In this paper, we statistically analyze the effect
of hardware impairments on power pattern of antenna array
systems. We consider a linear array and formulate the stochastic
beam pattern as a function of variations in phase, gain and
element positions. By deriving a closed-form expression for the
variance of the power pattern, we express how the performance
of antenna array can be degraded in each angle, allowing for
investigation of the role of each parameter in the final power
Estimation errors are incurred when calculating the sample space-time covariance matrix. We formulate the variance of this estimator when operating on a finite sample set, compare it to known results, and demonstrate its precision in simulations. The variance of the estimation links directly to previously explored perturbation of the analytic eigenvalues and eigenspaces of a parahermitian cross-spectral density matrix when estimated from finite data.
We address the problem of search-free DOA estimation from a single noisy snapshot for sensor arrays of arbitrary geometry, by extending a method of gridless super-resolution beam-forming to arbitrary arrays with noisy measurements. The primal atomic norm minimization problem is converted to a dual problem in which the periodic dual function is represented with a trigonometric polynomial using truncated Fourier series. The number of terms required for accurate representation depends linearly on the distance of the farthest sensor from a reference.
We present a novel localization method based on directional beams,
as available in novel massive MIMO transmission techniques instead
of radius information, and derive a least squares (LS) estimation
method. The new method is a direct LS method that can be solved by
a linear set of equations rather than an iterative method required for
radius information. In a further step, we also show how to transform
radius information into virtual beams to apply the proposed method.
Finally, we evaluate the accuracy of the new methods by simulations.
A modified nested linear array (MNLA) has been reported recently for a greater potential in increasing the degree-of-freedom. However, there exist some “holes” in the difference co-array, which results in missing “lags” and limited performance of direction-of-arrival (DOA) estimation. In order to tackle this problem, this paper applies a Toeplitz matrix completion technique to MNLA, and investigates the performance of DOA estimation on this basis. Particularly, a semidefinite program with trace minimization is derived to obtain the covariance matrix with Hermitian and Toeplitz structure.