Joint DOA and Fundamental Frequency Estimation Methods based on 2-D Filtering

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Resumé

It is well-known that filtering methods can be used for processing of signals in both time and space. This comprises, for example, fundamental frequency estimation and direction-of-arrival (DOA) estimation. In this paper, we propose two novel 2-D filtering methods for joint estimation of the fundamental frequency and the DOA of spatio-temporarily sampled periodic signals. The first and simplest method is based on the 2-D periodogram, whereas the second method is a generalization of the 2-D Capon method. In the experimental part, both qualitative and quantitative measurements show that the proposed methods are well-suited for solving the joint estimation problem. Furthermore, it is shown that the methods are able to resolve signals separated sufficiently in only one dimension. In the case of closely spaced sources, however, the 2-D Capon-based method shows the best performance.
OriginalsprogEngelsk
TidsskriftProceedings of the European Signal Processing Conference
Vol/bind2010
Sider (fra-til)2091-2095
ISSN2076-1465
StatusUdgivet - 2010
BegivenhedEuropean Signal Processing Conference 2010 - Aalborg, Danmark
Varighed: 23 aug. 201027 aug. 2010

Konference

KonferenceEuropean Signal Processing Conference 2010
LandDanmark
ByAalborg
Periode23/08/201027/08/2010

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Frequency estimation
Direction of arrival
Processing

Citer dette

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title = "Joint DOA and Fundamental Frequency Estimation Methods based on 2-D Filtering",
abstract = "It is well-known that filtering methods can be used for processing of signals in both time and space. This comprises, for example, fundamental frequency estimation and direction-of-arrival (DOA) estimation. In this paper, we propose two novel 2-D filtering methods for joint estimation of the fundamental frequency and the DOA of spatio-temporarily sampled periodic signals. The first and simplest method is based on the 2-D periodogram, whereas the second method is a generalization of the 2-D Capon method. In the experimental part, both qualitative and quantitative measurements show that the proposed methods are well-suited for solving the joint estimation problem. Furthermore, it is shown that the methods are able to resolve signals separated sufficiently in only one dimension. In the case of closely spaced sources, however, the 2-D Capon-based method shows the best performance.",
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Joint DOA and Fundamental Frequency Estimation Methods based on 2-D Filtering. / Jensen, Jesper Rindom; Christensen, Mads Græsbøll; Jensen, Søren Holdt.

I: Proceedings of the European Signal Processing Conference, Bind 2010, 2010, s. 2091-2095.

Publikation: Bidrag til tidsskriftKonferenceartikel i tidsskriftForskningpeer review

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AU - Jensen, Søren Holdt

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N2 - It is well-known that filtering methods can be used for processing of signals in both time and space. This comprises, for example, fundamental frequency estimation and direction-of-arrival (DOA) estimation. In this paper, we propose two novel 2-D filtering methods for joint estimation of the fundamental frequency and the DOA of spatio-temporarily sampled periodic signals. The first and simplest method is based on the 2-D periodogram, whereas the second method is a generalization of the 2-D Capon method. In the experimental part, both qualitative and quantitative measurements show that the proposed methods are well-suited for solving the joint estimation problem. Furthermore, it is shown that the methods are able to resolve signals separated sufficiently in only one dimension. In the case of closely spaced sources, however, the 2-D Capon-based method shows the best performance.

AB - It is well-known that filtering methods can be used for processing of signals in both time and space. This comprises, for example, fundamental frequency estimation and direction-of-arrival (DOA) estimation. In this paper, we propose two novel 2-D filtering methods for joint estimation of the fundamental frequency and the DOA of spatio-temporarily sampled periodic signals. The first and simplest method is based on the 2-D periodogram, whereas the second method is a generalization of the 2-D Capon method. In the experimental part, both qualitative and quantitative measurements show that the proposed methods are well-suited for solving the joint estimation problem. Furthermore, it is shown that the methods are able to resolve signals separated sufficiently in only one dimension. In the case of closely spaced sources, however, the 2-D Capon-based method shows the best performance.

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JF - Proceedings of the European Signal Processing Conference

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