Abstract
This paper focuses on the target detection in low-grazing angle using a hybrid multiple-input multiple-output (MIMO) radar systems in compound-Gaussian clutter, where the multipath effects are very abundant. The performance of detection can be improved via utilizing the multipath echoes. First, the reflection coefficient considering the curved earth effect is derived. Then, the general signal model for MIMO radar is introduced in low-grazing angle; also, the generalized likelihood test (GLRT) and generalized likelihood ratio test-linear quadratic (GLRT-LQ) are derived with known covariance matrix. Via the numerical examples, it is shown that the derived GLRT-LQ detector outperforms the GLRT detector in low-grazing angle, and both performances can be enhanced markedly when the multipath effects are considered.
Highlights
multiple-input multiple-output (MIMO) radar has gotten considerable attention in a novel class of radar system, where the term MIMO refers to the use of multiple-transmit as well as multiple-receive antennas
If we assume that covariance matrix Cc is known and according to [24], p(y | H0) and p(y | H1) are replaced by their Bayesian estimates, and, asymptotically, the generalized likelihood ratio test-linear quadratic (GLRT-LQ), extended to the MIMO case, is given by
This section is devoted to the performance assessment of the GLRT and GLRT-LQ detectors in low-grazing angle for MIMO radar, when the texture component of clutter distributed as gamma distribution, leading to the wellknown K clutter model
Summary
MIMO radar has gotten considerable attention in a novel class of radar system, where the term MIMO refers to the use of multiple-transmit as well as multiple-receive antennas. MIMO radar with widely separated antennas can capture the spatial diversity of the target’s radar cross section (RCS) [6] This spatial diversity provides the radar systems with the ability to support the improvement of the target parameter estimation [7, 8], high resolution target localization [9], and tracking performance [10]. For low-grazing angle detection of MIMO radar, the authors in [16] utilized the time reversal technique in a multipath environment to achieve high target detectability. We consider low-grazing angle target detection in compound-Gaussian clutter for MIMO radar. The compound-Gaussian clutter represents the heavy-tailed clutter statistics that are distinctive of several scenarios, for example, high-resolution or low-grazing angle radars in the presence of sea or foliage clutter [19, 20]. The generalized likelihood ratio test (GLRT) and generalized likelihood ratio test-linear quadratic (GLRT-LQ) are derived
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