Real-Valued DOA Estimation of Coprime Array via Toeplitz Construction-Based Spline Interpolation
Jingjing Pan, Qixuan Lu, Yide Wang, Meng Sun · IEEE Signal Processing Letters · 2026
Coprime array enables derivation of an extended array with the number of virtual elements beyond the number of physical sensors, resolving the underdetermined direction of-arrival (DOA) estimation problem while mitigating mutual coupling effects. However, the virtual array is discontinuous and contains some holes. To fully exploit the information of the virtual array, conventional methods typically employ complex matrix completion (MC) to iteratively recover the data of the covariance matrix, resulting in high complexity, particularly with large-scale coprime arrays. In this letter, a real-valued DOA estimation via the construction of Toeplitz covariance matrix and spline interpolation is proposed. The algorithm complexity is reduced by real-valued Toeplitz matrix, and then the holes are filled by spline interpolation. The recovered matrix can be used for DOA estimation by conventional subspace approaches. The superior computational performance of our approach is validated through comparative simulations with established methods.