In this paper, a joint diagonalization based two dimensional (2D) direction of departure (DOD) and 2D direction of arrival (DOA) estimation method for a mixture of circular and strictly noncircular (NC) sources is proposed based on an L-shaped bistatic multiple input multiple output (MIMO) radar. By making full use of the L-shaped MIMO array structure to obtain an extended virtual array at the receive array, we first combine the received data vector and its conjugated counterpart to construct a new data vector, and then an estimating signal parameter via rotational invariance techniques (ESPRIT)-like method is adopted to estimate the DODs and DOAs by joint diagonalization of the NC-based direction matrices, which can automatically pair the four dimensional (4D) angle parameters and solve the angle ambiguity problem with common one-dimensional (1D) DODs and DOAs. In addition, the asymptotic performance of the proposed algorithm is analyzed and the closed-form stochastic Cramer–Rao bound (CRB) expression is derived. As demonstrated by simulation results, the proposed algorithm has outperformed the existing one, with a result close to the theoretical benchmark.
Based on the quaternion theory, a novel algorithm named non-circular augmented quaternion MUSIC (NCAQ-MUSIC) is proposed for DOA and range estimation of noncircular signals impinging on a concentered orthogonal loop and dipole (COLD) array. Firstly, based on the augmented quaternion, the proposed algorithm uses the noncircular characteristic of the signals to achieve the virtual array expansion; secondly, the DOA and range parameters can be completely separated in the principle of rank reduction, and finally, the parameters of DOA and range are estimated through one dimensional search. Compared with direct mutil-dimensional (M-D) searching algorithms, the proposed method merely requires several one-dimension (1-D) spectral peak search which does not need parameter pairing. Simulation results verify the performance promotion of the proposed approach.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.