Entropy based approach for direction-of-arrival estimation in Gaussian and non-Gaussian correlated noise

Yifeng Zhou; Henry Leung; Patrick C. Yip; Q. Jin

Entropy based approach for direction-of-arrival estimation in Gaussian and non-Gaussian correlated noise

Yifeng Zhou^*, Henry Leung, Patrick C. Yip, Q. Jin

^*Corresponding author for this work

Research output: Contribution to journal › Conference article › peer-review

Abstract

In this paper, we present an entropy based approach for DOA estimation in Gaussian and non-Gaussian environments. The DOA estimates are obtained by minimizing an entropy measure of the array data in the noise sub-space. We show that the entropy approach leads to the MAP algorithm under the Gaussian assumption. Under the non-Gaussian assumption, we apply the varimax norm as an information measure. An intuitive consistency analysis is also performed. Computer simulations are used to demonstrate the effectiveness of the proposed approach.

Original language	English
Pages (from-to)	3505-3508
Number of pages	4
Journal	ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume	5
Publication status	Published - 1997 Jan 1
Externally published	Yes
Event	Proceedings of the 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP. Part 1 (of 5) - Munich, Ger Duration: 1997 Apr 21 → 1997 Apr 24

ASJC Scopus subject areas

Software
Signal Processing
Electrical and Electronic Engineering

Cite this

Entropy based approach for direction-of-arrival estimation in Gaussian and non-Gaussian correlated noise. / Zhou, Yifeng; Leung, Henry; Yip, Patrick C. et al.
In: ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, Vol. 5, 01.01.1997, p. 3505-3508.

Research output: Contribution to journal › Conference article › peer-review

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AU - Jin, Q.

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N2 - In this paper, we present an entropy based approach for DOA estimation in Gaussian and non-Gaussian environments. The DOA estimates are obtained by minimizing an entropy measure of the array data in the noise sub-space. We show that the entropy approach leads to the MAP algorithm under the Gaussian assumption. Under the non-Gaussian assumption, we apply the varimax norm as an information measure. An intuitive consistency analysis is also performed. Computer simulations are used to demonstrate the effectiveness of the proposed approach.

AB - In this paper, we present an entropy based approach for DOA estimation in Gaussian and non-Gaussian environments. The DOA estimates are obtained by minimizing an entropy measure of the array data in the noise sub-space. We show that the entropy approach leads to the MAP algorithm under the Gaussian assumption. Under the non-Gaussian assumption, we apply the varimax norm as an information measure. An intuitive consistency analysis is also performed. Computer simulations are used to demonstrate the effectiveness of the proposed approach.

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M3 - Conference article

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JO - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

JF - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

T2 - Proceedings of the 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP. Part 1 (of 5)

Y2 - 21 April 1997 through 24 April 1997

ER -

Entropy based approach for direction-of-arrival estimation in Gaussian and non-Gaussian correlated noise

Abstract

ASJC Scopus subject areas

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