Compressed Sensing-Based DOA Estimation with Unknown Mutual Coupling Effect
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Sparse Bayesian Learning for DOA Estimation with Mutual Coupling
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
Sparse Automotive MIMO Radar for Super-Resolution Single Snapshot DOA Estimation With Mutual Coupling
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
DOA estimation and mutual coupling calibration with the SAGE algorithm
Sparse Bayesian Learning for DOA Estimation with Mutual Coupling
DOA Estimation with Sparse Array under Unknown Mutual Coupling
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
Simultaneous Estimation of Mutual Coupling Matrix and Doas Using Structured Least Square Method
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