Computationally Efficient Direction-of-Arrival Estimation Algorithms for a Cubic Coprime Array
Abstract
:1. Introduction
- (a)
- We propose a TA-MUSIC algorithm with CCA geometry to enable massive MIMOs to fully employ DOFs and achieve superior DOA estimation by employing both the auto-covariance matrix and the mutual covariance matrix of the entire array. In addition, we verify that by using the coprime property, the proposed algorithm can suppress the ambiguity problem.
- (b)
- We propose an E-MUSIC algorithm for 2D DOA estimation, which can effectively decrease the complexity of the classic MUSIC algorithm. After utilizing the ESPRIT algorithm to initialize and obtain a rough estimation, we then conduct a fine search within a smaller sector to achieve lower complexity.
- (c)
- Our numerical simulation results confirm that the proposed algorithms outperform the classical ESPRIT algorithm and the PM algorithm in DOA estimation.
2. Signal Model
3. Proposed Method for DOA Estimation
3.1. Review
3.2. TA-MUSIC Algorithm
3.3. The E-MUSIC Algorithm
3.4. Detailed Steps
4. Performance Analysis
4.1. Computational Complexity
4.2. Degree of DOF
4.3. Advantages
- The proposed TA-MUSIC performs better DOA estimations by employing all of the array information, including the auto-covariance matrix and the mutual covariance matrix, whereas E-MUSIC only utilizes the auto-covariance matrix information. In addition, TA-MUSIC can fully achieve DOFs of , while the algorithms in [34,35,36] only achieve DOFs. Furthermore, E-MUSIC can obtain DOFs, which are larger than .
- The proposed TA–MUSIC algorithm can attain paired angles automatically and outperforms the conventional ESPRIT and PM algorithms in DOA estimation performance.
4.4. Cramer–Rao Bound
5. Simulation Results
5.1. Comparison of the DOA Estimation Performance of Different Algorithms
5.2. RMSE with a Varying Number of Sensors
5.3. Resolution Performance
6. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
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Algorithm | Complex Multiplication | Running time |
---|---|---|
Classic MUSIC | 3406.7221 | |
TA-MUSIC | 7013.1121 | |
E-MUSIC | 0.00697637 |
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Gong, P.; Chen, X. Computationally Efficient Direction-of-Arrival Estimation Algorithms for a Cubic Coprime Array. Sensors 2022, 22, 136. https://doi.org/10.3390/s22010136
Gong P, Chen X. Computationally Efficient Direction-of-Arrival Estimation Algorithms for a Cubic Coprime Array. Sensors. 2022; 22(1):136. https://doi.org/10.3390/s22010136
Chicago/Turabian StyleGong, Pan, and Xixin Chen. 2022. "Computationally Efficient Direction-of-Arrival Estimation Algorithms for a Cubic Coprime Array" Sensors 22, no. 1: 136. https://doi.org/10.3390/s22010136