Broad-band signal-subspace spatial-spectrum (BASS-ALE) estimation

1988 ◽  
Vol 36 (7) ◽  
pp. 953-964 ◽  
Author(s):  
K.M. Buckley ◽  
L.J. Griffiths
Keyword(s):  
Broad Band ◽  
Spatial Spectrum ◽  
Signal Subspace ◽  
Band Signal

A Broad-Band Signal Generator

1948 ◽  
Vol 67 (1) ◽  
pp. 316-320
Author(s):  
Thomas P. Hahn ◽  
John Ebert ◽  
W. A. Lynch
Keyword(s):  
Broad Band ◽  
Signal Generator ◽  
Band Signal

Direction of Arrival Estimation Based on a Tensor Approach

2014 ◽  
Vol 530-531 ◽  
pp. 581-585
Author(s):  
Jin Fang Cheng ◽  
Fu Qian ◽  
Nan Li
Keyword(s):  
Singular Values ◽  
Spatial Spectrum ◽  
Signal Subspace ◽  
Subspace Projection ◽  
Third Order ◽  
Order Tensor ◽  
Multiple Signal Classification ◽  
Vector Hydrophone ◽  
Value Decomposition ◽  
Hydrophone Array

In this letter, we put forward a novel tensor-based Multiple Signal Classification (TB-MUSIC) applicable to a vector hydrophone array. For this purpose, the signal subspace is derived from the higher order singular value decomposition (HOSVD) of the third order tensor of the output model. Then the proposed method is achieved by signal subspace projection weighted with the reciprocal of principal singular values multiplying by the spatial spectrum based on TB-MUSIC. The synthetic spatial spectrum shows higher resolution and robustness under no-ideal scenarios. Monte Carlo experimental results are provided to illustrate the better performance of the proposed method.

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