scholarly journals Maximum Element Dichotomous Coordinate Descent Based Minimum Variance Distortionless Response DoA Estimator

Electronics ◽  
2021 ◽  
Vol 10 (23) ◽  
pp. 2966
Author(s):  
Zhi Quan ◽  
Yingying Zhang ◽  
Jie Liu ◽  
Yao Wang
Keyword(s):  
Computational Complexity ◽  
Estimation Error ◽  
Doa Estimation ◽  
Minimum Variance ◽  
Coordinate Descent ◽  
Recursive Least Squares ◽  
Numerical Comparison ◽  
Coordinate Descent Algorithm ◽  
Minimum Variance Distortionless Response ◽  
Field Programmable

In this paper, we devise an efficient approach for estimating the direction of arrival (DoA). The proposed DoA estimation approach is based on minimum variance distortionless response (MVDR) criteria within a recursive least squares (RLS) framework. The dichotomous coordinate descent algorithm is used to modify the calculation of the output power spectrum, and a diagonal loading term is applied to improve the robustness of the DoA estimator. These modifications allow us to both reduce the computational complexity of the RLS DoA estimator and increase the estimation performance. A numerical comparison confirms that the proposed DoA estimator outperforms the conventional RLS DoA estimator in terms of the computational complexity and DoA estimation error. Finally, the proposed theoretical DoA estimator is implemented on a field-programmable gate array (FPGA) board to verify the feasibility of the method. The numerical results of a fixed-point implementation demonstrate that the performance of the proposed method is very close to that of its floating-point counterpart.

scholarly journals An Efficient DOA Estimation Algorithm Based on Diagonal-Symmetric Loading

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Yangyang Xie ◽  
Biao Wang ◽  
Feng Chen
Keyword(s):  
Super Resolution ◽  
Estimation Algorithm ◽  
Doa Estimation ◽  
Minimum Variance ◽  
Spatial Spectrum ◽  
Estimation Accuracy ◽  
Minimum Variance Distortionless Response ◽  
Symmetric Loading ◽  
Subspace Processing ◽  
Source Number

In order to solve the problem that the subspace-like direction of arrival (DOA) estimation performs poor due to the error of sources number, this paper proposes a new super-resolution DOA estimation algorithm based on the diagonal-symmetric loading (DSL). Specifically, orthogonality principle of the minimum eigenvector of the specific covariance matrix and the source number estimation based on the improved K-means method were adopted to construct the spatial spectrum. Then, by considering the signal-to-interference-to-noise ratio (SINR), the theoretical basis for selecting parameters was given and verified by numerical experiment. To evaluate the effectiveness of the proposed algorithm, this paper compared it with the methods of minimum variance distortionless response (MVDR) and new signal subspace processing (NSSP). Experimental results prove that the proposed DSL has higher resolution and better estimation accuracy than the MVDR and NSSP.

scholarly journals Direction of Arrival Estimation using Conventional Subspace Algorithms

2019 ◽  
Vol 8 (9) ◽  
pp. 815-819
Keyword(s):  
Array Signal Processing ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Research Area ◽  
Minimum Variance ◽  
Spatial Spectrum ◽  
Basic Knowledge ◽  
Main Beam ◽  
Spectrum Estimation ◽  
Minimum Variance Distortionless Response

In recent times, Direction of Arrival (DOA) Estimation study earns attention in array signal processing and it develops rapidly in several application such as sonar, radar, communication, biomedicine and seismology measurements. The self adaption and spatial spectrum are the broad research area in array processing. The spatial spectrum estimation focused on the signal distribution in the space is received from all direction to receiver. To maintain accuracy in DOA estimation for the antenna array the basic knowledge is required for main beam, and side lobes pattern must be small to suppress signal from other direction. This paper discussed the overview of the Direction of Arrival (DOA) estimation based on classical Sum and delay beamformer, Minimum Variance Distortionless Response (MVDR) technique, Min Norm technique and Multiple Signal Classification(MUSIC) by using the spatial spectrum parameters.

scholarly journals In-Depth Exploration of Signal Self-Cancellation Phenomenon to Achieve DOA Estimation of Underwater Acoustic Sources

2019 ◽  
Vol 9 (3) ◽  
pp. 570 ◽  
Author(s):  
Fang Wang ◽  
Yong Chen ◽  
Jianwei Wan
Keyword(s):  
Estimation Method ◽  
Doa Estimation ◽  
Minimum Variance ◽  
Estimation Accuracy ◽  
Underwater Acoustic ◽  
Direction Estimation ◽  
Minimum Variance Distortionless Response ◽  
Acoustic Sources ◽  
Ocean Environment ◽  
Spatial Power Spectrum

In the ocean environment, the minimum variance distortionless response beamformer usually has the problem of signal self-cancellation, that is, the acoustic signal of interest is erroneously suppressed as interference. By exploring the useful information behind the signal self-cancellation phenomenon, a high-precision direction estimation method for underwater acoustic sources is proposed. First, a pseudo spatial power spectrum is obtained by performing unit circle mapping on the beam response in the direction interval. Second, the online calculation process is given for reducing the computational complexity. The computer simulation results show that the proposed algorithm can obtain satisfactory direction estimation accuracy under the conditions of low intensity of acoustic source, strong interference and noise, and less array snapshot data.

A Unitary-UCA-Root-MUSIC Algorithm Based on MSWF

2014 ◽  
Vol 610 ◽  
pp. 339-344
Author(s):  
Qiang Guo ◽  
Yun Fei An
Keyword(s):  
Computer Simulation ◽  
Computational Complexity ◽  
Real Time ◽  
Unitary Transformation ◽  
Wiener Filter ◽  
Doa Estimation ◽  
Signal Subspace ◽  
Music Algorithm ◽  
Multi Stage ◽  
Simulation Results

A UCA-Root-MUSIC algorithm for direction-of-arrival (DOA) estimation is proposed in this paper which is based on UCA-RB-MUSIC [1]. The method utilizes not only a unitary transformation matrix different from UCA-RB-MUSIC but also the multi-stage Wiener filter (MSWF) to estimate the signal subspace and the number of sources, so that the new method has lower computational complexity and is more conducive to the real-time implementation. The computer simulation results demonstrate the improvement with the proposed method.

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