Abstract
In this paper, a robust angle estimator for uncorrelated targets that employs a compressed sense (CS) scheme following a fast greedy (FG) computation is proposed to achieve improved computational efficiency and performance for the bistatic MIMO radar with unknown gain-phase errors. The algorithm initially avoids the wholly computation of the received signal by compiling a lower approximation through a greedy Nyström approach. Then, the approximated signal is transformed into a sparse signal representation where the sparsity of the target is exploited in the spatial domain. Finally, a CS method, Simultaneous Orthogonal Matching Pursuit with an inherent gradient descent method, is utilized to reconstruct the signal and estimate the angles and the unknown gain-phase errors. The proposed algorithm, aside achieving closed-form resolution for automatically paired angle estimation, offers attractive computational competitiveness, specifically in large array scenarios. Additionally, the analyses of the computational complexity and the Cramér–Rao bounds for angle estimation are derived theoretically. Numerical experiments demonstrate the improvement and effectiveness of the proposed method against existing methods.
Highlights
The demanding requirements, the accuracies in location and the need for high resolutions for radar systems, have led to extensive attention to multiple-input multipleoutput (MIMO) radar [1]. e concept of the MIMO radar system is to instantaneously emit mutually orthogonal waveforms with multiple antennas while receiving the reflected echoes with multiple receive antennas
Different from the monostatic MIMO, bistatic MIMO radar structures a widely separated antenna distance between the transmitter and receiver positions, its ability to achieve an improved performance of target localization and detection [7]. is paper studies the angle estimation problem, considering a bistatic MIMO where the angles to the transmit and receive arrays are regular and dissimilar; referred to as direction of departure (DOD) and direction of arrival (DOA)
A compressed sense method through a fast greedy Nystrom approach to achieve a computationally efficient angle estimation with gain-phase error effect for the bistatic MIMO radar is presented in this paper
Summary
The demanding requirements, the accuracies in location and the need for high resolutions for radar systems, have led to extensive attention to multiple-input multipleoutput (MIMO) radar [1]. e concept of the MIMO radar system is to instantaneously emit mutually orthogonal waveforms with multiple antennas while receiving the reflected echoes with multiple receive antennas. En, Li et al [15] proposed a propitious reduced-dimension MUSIC procedure to achieve angle and gain-phase error estimations These subspace methods do not consider the additional characteristics of the received signals and only resort to distinguishing the noise subspaces. Different from others, we propose a robust algorithm that obtains the angle and antenna gain-phase error estimation for the bistatic MIMO radar. By formulating a diagonal matrix to describe the effect of the antenna array errors, the theoretical expression of the estimation of the gain-phase error is computed using the gradient descent method following signal reconstruction through a CS-based SOMP method.
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