Abstract
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.
Highlights
A multiple input multiple output (MIMO) radar can provide increased degrees of freedom by exploiting waveform diversity, with an enhanced performance for spatial resolution, parameter estimation, and target detection [1,2,3,4,5,6,7]
For MIMO radar systems based on planar arrays, a method for joint estimation of 2D-direction of departure (DOD) and 2D-direction of arrival (DOA) was presented in references [16,17,18] by transforming the four dimensional (4D) angle estimates into four 1D estimates without any pairing procedures
For a more general situation with the coexistence of noncircular and circular signals, estimating signal parameter via rotational invariance techniques (ESPRIT) and unitary ESPRIT were employed in reference [26] for MIMO radar; no theoretical error performance analysis was provided for the proposed method, and the derived stochastic Cramer–Rao bound (CRB) does not have a closed-form expression
Summary
A multiple input multiple output (MIMO) radar can provide increased degrees of freedom by exploiting waveform diversity, with an enhanced performance for spatial resolution, parameter estimation, and target detection [1,2,3,4,5,6,7]. Joint diagonalization-based ESPRIT method was presented in reference [15], where a closed-form expression for both DOA and DOD was obtained and automatically paired. For MIMO radar systems based on planar arrays, a method for joint estimation of 2D-DOD and 2D-DOA was presented in references [16,17,18] by transforming the four dimensional (4D) angle estimates into four 1D estimates without any pairing procedures. For a more general situation with the coexistence of noncircular and circular signals, ESPRIT and unitary ESPRIT were employed in reference [26] for MIMO radar; no theoretical error performance analysis was provided for the proposed method, and the derived stochastic Cramer–Rao bound (CRB) does not have a closed-form expression. Denote the real and imaginary parts; diag(·) denotes the diagonal matrix; blkdiag(·) represents the generation of a block diagonal matrix; ⊗ and are the Kronecker and Hadamard products, respectively; Ik denotes the k-dimensional identity matrix; γk represents the k-dimensional exchange matrix; 0k×l and 1k×l denote the k × l zero matrix and all-one matrix, respectively; arg(·) is the phase operation; and tr(·) represents the trace of a matrix
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