Fast detection of coherent signals using pre-conditioned root-MUSIC based on Toeplitz matrix reconstruction

Author(s):  
A. Goian ◽  
M. I. AlHajri ◽  
R. M. Shubair ◽  
L. Weruaga ◽  
A. R. Kulaib ◽  
...  
2011 ◽  
Vol 135-136 ◽  
pp. 331-335
Author(s):  
Ling Tang ◽  
Hong Song ◽  
Lian Jun Hu

A new blind beamforming algorithm for separating and estimating coherent signals arriving at an antenna array is proposed in this paper. This algorithm is implemented through arranging the received data’s correlation function of each array element and reference array element (the first array element), to form the Hermitian Toeplitz matrix first. Then through the singular value decomposition of the matrix the signal subspace and noise subspace can be get, in order to achieve the direction vector of coherent sources to beamform, which can separate the independent signals from different directions effectively without knowing the transcendent knowledge of the signals. The new approach can estimate the coherent signals’ direction-of-arrival(DOA) on the basis of separation, and has good performance under the low SNR. The simulation results show that the proposed method is effective.


2011 ◽  
Vol 291-294 ◽  
pp. 3250-3254 ◽  
Author(s):  
Ke Zhang ◽  
Peng Ma ◽  
Jian Yun Zhang

For DOA estimation of coherent signals in switch antenna array (SAA), a new fast algorithm is proposed. Instead of conventional sub-space algorithm’s covariance matrix, a Toeplitz matrix is constructed with a single cycle of sampled data. It is proved theoretically that the ranks of the Toeplitz matrix is equal to the number of signal sources and has no relations with the coherency of the signal source. Through eigenvalue decomposition, signal and noise subspace are obtained respectively, then DOA estimation can be done by one-dimensional spectral peak searching according to the MUSIC algorithm. The theoretical analysis and simulation results demonstrate validity and superiority of the novel algorithm.


Sensors ◽  
2020 ◽  
Vol 20 (12) ◽  
pp. 3595 ◽  
Author(s):  
Zhuang Xie ◽  
Chongyi Fan ◽  
Jiahua Zhu ◽  
Xiaotao Huang

This paper proposes a beamforming method in the presence of coherent multipath arrivals at the array. The proposed method avoids the prior knowledge or estimation of the directions of arrival (DOAs) of the direct path signal and the multipath signals. The interferences are divided into two groups based on their powers and the interference-plus-noise covariance matrix (INCM) is reconstructed through the doubly covariance matrix reconstruction concept. The composite steering vector (CSV) that accounts for the direct path signal and multipath signals is estimated as the principal eigenvector of the sample covariance matrix with interferences and noise removed. The optimal weight vector is finally computed using the INCM and the CSV. The proposed method involves no spatial smoothing and avoids reduction in the degree of freedom. Simulation results demonstrate the improved performance of the proposed method.


Sensors ◽  
2019 ◽  
Vol 19 (3) ◽  
pp. 707 ◽  
Author(s):  
Zhen Meng ◽  
Weidong Zhou

Coprime arrays have shown potential advantages for direction-of-arrival (DOA) estimation by increasing the number of degrees-of-freedom in the difference coarray domain with fewer physical sensors. In this paper, a new DOA estimation algorithm for coprime array based on the estimation of signal parameter via rotational invariance techniques (ESPRIT) is proposed. We firstly derive the observation vector of the virtual uniform linear array but the covariance matrix of this observation vector is rank-deficient. Different from the traditional Toeplitz matrix reconstruction method using the observation vector, we propose a modified Toeplitz matrix reconstruction method using any non-zero row of the covariance matrix in the virtual uniform linear array. It can be proved in theory that the reconstructed Toeplitz covariance matrix has full rank. Therefore, the improved ESPRIT method can be used for DOA estimation without peak searching. Finally, the closed-form solution for DOA estimation in coprime array is obtained. Compared to the traditional coprime multiple signal classification (MUSIC) methods, the proposed method circumvents the use of spatial smoothing technique, which usually results in performance degradation and heavy computational burden. The effectiveness of the proposed method is demonstrated by numerical examples.


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