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Hybrid iterative TDOA emitter localization using two different techniques

Alp Ertürk, Aydın Bayri

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Abstract

Two well developed techniques in emitter location estimation using time difference of arrival (TDOA) are analyzed and compared for different situations and noise values. These techniques are a passive localization algorithm and a closed-form solution based on association by clustering. The advantages and disadvantages of these techniques are determined and supported by the simulation examples. Also, a hybrid model, using these two methods and including an iterative process based on maximum likelihood (ML) is presented and analyzed in performance.

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What this paper is about

Two well developed techniques in emitter location estimation using time difference of arrival (TDOA) are analyzed and compared for different situations and noise values. These techniques are a passive localization algorithm and a closed-form solution based on association by clustering. The advantages and disadvantages of these techniques are determined and supported by the simulation examples. Also, a hybrid model, using these two methods and including an iterative process based on maximum likelihood (ML) is presented and analyzed in performance.

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Available abstract

Two well developed techniques in emitter location estimation using time difference of arrival (TDOA) are analyzed and compared for different situations and noise values. These techniques are a passive localization algorithm and a closed-form solution based on association by clustering. The advantages and disadvantages of these techniques are determined and supported by the simulation examples. Also, a hybrid model, using these two methods and including an iterative process based on maximum likelihood (ML) is presented and analyzed in performance.

Key concepts: Multilateration, FDOA, Common emitter, Iterative method, Computer science, Iterative and incremental development, Cluster analysis, Noise (video)

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