SNR-dependent filtering for time of arrival estimation in high noise

Alexander Apartsin, Leon N. Cooper, Nathan Intrator

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

6 Scopus citations

Abstract

Time of Arrival (ToA) estimation is a cornerstone of many of the remote sensing applications including radar, sonar, and reflective seismology. The conventional Matched Filter Maximum Likelihood (MFML) ToA estimator suffers from rapid deterioration in the accuracy as Signal to Noise Ratio (SNR) falls below certain threshold value. In this paper we suggest an alternative method for ToA estimation based on the fusion of measurements from biased estimators which are obtained using a pair of unmatched filters. Suboptimal but not perfectly correlated estimators are combined together to produce a robust estimator for ToA estimation in high noise. The unmatched filters pair is parameterized by a single parameter (phase shift) which is selected based on estimated SNR level.

Original languageEnglish
Title of host publicationProceedings of the 2010 IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2010
Pages427-431
Number of pages5
DOIs
StatePublished - 2010
Externally publishedYes
Event2010 IEEE 20th International Workshop on Machine Learning for Signal Processing, MLSP 2010 - Kittila, Finland
Duration: 29 Aug 20101 Sep 2010

Publication series

NameProceedings of the 2010 IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2010

Conference

Conference2010 IEEE 20th International Workshop on Machine Learning for Signal Processing, MLSP 2010
Country/TerritoryFinland
CityKittila
Period29/08/101/09/10

Keywords

  • Threshold effect
  • Time of arrival

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