2011•Unpublished venueRequires access

A quadratic constraint solution method for TDOA and FDOA localization

Fucheng Quo, K. C. Ho

Open publisher page 60 citations

Abstract

This paper proposes a new closed-form solution for the position and velocity of a moving source obtained from the time differences of arrival(TDOAs) and frequency differences of arrival(FDOAs) of its emitted signal arrived at a number of receivers. The method uses weighted least-squares formulation and imposes quadratic constraints among the positioning variables to improve performance. The proposed solution can achieve the Cramer-Rao lower bound(CRLB) accuracy for Gaussian TDOA and FDOA noise with a higher noise threshold than the previous method [7]. Simulations are included to examine the performance of the proposed solution and compare with the previous method.

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What this paper is about

This paper proposes a new closed-form solution for the position and velocity of a moving source obtained from the time differences of arrival(TDOAs) and frequency differences of arrival(FDOAs) of its emitted signal arrived at a number of receivers. The method uses weighted least-squares formulation and imposes quadratic constraints among the positioning variables to improve performance. The proposed solution can achieve the Cramer-Rao lower bound(CRLB) accuracy for Gaussian TDOA and FDOA noise with a higher noise threshold than the previous method [7]. Simulations are included to examine the performance of the proposed solution and compare with the previous method.

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OpenAlex reports 60 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

This paper proposes a new closed-form solution for the position and velocity of a moving source obtained from the time differences of arrival(TDOAs) and frequency differences of arrival(FDOAs) of its emitted signal arrived at a number of receivers. The method uses weighted least-squares formulation and imposes quadratic constraints among the positioning variables to improve performance. The proposed solution can achieve the Cramer-Rao lower bound(CRLB) accuracy for Gaussian TDOA and FDOA noise with a higher noise threshold than the previous method [7]. Simulations are included to examine the performance of the proposed solution and compare with the previous method.

Key concepts: FDOA, Multilateration, Cramér–Rao bound, Constraint (computer-aided design), Noise (video), Upper and lower bounds, Quadratic equation, Algorithm

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