Joint TDOA and FDOA estimation: A conditional bound and its use for optimally weighted localization

Arie Yeredor, Eyal Angel

Research output: Contribution to journalArticlepeer-review

Abstract

Modern passive emitter-location systems are often based on joint estimation of the time-difference of arrival (TDOA) and frequency-difference of arrival (FDOA) of an unknown signal at two (or more) sensors. Classical derivation of the associated Cramér-Rao bound (CRB) relies on a stochastic, stationary Gaussian signal-model, leading to a diagonal Fisher information matrix with respect to the TDOA and FDOA. This diagonality implies that (under asymptotic conditions) the respective estimation errors are uncorrelated. However, for some specific (nonstationary, non-Gaussian) signals, especially chirp-like signals, these errors can be strongly correlated. In this work we derive a conditional (or a signal-specific) CRB, modeling the signal as a deterministic unknown. Given any particular signal, our CRB reflects the possible signal-induced correlation between the TDOA and FDOA estimates. In addition to its theoretical value, we show that the resulting CRB can be used for optimal weighting of TDOA-FDOA pairs estimated over different signal-intervals, when combined for estimating the target location. Substantial improvement in the resulting localization accuracy is shown to be attainable by such weighting in a simulated operational scenario with some chirp-like target signals.

Original languageEnglish
Article number5678660
Pages (from-to)1612-1623
Number of pages12
JournalIEEE Transactions on Signal Processing
Volume59
Issue number4
DOIs
StatePublished - Apr 2011

Keywords

  • Chirp
  • conditional bound
  • confidence ellipse
  • frequency-difference of arrival (FDOA)
  • passive emitter location
  • time-difference of arrival (TDOA)

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Electrical and Electronic Engineering

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