Prior mismatch in Bayesian direction of arrival estimation for sparse arrays

Joshua M. Kantor, Christ Richmond, Bill Correll, Daniel Bliss

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations


We study the mean-squared-error (MSE) performance of Bayesian direction-of-arrival (DOA) estimation for sparse linear arrays in which prior belief about the target location is incorporated into the estimation process. We utilize a recent extension of the method of interval errors (MIE) to the case of maximum a posteriori (MAP) direction-of-arrival estimation to more accurately predict low-medium MSE values in the presence of prior mismatch. We also develop a misspecified Cramér-Rao bound on MAP estimation that can improve the performance of MIE. We specialize to log-periodic arrays to conduct a notional trade study in which we consider the trade in improved estimation performance potentially possible with larger sparser arrays vs the increased sensitivity to incorrectly specified priors.

Original languageEnglish (US)
Title of host publicationIEEE National Radar Conference - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages6
StatePublished - Jun 22 2015
Event2015 IEEE International Radar Conference, RadarCon 2015 - Arlington, United States
Duration: May 10 2015May 15 2015


Other2015 IEEE International Radar Conference, RadarCon 2015
CountryUnited States

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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