TY - JOUR
T1 - DePattern
T2 - A Search-Free DOA Estimation Algorithm With High Precision for Coprime Arrays
AU - Tian, Xinyang
AU - Gao, Yixuan
AU - Ke, Sheng
N1 - Publisher Copyright:
© 2001-2012 IEEE.
PY - 2025
Y1 - 2025
N2 - Direction-of-arrival (DOA) estimation using coprime linear arrays has garnered significant attention thanks to its low design complexity and exceptional performance, yet the failure to satisfy the half-wavelength assumption introduces a phase ambiguity problem that remains insufficiently analyzed in existing literature. In this article, we introduce the concept of root-MUSIC match pattern to visualize the DOA estimation challenges associated with coprime arrays, enabling a more intuitive analysis of the various phase ambiguities through geometric analysis. The term “DePattern” refers to the algorithms and analyses developed based on the root-MUSIC matching pattern (RMMP) framework. Leveraging RMMP, we propose a search-free DOA estimation algorithm that avoids angle search and anti-ambiguity search while thoroughly resolving the ambiguity problem inherent in coprime arrays. The algorithm further constructs a minimum mean-square-error (MMSE) estimator and implements adaptive calculation of the estimator weights. This adaptive weighting allows the proposed algorithm to optimize the estimation performance while maintaining computational efficiency. Furthermore, the MMSE estimator also provides convenience for subsequent performance analysis. Simulation results validate the theoretical analysis and demonstrate the effectiveness of the proposed anti-phase ambiguity algorithm. Compared to existing methods, the proposed algorithm achieves estimation accuracy comparable to full-array-based algorithms while maintaining the low computational complexity at the level of the subarray-based algorithm.
AB - Direction-of-arrival (DOA) estimation using coprime linear arrays has garnered significant attention thanks to its low design complexity and exceptional performance, yet the failure to satisfy the half-wavelength assumption introduces a phase ambiguity problem that remains insufficiently analyzed in existing literature. In this article, we introduce the concept of root-MUSIC match pattern to visualize the DOA estimation challenges associated with coprime arrays, enabling a more intuitive analysis of the various phase ambiguities through geometric analysis. The term “DePattern” refers to the algorithms and analyses developed based on the root-MUSIC matching pattern (RMMP) framework. Leveraging RMMP, we propose a search-free DOA estimation algorithm that avoids angle search and anti-ambiguity search while thoroughly resolving the ambiguity problem inherent in coprime arrays. The algorithm further constructs a minimum mean-square-error (MMSE) estimator and implements adaptive calculation of the estimator weights. This adaptive weighting allows the proposed algorithm to optimize the estimation performance while maintaining computational efficiency. Furthermore, the MMSE estimator also provides convenience for subsequent performance analysis. Simulation results validate the theoretical analysis and demonstrate the effectiveness of the proposed anti-phase ambiguity algorithm. Compared to existing methods, the proposed algorithm achieves estimation accuracy comparable to full-array-based algorithms while maintaining the low computational complexity at the level of the subarray-based algorithm.
KW - Coprime array
KW - direction-of-arrival (DOA) estimation
KW - grating angle problem
KW - joint performance optimization
KW - phase ambiguity
UR - https://www.scopus.com/pages/publications/105002765226
U2 - 10.1109/JSEN.2025.3558578
DO - 10.1109/JSEN.2025.3558578
M3 - Article
AN - SCOPUS:105002765226
SN - 1530-437X
VL - 25
SP - 19759
EP - 19775
JO - IEEE Sensors Journal
JF - IEEE Sensors Journal
IS - 11
ER -