Abstract
The unknown mutual coupling effect between antennas significantly degrades the target localization performance in the bistatic multiple-input multiple-output (MIMO) radar. In this paper, the joint estimation problem for the direction of departure (DOD) and direction of arrival (DOA) is addressed. By exploiting the target sparsity in the spatial domain and formulating a dictionary matrix with discretizing the DOD/DOA into grids, compressed sensing (CS)-based system model is given. However, in the practical MIMO radar systems, the target cannot be precisely on the grids, and the unknown mutual coupling effect degrades the estimation performance. Therefore, a novel CS-based DOD/DOA estimation model with both the off-grid and mutual coupling effect is proposed, and a novel sparse reconstruction method is proposed to estimate DOD/DOA with updating both the off-grid and mutual coupling parameters iteratively. Moreover, to describe the estimation performance, the corresponding Cramér–Rao lower bounds (CRLBs) with all the unknown parameters are theoretically derived. Simulation results show that the proposed method can improve the DOD/DOA estimation in the scenario with unknown mutual coupling effect, and outperform state-of-the-art methods.
Highlights
In multiple-input multiple-output (MIMO) radar systems [1,2], the independent waveforms are adopted in different transmitting antennas, so compared with the traditional array radars, the better performance of target estimation and detection can be achieved by using more spatial and waveform diversities [3,4,5]
Some studies [14,15,16,17] have proposed algorithms based on the multiple signal classification (MUSIC) and the estimation of signal parameters via rotational invariance techniques (ESPRIT) to estimate direction of departure (DOD)/direction of arrival (DOA) in MIMO radar systems
The orthogonal signals are affected by the mutual coupling effect, but we describe the corresponding effect by a matrix, and the non-orthogonality is transferred into the steering vectors by the mutual coupling matrix
Summary
In multiple-input multiple-output (MIMO) radar systems [1,2], the independent waveforms are adopted in different transmitting antennas, so compared with the traditional array radars, the better performance of target estimation and detection can be achieved by using more spatial and waveform diversities [3,4,5]. Some studies [14,15,16,17] have proposed algorithms based on the multiple signal classification (MUSIC) and the estimation of signal parameters via rotational invariance techniques (ESPRIT) to estimate DOD/DOA in MIMO radar systems These studies have not considered the mutual coupling between antennas in transmitter and receiver. The DOD/DOA estimation method with unknown mutual coupling is proposed in [19] Different from these present papers, we propose a novel method to estimate the DOD/DOA in the bistatic MIMO radar system, where the sparsity of targets has been exploited to improve the estimation performance. We consider the problem of estimating the DOD/DOA in the bistatic MIMO radar system with mutual coupling between antennas. A, and for a vector a, [ a]n denotes the n-th entry of a
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