High resolution direct position determination of radio frequency sources

Tom Tirer, Anthony J. Weiss

Research output: Contribution to journalArticlepeer-review

129 Scopus citations

Abstract

The most common methods for localization of radio frequency transmitters are based on two processing steps. In the first step, parameters such as angle of arrival or time of arrival are estimated at each base station independently. In the second step, the estimated parameters are used to determine the location of the transmitters. The direct position determination approach advocates using the observations from all the base stations together in order to estimate the locations in a single step. This single-step method is known to outperform two-step methods when the signalto- noise ratio is low. In this paper, we propose a direct-position-determination- based method for localization of multiple emitters that transmit unknown signals. The method does not require knowledge of the number of emitters. It is based on minimum-variance-distortionless- response considerations to achieve a high resolution estimator that requires only a two-dimensional search for planar geometry, and a three-dimensional search for the general case.

Original languageEnglish
Article number7337378
Pages (from-to)192-196
Number of pages5
JournalIEEE Signal Processing Letters
Volume23
Issue number2
DOIs
StatePublished - 1 Feb 2016
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2015 IEEE.

Funding

This work was supported in part by the Israel Science Foundation under Grants 503/15 and 965/15) and in part by the Institute for Future Technologies Research named for the Medvedi, Shwartzman and Gensler. The associate editor coordinating the review of this manuscript and approving it for publication was Dr. Muhammad Ikram.

FundersFunder number
Institute for Future Technologies Research
Israel Science Foundation503/15, 965/15

    Keywords

    • Array processing
    • Direct position determination
    • Emitter localization
    • Maximum likelihood
    • Minimum variance distortionless response (MVDR)
    • Multiple signal classification (MUSIC)

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