2009Jisuanji fangzhenRequires access

On New Algorithm for TDOA Location Based on Tikhonov Regularization Theory

Luo Ming-jun

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Abstract

A novel multi-station TDOA location method based on Tikhonov regularization theory was proposed.The regularization method,with the advantage that it needed no assumptions on the distribution of noises,was adopted to solve the linearized location equations with a quasi-optimal principle.The convergence of the regularization solution was theoretically confirmed,and then the regularization location procedure was introduced.In simulation part,regularization location method was compared with the ordinary least square(OLS) location method under different noise conditions.The regularization location shows a higher estimate precision and better ability of resisting noises than OLS method.Conclusions can be drawn that regularization location method is practicable.

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What this paper is about

A novel multi-station TDOA location method based on Tikhonov regularization theory was proposed.The regularization method,with the advantage that it needed no assumptions on the distribution of noises,was adopted to solve the linearized location equations with a quasi-optimal principle.The convergence of the regularization solution was theoretically confirmed,and then the regularization location procedure was introduced.In simulation part,regularization location method was compared with the ordinary least square(OLS) location method under different noise conditions.The regularization location shows a higher estimate precision and better ability of resisting noises than OLS method.Conclusions can be drawn that regularization location method is practicable.

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Available abstract

A novel multi-station TDOA location method based on Tikhonov regularization theory was proposed.The regularization method,with the advantage that it needed no assumptions on the distribution of noises,was adopted to solve the linearized location equations with a quasi-optimal principle.The convergence of the regularization solution was theoretically confirmed,and then the regularization location procedure was introduced.In simulation part,regularization location method was compared with the ordinary least square(OLS) location method under different noise conditions.The regularization location shows a higher estimate precision and better ability of resisting noises than OLS method.Conclusions can be drawn that regularization location method is practicable.

Key concepts: Tikhonov regularization, Regularization (linguistics), Backus–Gilbert method, Regularization perspectives on support vector machines, Mathematics, Mathematical optimization, Algorithm, Applied mathematics

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