2014Unpublished venueRequires access

DOA estimation of IR-UWB signals using coherent signal processing

D. Santhosh Kumar, I. S. Hinduja, V. V. Mani

Open publisher page 3 citations

Abstract

In this paper coherent signal subspace method (CSM) is used to estimate the direction of arrival (DOA) of ultra wide band (UWB) signals in a multipath, non line of sight (NLOS) environment. As the name suggests it focuses the signal space of the wideband signal into a narrow subspace and the pseudospectrum of the resultant focused signal is calculated. The focusing frequency is calculated by minimizing the subspace fitting error. The frequency hence obtained gives better estimation results as compared to the case where the mid frequency of the spectrum is taken as the focusing frequency. This method proves to be the best choice for a wideband signal as it involves the multiple signal classification (MUSIC) algorithm, which has this innate ability to seperate multipath channels.

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What this paper is about

In this paper coherent signal subspace method (CSM) is used to estimate the direction of arrival (DOA) of ultra wide band (UWB) signals in a multipath, non line of sight (NLOS) environment. As the name suggests it focuses the signal space of the wideband signal into a narrow subspace and the pseudospectrum of the resultant focused signal is calculated. The focusing frequency is calculated by minimizing the subspace fitting error. The frequency hence obtained gives better estimation results as compared to the case where the mid frequency of the spectrum is taken as the focusing frequency. This method proves to be the best choice for a wideband signal as it involves the multiple signal classification (MUSIC) algorithm, which has this innate ability to seperate multipath channels.

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Available abstract

In this paper coherent signal subspace method (CSM) is used to estimate the direction of arrival (DOA) of ultra wide band (UWB) signals in a multipath, non line of sight (NLOS) environment. As the name suggests it focuses the signal space of the wideband signal into a narrow subspace and the pseudospectrum of the resultant focused signal is calculated. The focusing frequency is calculated by minimizing the subspace fitting error. The frequency hence obtained gives better estimation results as compared to the case where the mid frequency of the spectrum is taken as the focusing frequency. This method proves to be the best choice for a wideband signal as it involves the multiple signal classification (MUSIC) algorithm, which has this innate ability to seperate multipath channels.

Key concepts: Signal processing, Computer science, SIGNAL (programming language), Radar signal processing, Estimation, Electronic engineering, Speech recognition, Telecommunications

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