scholarly journals Robust direction-of-arrival estimation in non-Gaussian noise

1998 ◽  
Vol 46 (5) ◽  
pp. 1443-1451 ◽  
Author(s):  
Y. Yardimci ◽  
A.E. Cetin ◽  
J.A. Cadzow
2017 ◽  
Vol 6 (3) ◽  
pp. 33
Author(s):  
T. Aslam ◽  
I. Ahmed ◽  
M. I. Aslam ◽  
S. M. U. Ali ◽  
T. Malik

We present an algorithm to estimate direction of arrival (DOA) of an incoming wave received at an array antenna in the scenario where the incoming wave is contaminated by the additive white Gaussian noise and scattered by arbitrary shaped 3D scatterer(s). We present different simulation examples to show the validity of the proposed method. It is observed that the proposed algorithm is capable of closely estimating the DOA of an incoming wave irrespective of the shape of the scatterer provided the decision is made over multiple iterations. Moreover, presence of noise affects the estimate especially in the case of low signal-to-noise ratio (SNR) that gives a relatively large estimation error. However, for larger SNR the DOA estimation is primarily dependent on the scatterer only.


2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Shuang Li ◽  
Xiaoxiao Jiang ◽  
Sai Ma ◽  
Yingguan Wang

A novel direction-of-arrival (DOA) estimation method is proposed based on the sparse cumulants fitting without redundancy. Firstly, we derive that some fourth order cumulants of the array output are redundant and therefore are removed to reduce computational complexity. Then, the left cumulants are sparsely represented on an overcomplete basis and the DOAs are resolved by using a software package. Despite introducing a high variance, the proposed method shows several advantages including the ability to detect more sources than sensors, high resolution, and robustness to all kinds of Gaussian noise. Besides, our method does not have to know, a priori, the number of sources. Simulation results are presented to illustrate the effectiveness and efficiency of the proposed method.


2016 ◽  
Vol 128 ◽  
pp. 512-520 ◽  
Author(s):  
Olivier Besson ◽  
Yuri Abramovich ◽  
Ben Johnson

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