Subspace methods for self-calibration of ULAs with unknown mutual coupling: A false-peak analysis

摘要

Self-calibration can mitigate the adverse effect of array imperfections in direction-of-arrival (DoA) estimation. In this paper, we consider self-calibration of uniform linear arrays (ULAs) with unknown mutual coupling and focus on subspace-based methods. By modeling the effect of mutual coupling through complex symmetric Toeplitz matrices, we first analyze its influence to existing subspace methods. Our analytical results illustrate that mutual coupling can induce false peaks in spatial spectra of these methods, and more importantly, most of these peaks are predictable. Based on the analytical results, we then propose new spectra to suppress these predictable false peaks, and new self-calibration algorithms for the proposed spectra. Simulations are performed to validate our analytical results and to illustrate the advantages of the proposed algorithms.