Direction-of-arrival estimation of a single distorted wavefront with time-variant amplitude

Abstract: Direction-of-arrival (DOA) estimation algorithms in array processing applications have been developed under time-invariant wavefronts. In most applications this assumption is not realistic due to the nonhomogeneous propagation medium which can distort the wavefront received by the array. This paper extends the author’s previous work on signal-to-noise ratio (SNR) estimation, in developing a novel approach for estimating the DOA of a single narrow-band amplitude-distorted wavefront received by an arbitrary antenna array. The distorted-amplitude wavefront is assumed to vary according to the first order autoregressive AR(1) model with unknown coefficients. An approximate maximum-likelihood-based (ML-based) approach to estimate the DOA parameter is developed in the high SNR scenario. Compared with the classical ML method that requires computationally prohibitive multi-dimensional search, the proposed approach obtains the DOA estimate by maximizing a new cost function with respect to a single DOA parameter derived using Markov property of the AR(1) process. Compact CramérRao lower bound (CRB) expressions for DOA parameter are derived for different kinds of time-varying fading amplitudes. High and low SNR approximation expressions for the CRB are also derived, that enable the derivation of a number of CRB properties. Finally, simulation results show the performance of the proposed estimator and validate the theoretical analysis.