Abstract
Direction of arrival (DOA) estimation is an essential problem in the radar systems. In this paper, the problem of DOA estimation is addressed in the multiple-input and multiple-output (MIMO) radar system for the fast-moving targets. A virtual aperture is provided by orthogonal waveforms in the MIMO radar to improve the DOA estimation performance. Different from the existing methods, we consider the DOA estimation method with only one snapshot for the fast-moving targets and achieve the super-resolution estimation from the snapshot. Based on a least absolute shrinkage and selection operator (LASSO), a denoise method is formulated to obtain a sparse approximation to the received signals, where the sparsity is measured by a new type of atomic norm for the MIMO radar system. However, the denoise problem cannot be solved efficiently. Then, by deriving the dual norm of the new atomic norm, a semidefinite matrix is constructed from the denoise problem to formulate a semidefinite problem with the dual optimization problem. Finally, the DOA is estimated by peak-searching the spatial spectrum. Simulation results show that the proposed method achieves better performance of the DOA estimation in the MIMO radar system with only one snapshot.
Highlights
Direction of arrival (DOA) estimation is an essential problem in the radar systems
Based on a least absolute shrinkage and selection operator (LASSO), a denoise method is formulated to obtain a sparse approximation to the received signals, where the sparsity is measured by a new type of atomic norm for the multiple-input and multiple-output (MIMO) radar system
The discrete Fourier transform (DFT) [19] is used to estimate the DOA, where the received signals are sampled by the antennas in the spatial domain, and the DOA estimation is equal to a corresponding frequency estimation in the transformed domain. erefore, the frequency (DOA) in the spatial domain is obtained by the DFT methods, but the resolution of DFT method is limited by Rayleigh criterion. e methods that can break through the Rayleigh criterion are called super-resolution methods
Summary
Received 11 October 2019; Revised 28 December 2019; Accepted 14 January 2020; Published 16 March 2020. The problem of DOA estimation is addressed in the multiple-input and multiple-output (MIMO) radar system for the fast-moving targets. Based on a least absolute shrinkage and selection operator (LASSO), a denoise method is formulated to obtain a sparse approximation to the received signals, where the sparsity is measured by a new type of atomic norm for the MIMO radar system. E compressed sensing- (CS-) based methods have been proposed [29, 30] to improve the DOA estimation performance with fewer measurements, where the target sparsity is exploited in the spatial domain [31,32,33,34,35]. En, by exploiting both the structure of the MIMO radar system and the target sparsity in the spatial domain, a new type of atomic norm is proposed to obtain the trade-off between the target sparsity and the reconstructed signals. R{a} denotes the real part of a complex value. (·)H denotes the Hermitian transpose of a complex matrix/vector
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