Localizing mixed far- and near-field sources using beamforming deconvolution techniques
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摘要:
提出了定位远近场混合源的波束解卷积技术, 针对非相干远近场混合声信号的线列阵观测结果, 推导了其常规波束形成(CBF)空间谱中固有的广义二维卷积数学关系, 利用Richardson-Lucy算法实现波束能量聚焦以获得近场目标的精确空域参数估计, 通过混合源协方差矩阵向近场流形的正交补空间投影操作提取远场分量, 并分析得到其内在的一维卷积关系, 然后通过角度域波束解卷积进行远场信号的波达估计。仿真分析表明, 所提方法提升了CBF谱的空域分辨力, 通过投影映射隔离近场分量后实现了混合源的分离。与现有方案相比, 所提算法针对远场信源可实现10 dB的背景噪声级抑制。
Abstract:A beam deconvolution technique for the location of the mixed far- and near-field sources is presented in this paper. The generalized two-dimensional convolution formalism inherent in the conventional beamforming (CBF) spatial spectrum yielded by the linear array observations for noncoherent mixed signals is derived. The Richardson-Lucy algorithm is exploited to focus beam power and obtain accurate spatial parameters of the near-field sources. The far-field components are extracted by mapping the mixed-source covariance matrix to the near-field manifold’s orthogonal complement space. The intrinsic one-dimensional convolution relationship is revealed. Hence, the angular domain beamforming deconvolution is used to estimate the far-field signals’ incident angles. The simulation results show that the proposed method improves the spatial resolution of the CBF spectrum and can separate the mixed sources after isolating the near-field components by projection mapping. Besides, a background noise level suppression of 10 dB for the far-field sources is achieved by comparing it with the existing schemes.
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Key words:
- Passive location /
- Far-field source /
- Near-field source /
- Deconvolved beamforming
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