Explicit Ziv-Zakai Bound For Multiple Sources Doa Estimation

Zongyu Zhang; Yujie Gu; Zhiguo Shi

doi:10.1109/icassp49357.2023.10094868

Explicit Ziv-Zakai Bound For Multiple Sources Doa Estimation

Zongyu Zhang, Yujie Gu, Zhiguo Shi

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

In direction-of-arrival (DOA) estimation, Cramér-Rao bound is widely used to lower bound the mean square error (MSE), which, however, is a local bound. As a global bound, existing Ziv-Zakai bound (ZZB) is restricted by the single source assumption and has not considered the effect of ordering process during MSE calculation. In this paper, we derive an explicit ZZB for multiple sources DOA estimation, where the ZZB derivation framework is first extended to multiple sources case. Further, order statistics are introduced to describe the effect the ordering process on the change of a priori distribution of DOAs, which finally makes the derived ZZB tight over a wide range of signal-to-noise ratio. The derived ZZB reveals the relationship between the number of sources and the convergence performance in the a priori performance region. Simulation results demonstrate the global tightness of the derived ZZB.

Original language	English
Title of host publication	ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing, Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781728163277
DOIs	https://doi.org/10.1109/icassp49357.2023.10094868
State	Published - 2023
Externally published	Yes
Event	48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023 - Rhodes Island, Greece Duration: 4 Jun 2023 → 10 Jun 2023

Publication series

Name	ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume	2023-June
ISSN (Print)	1520-6149

Conference

Conference	48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023
Country/Territory	Greece
City	Rhodes Island
Period	4/06/23 → 10/06/23

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

Funding

The work of Zongyu Zhang and Zhiguo Shi was supported by the National Natural Science Foundation of China under Grants U21A20456, 61901413, and 62271444.

Funders	Funder number
National Natural Science Foundation of China	62271444, 61901413, U21A20456

Keywords

Cramér-Rao bound
Ziv-Zakai bound
direction-of-arrival estimation
mean square error
order statistics
permutation ambiguity

Access to Document

10.1109/icassp49357.2023.10094868

Cite this

Zhang, Z., Gu, Y., & Shi, Z. (2023). Explicit Ziv-Zakai Bound For Multiple Sources Doa Estimation. In ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing, Proceedings (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings; Vol. 2023-June). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/icassp49357.2023.10094868

Zhang, Zongyu ; Gu, Yujie ; Shi, Zhiguo. / Explicit Ziv-Zakai Bound For Multiple Sources Doa Estimation. ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing, Proceedings. Institute of Electrical and Electronics Engineers Inc., 2023. (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings).

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abstract = "In direction-of-arrival (DOA) estimation, Cram{\'e}r-Rao bound is widely used to lower bound the mean square error (MSE), which, however, is a local bound. As a global bound, existing Ziv-Zakai bound (ZZB) is restricted by the single source assumption and has not considered the effect of ordering process during MSE calculation. In this paper, we derive an explicit ZZB for multiple sources DOA estimation, where the ZZB derivation framework is first extended to multiple sources case. Further, order statistics are introduced to describe the effect the ordering process on the change of a priori distribution of DOAs, which finally makes the derived ZZB tight over a wide range of signal-to-noise ratio. The derived ZZB reveals the relationship between the number of sources and the convergence performance in the a priori performance region. Simulation results demonstrate the global tightness of the derived ZZB.",

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Zhang, Z, Gu, Y & Shi, Z 2023, Explicit Ziv-Zakai Bound For Multiple Sources Doa Estimation. in ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing, Proceedings. ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, vol. 2023-June, Institute of Electrical and Electronics Engineers Inc., 48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023, Rhodes Island, Greece, 4/06/23. https://doi.org/10.1109/icassp49357.2023.10094868

Explicit Ziv-Zakai Bound For Multiple Sources Doa Estimation. / Zhang, Zongyu; Gu, Yujie; Shi, Zhiguo.
ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing, Proceedings. Institute of Electrical and Electronics Engineers Inc., 2023. (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings; Vol. 2023-June).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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Zhang Z, Gu Y, Shi Z. Explicit Ziv-Zakai Bound For Multiple Sources Doa Estimation. In ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing, Proceedings. Institute of Electrical and Electronics Engineers Inc. 2023. (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings). doi: 10.1109/icassp49357.2023.10094868

Explicit Ziv-Zakai Bound For Multiple Sources Doa Estimation

Abstract

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Bibliographical note

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Keywords

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