scholarly journals Improved ESPRIT Method for Joint Direction-of-Arrival and Frequency Estimation Using Multiple-Delay Output

2012 ◽  
Vol 2012 ◽  
pp. 1-9 ◽  
Author(s):  
Wang Xudong ◽  
Xiaofei Zhang ◽  
Jianfeng Li ◽  
Jinchao Bai
Keyword(s):  
Antenna Arrays ◽  
Frequency Estimation ◽  
Direction Of Arrival ◽  
Joint Angles ◽  
Linear Arrays ◽  
Estimation Performance ◽  
Multiple Delay ◽  
Joint Direction ◽  
Esprit Algorithm ◽  
Linear Antenna Arrays

An automatic pairing joint direction-of-arrival (DOA) and frequency estimation is presented to overcome the unsatisfactory performances of estimation of signal parameter via rotational invariance techniques- (ESPRIT-) like algorithm of Wang (2010), which requires an additional pairing. By using multiple-delay output of a uniform linear antenna arrays (ULA), the proposed algorithm can estimate joint angles and frequencies with an improved ESPRIT. Compared with Wang’s ESPRIT algorithm, the angle estimation performance of the proposed algorithm is greatly improved. The frequency estimation performance of the proposed algorithm is same with that of Wang’s ESPRIT algorithm. Furthermore, the proposed algorithm can obtain automatic pairing DOA and frequency parameters, and it has a comparative computational complexity in contrast to Wang’s ESPRIT algorithm. By the way, this proposed algorithm can also work well for nonuniform linear arrays. The useful behavior of this proposed algorithm is verified by simulations.

Joint DOA and Frequency Estimation for Linear Array with Compressed Sensing PARAFAC Framework

2017 ◽  
Vol 26 (09) ◽  
pp. 1750136 ◽  
Author(s):  
Shu Li ◽  
Zezhou Sun ◽  
Xiaofei Zhang ◽  
Weiyang Chen ◽  
Dazhuan Xu
Keyword(s):  
Compressed Sensing ◽  
Frequency Estimation ◽  
Estimation Algorithm ◽  
Linear Arrays ◽  
Propagator Method ◽  
Joint Direction ◽  
Parallel Factor ◽  
Esprit Algorithm ◽  
Spatial Sparsity ◽  
Better Than

In this paper, a joint direction of arrival (DOA) and frequency estimation algorithm of narrow-band signals is proposed via compressed sensing (CS) parallel factor (PARAFAC) framework. The proposed algorithm constructs the data model into a PARAFAC model, and compresses it to a smaller one. Then trilinear alternating least-squares (TALS) algorithm is exploited to estimate the compressed parameter matrices, and finally the joint DOA and frequency estimation is obtained via the spatial sparsity and the frequency sparsity. Due to compression, the proposed algorithm has lower computational complexity than the conventional PARAFAC algorithm, and saves more memory capacity for practical application. The DOA and frequency estimation performance of the proposed algorithm is very close to that of the conventional PARAFAC algorithm, and better than those of the estimation of signal parameters via rotational invariance techniques (ESPRIT) algorithm and the propagator method (PM). Furthermore, the proposed algorithm can achieve automatically paired DOA and frequency estimation. Besides, it is applicable for nonuniform linear arrays. Effectiveness of the proposed algorithm is assessed by simulations.

scholarly journals Ambiguity Resolution in Direction of Arrival Estimation with Linear Antenna Arrays Using Differential Geometry

2022 ◽  
Vol 70 (1) ◽  
pp. 581-599
Author(s):  
Alamgir Safi ◽  
Muhammad Asghar Khan ◽  
Fahad Algarni ◽  
Muhammad Adnan Aziz ◽  
M. Irfan Uddin ◽  
...  
Keyword(s):  
Differential Geometry ◽  
Antenna Arrays ◽  
Ambiguity Resolution ◽  
Direction Of Arrival ◽  
Direction Of Arrival Estimation ◽  
Linear Antenna ◽  
Linear Antenna Arrays

scholarly journals An Efficient Adaptive and Steep-Convergent Sidelobes Simultaneous Reduction Algorithm for Massive Linear Arrays

Electronics ◽  
2022 ◽  
Vol 11 (2) ◽  
pp. 170
Author(s):  
Yasser Albagory ◽  
Fahad Alraddady
Keyword(s):  
Antenna Arrays ◽  
Reduction Process ◽  
Damping Factor ◽  
Reduction Algorithm ◽  
Sidelobe Level ◽  
Simultaneous Reduction ◽  
Linear Arrays ◽  
Power Pattern ◽  
Wireless Communications Systems ◽  
Linear Antenna Arrays

Antenna arrays have become an essential part of most wireless communications systems. In this paper, the unwanted sidelobes in the symmetric linear array power pattern are reduced efficiently by utilizing a faster simultaneous sidelobes processing algorithm, which generates nulling sub-beams that are adapted to control and maintain steep convergence toward lower sidelobe levels. The proposed algorithm is performed using adaptive damping and heuristic factors which result in learning curve perturbations during the first few loops of the reduction process and is followed by a very steep convergence profile towards deep sidelobe levels. The numerical results show that, using the proposed adaptive sidelobes simultaneous reduction algorithm, a maximum sidelobe level of −50 dB can be achieved after only 10 iteration loops (especially for very large antenna arrays formed by 256 elements, wherein the processing time is reduced to approximately 25% of that required by the conventional fixed damping factor case). On the other hand, the generated array weights can be applied to practical linear antenna arrays under mutual coupling effects, which have shown very similar results to the radiation pattern of the isotropic antenna elements with very deep sidelobe levels and the same beamwidth.

Sign in / Sign up

Export Citation Format

Share Document