Time difference localization in the presence of outliers

Joseph S. Picard*, Anthony J. Weiss

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

28 Scopus citations


In this work we examine new ways to solve a time-difference-of-arrival (TDOA) localization problem when the set of measurements is contaminated by outliers. The proposed method relies on the minimization of an Lp-norm based cost function with p∈(0,1]. This norm is known to provide robustness against outliers. Some known positioning method can eventually successfully locate an emitter in the presence of outlier measurements, but it is at the expense of huge computational costs due to multi-dimensional grid search. We propose in this paper a way to dramatically lighten the computational load by reducing the problem to a few linear searches. Even if 70% of the measurements are outliers, the proposed positioning method provides high accuracy location estimates, while keeping the computational load very low. Optionally, the location estimates can be used to identify and reject outliers from the data set, which can then serve as an input of any common TDOA positioning method to obtain refined location estimates. Numerical examples corroborate our results, both in terms of accuracy and of computational time.

Original languageEnglish
Pages (from-to)2432-2443
Number of pages12
JournalSignal Processing
Issue number10
StatePublished - Oct 2012


FundersFunder number
Center for Absorption in Science
Institute for Future Technologies Research named for the Medvedi, Shwartzman and Gensler Families
Weinstein Research Institute for Signal Processing
Israel Science Foundation218/08


    • Emitter localization
    • Location estimation
    • Multipath
    • Outliers
    • Time-difference-of- arrival


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