2011•IEEE Transactions on Signal ProcessingRequires access

An Asymptotically Efficient Estimator for TDOA and FDOA Positioning of Multiple Disjoint Sources in the Presence of Sensor Location Uncertainties

Ming Sun, K. C. Ho

Open publisher page 147 citations

Abstract

This correspondence considers the problem of locating multiple disjoint sources using time differences of arrival (TDOAs) and frequency differences of arrival (FDOAs) in the presence of sensor position and velocity errors. Previous work applies to one source only with suboptimum performance for near source, or requires joint estimation of the source and sensor locations that could be computation demanding. Through nonlinearly transforming the measurements and converting them with respect to the inaccurate sensor locations, we have developed an algebraic solution to this problem. The solution is shown analytically to achieve the Cramér–Rao lower bound (CRLB) performance over small noise region and does not require joint estimation with sensor locations.

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What this paper is about

This correspondence considers the problem of locating multiple disjoint sources using time differences of arrival (TDOAs) and frequency differences of arrival (FDOAs) in the presence of sensor position and velocity errors. Previous work applies to one source only with suboptimum performance for near source, or requires joint estimation of the source and sensor locations that could be computation demanding. Through nonlinearly transforming the measurements and converting them with respect to the inaccurate sensor locations, we have developed an algebraic solution to this problem. The solution is shown analytically to achieve the Cramér–Rao lower bound (CRLB) performance over small noise region and does not require joint estimation with sensor locations.

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OpenAlex reports 147 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

This correspondence considers the problem of locating multiple disjoint sources using time differences of arrival (TDOAs) and frequency differences of arrival (FDOAs) in the presence of sensor position and velocity errors. Previous work applies to one source only with suboptimum performance for near source, or requires joint estimation of the source and sensor locations that could be computation demanding. Through nonlinearly transforming the measurements and converting them with respect to the inaccurate sensor locations, we have developed an algebraic solution to this problem. The solution is shown analytically to achieve the Cramér–Rao lower bound (CRLB) performance over small noise region and does not require joint estimation with sensor locations.

Key concepts: Multilateration, Cramér–Rao bound, Estimator, Disjoint sets, FDOA, Algorithm, Upper and lower bounds, Computer science

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