Bounds on Passive Tdoa Estimation in Mixtures

Amir Weiss; Arie Yeredor

doi:10.1109/ssp.2018.8450810

Bounds on Passive Tdoa Estimation in Mixtures

Amir Weiss, Arie Yeredor

Tel Aviv University

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

1 Scopus citations

Abstract

We consider the problem of Time Difference of Arrival (TDOA) estimation in mixtures, namely when several sources are received by several receivers, possibly with different delays and attenuations. Under the assumption that the sources are stationary Gaussian with known spectra (a semi-blind scenario), we derive the Cramér-Rao Lower Bound on the Mean Squared Error (MSE) in unbiased joint estimation of the delays and of the mixing coefficients. We then analyze the results, drawing conclusions on the effects of the different model parameters (mixing coefficients, delay differences, signal to noise ratio) on the resulting bound, pointing out essential differences from the classical cases of static mixtures (with no delays) on one hand, and of single-source TDOA estimation on the other hand.

Original language	English
Title of host publication	2018 IEEE Statistical Signal Processing Workshop, SSP 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	50-54
Number of pages	5
ISBN (Print)	9781538615706
DOIs	https://doi.org/10.1109/ssp.2018.8450810
State	Published - 29 Aug 2018
Externally published	Yes
Event	20th IEEE Statistical Signal Processing Workshop, SSP 2018 - Freiburg im Breisgau, Germany Duration: 10 Jun 2018 → 13 Jun 2018

Publication series

Name	2018 IEEE Statistical Signal Processing Workshop, SSP 2018

Conference

Conference	20th IEEE Statistical Signal Processing Workshop, SSP 2018
Country/Territory	Germany
City	Freiburg im Breisgau
Period	10/06/18 → 13/06/18

Bibliographical note

Publisher Copyright:
© 2018 IEEE.

Keywords

Cramér-Rao lower bound
TDOA
maximum likelihood
source separation

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10.1109/ssp.2018.8450810

Cite this

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title = "Bounds on Passive Tdoa Estimation in Mixtures",

abstract = "We consider the problem of Time Difference of Arrival (TDOA) estimation in mixtures, namely when several sources are received by several receivers, possibly with different delays and attenuations. Under the assumption that the sources are stationary Gaussian with known spectra (a semi-blind scenario), we derive the Cram{\'e}r-Rao Lower Bound on the Mean Squared Error (MSE) in unbiased joint estimation of the delays and of the mixing coefficients. We then analyze the results, drawing conclusions on the effects of the different model parameters (mixing coefficients, delay differences, signal to noise ratio) on the resulting bound, pointing out essential differences from the classical cases of static mixtures (with no delays) on one hand, and of single-source TDOA estimation on the other hand.",

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Weiss, A & Yeredor, A 2018, Bounds on Passive Tdoa Estimation in Mixtures. in 2018 IEEE Statistical Signal Processing Workshop, SSP 2018., 8450810, 2018 IEEE Statistical Signal Processing Workshop, SSP 2018, Institute of Electrical and Electronics Engineers Inc., pp. 50-54, 20th IEEE Statistical Signal Processing Workshop, SSP 2018, Freiburg im Breisgau, Germany, 10/06/18. https://doi.org/10.1109/ssp.2018.8450810

Bounds on Passive Tdoa Estimation in Mixtures. / Weiss, Amir; Yeredor, Arie.
2018 IEEE Statistical Signal Processing Workshop, SSP 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 50-54 8450810 (2018 IEEE Statistical Signal Processing Workshop, SSP 2018).

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

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Bounds on Passive Tdoa Estimation in Mixtures

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Conference

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Keywords

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