Compressed Sensing-Based DOA Estimation with Unknown Mutual Coupling Effect
Abstract
No abstract recorded for this item.
No abstract recorded for this item.
Sparse Bayesian learning (SBL) has given renewed interest to the problem of direction-of-arrival (DOA) estimation. It is generally assumed that the measurement matrix in SBL is precisely known. Unfortunately, this assumption may be invalid in practice due to the imperfect manifol
A novel sparse automotive multiple-input multiple-output (MIMO) radar configuration is proposed for low-complexity super-resolution single snapshot direction-of-arrival (DOA) estimation. The physical antenna effects are incorporated in the signal model via open-circuited embedded
In this paper, we propose a direction-of-arrival (DOA) estimation algorithm under unknown mutual coupling with a sparse linear array (SLA). We employ an SLA composed of two uniform linear arrays (ULA), and the element spacing of one of the subarrays is large enough to neglect the
A structured Least Square (LS) method for simultaneous estimation of the mutual coupling matrix (MCM) and direction of arrival (DOA) of signal source is proposed in this paper. Mutual coupling effects are modelled in the form of a complex Toeplitz matrix. The DOAs and MCM can be