华中科技大学学报（自然科学版）2026，Vol.54Issue(3)：124-130,7.DOI:10.13245/j.hust.250332
基于增强型tCADiS的原子范数最小化DOA估计
DOA estimation based on augmented tailored coprime array with displaced subarrays via atomic norm minimization
摘要
Abstract
To address the issue of limited degrees of freedom(DOF)caused by the excessive number of voids in virtual array elements within the coprime array,an atomic norm minimization localization method utilizing augmented tailored coprime array with displaced subarrays(AtCADiS)was proposed to attain greater DOF for precise localization.The「M/2」 sensors were strategically positioned on the tailored coprime array with displaced subarrays(tCADiS),after which the first sensor of the tCADiS was shifted to the right by N units to prolong the continuous lags of the tCADiS.Acquire the received signal via the array and employ the array interpolation technique to create a virtual uniform linear array.Within the gridless architecture,the Toeplitz covariance matrix was recreated utilizing interpolated virtual array signals to address the atomic norm minimization problem for the corresponding virtual measurement vector.The source angle was solved using spatial spectrum algorithm.Finally,the performance of the proposed AtCADiS was compared to other generalized coprime arrays,with experimental results indicating enhanced localization accuracy,superior convergence,and a significant reduction in experimental runtime under conditions of fewer snapshots and a lower signal-to-noise ratio(SNR).关键词
广义互质阵列/阵列插值/无网格/原子范数最小化/DOA估计Key words
generalized coprime arrays/virtual array interpolation/gridless/atomic norm minimization/direction of arrival estimation分类
信息技术与安全科学引用本文复制引用
何继爱,李冠男..基于增强型tCADiS的原子范数最小化DOA估计[J].华中科技大学学报（自然科学版）,2026,54(3):124-130,7.基金项目
国家自然科学基金资助项目(62361040). （62361040）
