A Direction-Finding Algorithm for Electromagnetic Vector Sensor MIMO Radar Based on Parallel Factor Decomposition
Most existing electromagnetic vector sensor multiple-input multiple-output(EMVS-MIMO)radars restrict the distribution of transceiver array elements.The resolution of radar direction measurement is limited due to half-wavelength constraints.To address this limitation,this paper proposes an algorithm based on the parallel factor(PARAFAC)decomposition for two dimension(2D)angle estimation of the target.The algorithm is applicable to arbitrary transmitter array geometries and sparse receiver array geometries.First,a third-order PARAFAC tensor model is constructed for the matched-filtered signal of the receiving array.Second,the PARAFAC decomposition is utilized to estimate the transmit direction,receive direction,and composite factor matrix.Finally,a closed-form solution for high-resolution,ambiguity-free 2D angle estimation of the target is obtained by combining the rotationally invariant method,the vector outer product method and the least squares method.The proposed algorithm is characterized by high accuracy and low computational complexity.Computer simulations verify the tensor decomposition-based algorithm can be applied to an arbitrary dual-base EMVS-MIMO radar model,and can accurately estimate the 2D angular parameters of multiple targets.This validation demonstrates the effectiveness and superiority of the proposed algorithm.
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