Polynomial rooting-based parameter estimation for polarimetric monostatic MIMO radar

•The article discusses the ability of polarimetric multiple-input multiple-output (MIMO) radar to operate data in joint spatial and polarization domains.•The article explores the non-ideal factors that may exist in practical polarimetric MIMO radar and points out that many existing methods cannot handle these factors.•The article proposes a joint direction-of-arrival (DOA) and polarization parameter estimation method, termed PMS2, which incorporates the polarimetric manifold separation (PMS) technique and requires no pair matching or spectral peak searching procedures. The proposed PMS2 approach can perform joint DOA and polarization estimation for polarimetric MIMO radar with various non-ideal factors for an array, such as gain error, phase error, and position error.•The article provides the Cramér-Rao lower bound for the multi-dimensional parameters involved in the estimation problem.•The article presents simulation results that demonstrate the performance advantages of the proposed PMS2 approach, which is attributed to the compact structure of polarimetric transceivers and the ability of the PMS2 approach to handle the polarimetric properties of signals. Compared with conventional multiple-input multiple-output (MIMO) radar, polarimetric MIMO radar has been proven to hold the additional capability to operate data in the joint spatial and polarization domains. However, practical transceivers may involve antenna arrays with classical non-ideal factors (e.g., gain/phase/position errors) and polarimetric non-ideal factors (e.g., polarimetric antenna misorientation), and many current approaches cannot handle such non-ideal factors in real applications. In this study, polynomial rooting-based direction-of-arrival (DOA) and polarization parameter estimation is investigated for polarimetric monostatic MIMO radar with non-ideal transceivers. By incorporating the polarimetric manifold separation (PMS) technique, a joint DOA and polarization parameter estimation method, termed PMS2, is proposed with a closed-form solution. The Cramér-Rao bound for the multi-dimensional parameters involved in the estimation problem is also given. Simulation results demonstrate the performance advantages of the proposed PMS2 approach, which is attributed to the compact structure of polarimetric transceivers and the ability of the PMS2 approach to handle the polarimetric properties of signals.