Unknown Direction" in IEICE TRANSACTIONS on Communications,
vol. E104-B, no. 6, pp. 639-646, June 2021, doi: 10.1587/transcom.2020EBP3119.

Abstract: In this paper, we propose an active calibration algorithm to tackle both gain-phase errors and position perturbations. Unlike many other active calibration methods, which fix the array while changing the location of the source, our approach rotates the array but does not change the location of the source, and knowledge of the direction-of-arrival (DOA) of the far-field calibration source is not required. The superiority of the proposed method lies in the fact that measurement of the direction of a far-field calibration source is not easy to carry out, while measurement of the rotation angle via the proposed calibration strategy is convenient and accurate. To obtain the receiving data from different directions, the sensor array is rotated to three different positions with known rotation angles. Based on the eigen-decomposition of the data covariance matrices, we can use the direction of the auxiliary source to represent the gain-phase errors and position perturbations. After that, we estimate the DOA of the calibration source by a one-dimensional search. Finally, the sensor gain-phase errors and position perturbations are calculated by using the estimated direction of the calibration source. Simulations verify the effectiveness and performance of the algorithm.

URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.2020EBP3119/_p

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@ARTICLE{e104-b_6_639,

author={Zheng DAI, Weimin SU, Hong GU, },

journal={IEICE TRANSACTIONS on Communications},

title={Sensor Gain-Phase Error and Position Perturbation Estimation Using an Auxiliary Source in an Unknown Direction},

year={2021},

volume={E104-B},

number={6},

pages={639-646},

abstract={In this paper, we propose an active calibration algorithm to tackle both gain-phase errors and position perturbations. Unlike many other active calibration methods, which fix the array while changing the location of the source, our approach rotates the array but does not change the location of the source, and knowledge of the direction-of-arrival (DOA) of the far-field calibration source is not required. The superiority of the proposed method lies in the fact that measurement of the direction of a far-field calibration source is not easy to carry out, while measurement of the rotation angle via the proposed calibration strategy is convenient and accurate. To obtain the receiving data from different directions, the sensor array is rotated to three different positions with known rotation angles. Based on the eigen-decomposition of the data covariance matrices, we can use the direction of the auxiliary source to represent the gain-phase errors and position perturbations. After that, we estimate the DOA of the calibration source by a one-dimensional search. Finally, the sensor gain-phase errors and position perturbations are calculated by using the estimated direction of the calibration source. Simulations verify the effectiveness and performance of the algorithm.},

keywords={},

doi={10.1587/transcom.2020EBP3119},

ISSN={1745-1345},

month={June},}

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TY - JOUR

TI - Sensor Gain-Phase Error and Position Perturbation Estimation Using an Auxiliary Source in an Unknown Direction

T2 - IEICE TRANSACTIONS on Communications

SP - 639

EP - 646

AU - Zheng DAI

AU - Weimin SU

AU - Hong GU

PY - 2021

DO - 10.1587/transcom.2020EBP3119

JO - IEICE TRANSACTIONS on Communications

SN - 1745-1345

VL - E104-B

IS - 6

JA - IEICE TRANSACTIONS on Communications

Y1 - June 2021

AB - In this paper, we propose an active calibration algorithm to tackle both gain-phase errors and position perturbations. Unlike many other active calibration methods, which fix the array while changing the location of the source, our approach rotates the array but does not change the location of the source, and knowledge of the direction-of-arrival (DOA) of the far-field calibration source is not required. The superiority of the proposed method lies in the fact that measurement of the direction of a far-field calibration source is not easy to carry out, while measurement of the rotation angle via the proposed calibration strategy is convenient and accurate. To obtain the receiving data from different directions, the sensor array is rotated to three different positions with known rotation angles. Based on the eigen-decomposition of the data covariance matrices, we can use the direction of the auxiliary source to represent the gain-phase errors and position perturbations. After that, we estimate the DOA of the calibration source by a one-dimensional search. Finally, the sensor gain-phase errors and position perturbations are calculated by using the estimated direction of the calibration source. Simulations verify the effectiveness and performance of the algorithm.

ER -