000165789 001__ 165789
000165789 005__ 20260114135812.0
000165789 0247_ $$2doi$$a10.1016/j.sigpro.2019.107442
000165789 0248_ $$2sideral$$a115704
000165789 037__ $$aART-2020-115704
000165789 041__ $$aeng
000165789 100__ $$0(orcid)0000-0002-1041-0498$$aDiaz-Guerra, D.$$uUniversidad de Zaragoza
000165789 245__ $$aSource cancellation in cross-correlation functions for broadband multisource DOA estimation
000165789 260__ $$c2020
000165789 5060_ $$aAccess copy available to the general public$$fUnrestricted
000165789 5203_ $$aIn multi-source localization systems, a stronger source can hide weaker sources. In this paper, we present a new technique to eliminate the effect of a source in the Generalized Cross-Correlation functions (GCCs) of the signals captured with a broadband sensor array. The proposed method is based on the projection of the GCCs onto a subspace orthogonal to the source position. This technique may be seen as an extension of previous narrowband techniques with an efficient time-domain implementation. The method does not only eliminate the main peak generated by the source, but also the peaks that appear if other sources are correlated with the cancelled one. This technique can be applied to find the maximum of these new GCCs or combined with other GCC-based Direction of Arrival (DOA) estimation techniques, such as the SRP-PHAT algorithm. In addition, no assumption about time-frequency sparsity needs to be made. The technique has been evaluated with a microphone array in simulated conditions and in a real highly reverberant room to verify that the proposed technique provides better results than the conventional SRP-PHAT and other state of the art source cancellation techniques when the location of various sources with different energy levels is required.
000165789 536__ $$9info:eu-repo/grantAgreement/ES/DGA/FSE
000165789 540__ $$9info:eu-repo/semantics/openAccess$$aby-nc-nd$$uhttps://creativecommons.org/licenses/by-nc-nd/4.0/deed.es
000165789 590__ $$a4.662$$b2020
000165789 591__ $$aENGINEERING, ELECTRICAL & ELECTRONIC$$b44 / 273 = 0.161$$c2020$$dQ1$$eT1
000165789 592__ $$a0.907$$b2020
000165789 593__ $$aComputer Vision and Pattern Recognition$$c2020$$dQ1
000165789 593__ $$aControl and Systems Engineering$$c2020$$dQ1
000165789 593__ $$aSoftware$$c2020$$dQ1
000165789 593__ $$aSignal Processing$$c2020$$dQ1
000165789 593__ $$aElectrical and Electronic Engineering$$c2020$$dQ1
000165789 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/submittedVersion
000165789 700__ $$0(orcid)0000-0002-7500-4650$$aBeltran, J.R.$$uUniversidad de Zaragoza
000165789 7102_ $$15008$$2785$$aUniversidad de Zaragoza$$bDpto. Ingeniería Electrón.Com.$$cÁrea Tecnología Electrónica
000165789 773__ $$g170 (2020), 107442 [12 pp.]$$pSignal process.$$tSIGNAL PROCESSING$$x0165-1684
000165789 8564_ $$s3556517$$uhttps://zaguan.unizar.es/record/165789/files/texto_completo.pdf$$yPreprint
000165789 8564_ $$s1373858$$uhttps://zaguan.unizar.es/record/165789/files/texto_completo.jpg?subformat=icon$$xicon$$yPreprint
000165789 909CO $$ooai:zaguan.unizar.es:165789$$particulos$$pdriver
000165789 951__ $$a2026-01-14-12:45:43
000165789 980__ $$aARTICLE