Ph.D. Programs Foundation of Ministry of Education of China (No.20122304120011);Program supported by Fundamental Research Funds for the Central Universities (No.HEUCFR1119)
SHI Jie, YANG De-sen, SHI Sheng-guo. Research on Noise Sound Source Localization Method in Shallow Water Based on the Multi-Path Model Match[J]. Acta Electronica Sinica, 2013, 41(3): 575-581.
DOI:
SHI Jie, YANG De-sen, SHI Sheng-guo. Research on Noise Sound Source Localization Method in Shallow Water Based on the Multi-Path Model Match[J]. Acta Electronica Sinica, 2013, 41(3): 575-581. DOI: 10.3969/j.issn.0372-2112.2013.03.026.
Research on Noise Sound Source Localization Method in Shallow Water Based on the Multi-Path Model Match
The noise sound sources localization method used in shallow water is proposed.The proposed method establishes the array signal model according to the characteristics of the underwater acoustic multi-path channel
and makes use of the multi-path information and the coherent matched idea to construct the spatial focused steering vector which is in accordance with the actual sound propagation characteristics.As a result
the proposed method can not only overcome the multi-path effect but also improve the localization accuracy.Furthermore
we take the ideas of the focused beamforming based on the worst-case performance optimization for reference
and impose constraint conditions on the actual focused steering vectors to improve the optimum weight vectors and spatial spectrum form.It turns out that this method involves a quadratic minimum problem subject to non-linear constraints.Through the discussion and analysis of the spatial spectrum structure
localization errors
-3dB beamwidth
peak and sidelobe ratio (PSR)
we present the relationships between the constraint parameter choices and the mismatch errors.It is proved that the proposed algorithm can improve the robustness of the high resolution method MVDR(Minimum Variance Distortionless Response)
and obtain sharper spectrum peaks and better noise interference suppression ability.