Bounds on Passive Tdoa Estimation in Mixtures

Amir Weiss, Arie Yeredor

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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 languageEnglish
Title of host publication2018 IEEE Statistical Signal Processing Workshop, SSP 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages50-54
Number of pages5
ISBN (Print)9781538615706
DOIs
StatePublished - 29 Aug 2018
Event20th IEEE Statistical Signal Processing Workshop, SSP 2018 - Freiburg im Breisgau, Germany
Duration: 10 Jun 201813 Jun 2018

Publication series

Name2018 IEEE Statistical Signal Processing Workshop, SSP 2018

Conference

Conference20th IEEE Statistical Signal Processing Workshop, SSP 2018
Country/TerritoryGermany
CityFreiburg im Breisgau
Period10/06/1813/06/18

Keywords

  • Cramér-Rao lower bound
  • TDOA
  • maximum likelihood
  • source separation

Fingerprint

Dive into the research topics of 'Bounds on Passive Tdoa Estimation in Mixtures'. Together they form a unique fingerprint.

Cite this