Full laser-based Lamb waves array imaging based on the two-dimensional multiple signal classification algorithm

Author(s):  
Zeng-Hua Liu ◽  
Rui-Xiang Su ◽  
Ting-Ting Zhang ◽  
Gong Yu ◽  
Cun-Fu He ◽  
...  
2014 ◽  
Vol 926-930 ◽  
pp. 1795-1799
Author(s):  
Hao Zhou ◽  
Zhi Jie Huo

Vector-hydrophone can simultaneously measure acoustic pressure and orthogonal components of the particle velocity. The 180o ambiguity in DOA estimation can be eliminated using information obtained by vector hydrophone array. Multiple signal classification algorithm is a method that takes the eigen-decomposition of data co-variance matrix to obtain the estimation of signal spatial spectrum. The two-dimensional DOA of acoustic sources is estimated based on multiple signal classification algorithm using the vector-hydrophone uniform linear array. Simulation results show that better DOA resolution performance can be obtained from vector hydrophones. Furthermore, the paper takes the de-correlation of correlated sources using spatial smoothness technology to obtain perfect performance of two-dimensional DOA estimation.


2018 ◽  
Vol 12 (2) ◽  
pp. 101-109
Author(s):  
Guan Jishi ◽  
Shi Yaowu ◽  
Deng Lifei ◽  
Zhu Lanxiang ◽  
Shi Hongwei

In the DOA estimation of monostatic L-shaped array MIMO radar, Multiple Signal Classification algorithm is efficient. But the peak searching process of Multiple Signal Classification algorithm needs large amount of spectrum calculation. Focusing on the spectrum peak searching process of Multiple Signal Classification, an iterative search approach to reduce the calculation amount is proposed. The first- and second-order derivatives of Multiple Signal Classification spectrum functions are achieved and the calculation amount is analyzed. Two-dimensional Newton iteration methods are applied with multisearching threads and derivation information. The searching approach can greatly reduce the computational complexity of Multiple Signal Classification spectrum peak searching. The total calculation amount of the first and second derivatives is about 15 times of the spectrum function. However, in the two-dimensional searching, especially in the high accuracy processes, the amount of searched points can be reduced by ten hundreds times, and the computation is much lower than the common spectrum peak searching method. The simulation results show that when the search thread number reaches 100, the searching process can effectively achieve the entire spectrum peak and get the correct DOA estimation.


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