Robust Direction of Arrival (DOA) Estimation Using RBF Neural Network in Impulsive Noise Environment

descriptionPublicationkeyboard_double_arrow_right Part of book or chapter of book , Conference object , Article 01 Jan 2005Publisher:Springer Berlin Heidelberg

Authors: Hong Tang 0001; Tianshuang Qiu; Sen Li; Ying Guo; Wenrong Zhang;

doi: 10.1007/11427469_53

Robust Direction of Arrival (DOA) Estimation Using RBF Neural Network in Impulsive Noise Environment

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Abstract

The DOA problem in impulsive noise environment is approached as a mapping which can be modeled using a radial-basis function neural network (RBFNN). To improve the robustness, the input pairs are preprocessed by Fractional Low-Order Statistics (FLOS) technique. The performance of this network is compared to that of the FLOM-MUSIC for both uncorrelated and correlated source. Numerical results show the good performance of the RBFNN-based DOA estimation.

Related Organizations

Dalian Polytechnic University
China (People's Republic of)

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