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Novel direction of arrival estimation using Adaptive Directional Spatial Time-Frequency Distribution

•A multi-sensor Instantaneous Frequency (IF) estimation algorithm is developed for Direction of Arrival (DOA) estimation.•The proposed algorithm gives an accurate estimation even when TF signatures of sources partially overlap.•In order to improve the performance a new class of spatial adaptive time...

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Bibliographic Details
Published in:Signal processing 2020-03, Vol.168, p.107342, Article 107342
Main Authors: Khan, Nabeel Ali, Ali, Sadiq, Mohammadi, Mokhtar, Akram, Jamal
Format: Article
Language:English
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Summary:•A multi-sensor Instantaneous Frequency (IF) estimation algorithm is developed for Direction of Arrival (DOA) estimation.•The proposed algorithm gives an accurate estimation even when TF signatures of sources partially overlap.•In order to improve the performance a new class of spatial adaptive time-frequency distributions are defined. Novel spatial time-frequency distributions and instantaneous frequency estimation scheme are developed for the proposed direction of arrival estimation scheme. A new class of spatial adaptive time-frequency distributions is proposed that are obtained by local optimization of the smoothing kernel for obtaining spatial time-frequency distributions. The instantaneous frequencies of the source signals are estimated using modified Viterbi algorithm that exploits both the spatial diversity (estimated through spatial time-frequency distributions) and continuity of the instantaneous frequency curves for accurate estimation at low Signal-to-Noise-Ratio (SNR) scenarios when the signal components intersect each other in time-frequency domain. In the proposed scheme the estimated instantaneous frequencies are used for the direction of arrival estimation of each source separately, thus results in accurate estimates even in low SNR regime. Experimental results are given that indicate that the proposed direction of arrival estimation algorithm outperforms the traditional directional of arrival estimation schemes.
ISSN:0165-1684
1872-7557
DOI:10.1016/j.sigpro.2019.107342