Abstract
We study the blind calibration problem of uniform linear arrays of acoustic vector sensors for narrowband Gaussian signals, and propose an improved, asymptotically optimal blind calibration scheme. Following recent work by Ramamohan et al., we exploit the special (block-Toeplitz) structure of the underlying signals' spatial covariance matrix. However, we offer a substantial improvement over their ordinary Least Squares (LS)-based approach: Using asymptotic approximations we obtain Optimally-Weighted LS estimates of the sensors' gains and phases offsets. We show via simulations that our estimates exhibit near-optimal performance, with improvements reaching more than an order of magnitude in the mean squared estimation errors of the calibration parameters, as well as in directions of-arrival estimation.
Original language | English |
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Title of host publication | 2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020 - Proceedings |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 4677-4681 |
Number of pages | 5 |
ISBN (Electronic) | 9781509066315 |
DOIs | |
State | Published - May 2020 |
Externally published | Yes |
Event | 2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020 - Barcelona, Spain Duration: 4 May 2020 → 8 May 2020 |
Publication series
Name | ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings |
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Volume | 2020-May |
ISSN (Print) | 1520-6149 |
Conference
Conference | 2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020 |
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Country/Territory | Spain |
City | Barcelona |
Period | 4/05/20 → 8/05/20 |
Bibliographical note
Publisher Copyright:© 2020 IEEE.
Keywords
- Acoustic vector sensor
- blind calibration
- optimally-weighted least squares.
- uniform linear array