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Abstract
The flexibility needed to construct DoA estimators that can be used with rotating arrays subject to rapid variations of the signal frequency is offered by the stochastic maximum likelihood approach. Using a combination of analytic methods and Monte Carlo simulations, we show that for low and moderate source correlations the stochastic maximum likelihood estimator that assumes noncorrelated sources has accuracy comparable to the estimator that includes the correlation coefficient as one of the parameters. We propose several fast approximations of the stochastic maximum likelihood estimator and compare their accuracy with the Cramer-Rao lower bound. We also discuss the model order selection problem for the binary- and multiple-hypotheses cases.
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- Copyright (2020 IEEE)
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- Category:
- Articles
- Type:
- artykuły w czasopismach
- Published in:
-
IEEE TRANSACTIONS ON SIGNAL PROCESSING
no. 68,
pages 5219 - 5229,
ISSN: 1053-587X - Language:
- English
- Publication year:
- 2020
- Bibliographic description:
- Meller M., Stawiarski K.: On DoA estimation for rotating arrays using stochastic maximum likelihood approach// IEEE TRANSACTIONS ON SIGNAL PROCESSING -Vol. 68, (2020), s.5219-5229
- DOI:
- Digital Object Identifier (open in new tab) 10.1109/tsp.2020.3022207
- Verified by:
- Gdańsk University of Technology
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