Abstract
Two-dimensional direction-of-arrival (DOA) estimation in coprime planar array involves problems that the complexity of spectral peak search is huge and the noncircular feature of signals is not considered. Considering that unitary estimating signal parameters via rotational invariance techniques (Unitary-ESPRIT) is a low complexity subspace algorithm, an approach to estimate DOA fast for multiple signals is proposed in this paper. We first apply Unitary-ESPRIT to solve one possible value of each signal. Given the relationship between the ambiguous values and real values, we then have all possible values belonging to each subarray. Through finding the common values of two subarrays, we finally obtain the highly precise true DOAs. Moreover, when the signals are noncircular, we present an improved method using noncircular Unitary-ESPRIT, which is favorable in terms of accuracy and degree of freedom. Simulation results demonstrate the effectiveness of our proposed methods.
Highlights
Direction-of-arrival (DOA) estimation of multiple narrowband signals is a fundamental task in many applications such as radar [2], underwater acoustics [3, 4], indoor navigation [5, 6], and wireless communication [7]
We first analyze the computational complexity of the proposed method using Unitary-ESPRIT algorithm and compare it with the spectral peak search method based on 2D-MUSIC algorithm and partial spectrum search (PSS)
We assume that the impinging noncircular signals are BPSK modulation
Summary
Direction-of-arrival (DOA) estimation of multiple narrowband signals is a fundamental task in many applications such as radar [2], underwater acoustics [3, 4], indoor navigation [5, 6], and wireless communication [7]. We have proposed a method in [1], which uses the covariance matrix of coprime planar array to estimate a new covariance matrix with matrix completion theory This processing has much improved degree of freedom (DOF) bigger than the number of sensors, but the matrix completion costs much complexity and introduces the additional errors. It is meaningful that we propose a low complexity method for noncircular signals, which can utilize the noncircular feature to realize fast DOA estimation in coprime planar array. In order to avoid the high complexity cost by the spectral searching and utilize the signals features, in this paper, a fast DOA estimation method in coprime array for multiple signals is proposed. Throughout this paper, IN represents the N dimensional unit array; [∙]T and [∙]H denote transpose, and Hermitian transpose, respectively; diag[∙] represents a vector transforming to a diagonal matrix
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