More accuracy approach for signal subspace-based algorithms in bistatic EMVS-MIMO radar

This article proposed an improved signal subspace-based approach for parameter estimation in the bistatic multiple-input multiple-output radar system with an electromagnetic vector sensor (EMVS). In the proposed method, we recovered the joint transmit–receive polarization steering vector from the entire signal subspace using least squares by exploring the property of the Kronecker product and then recovered the transmit or receive polarization steering vector by position average process. We also proved that, in the recovered transmit polarization vector, the receive polarization parameters do not affect the estimation of the transmit polarization parameters. The same applies to the receive polarization vectors. Finally, the azimuth angle and polarization parameters are estimated using the ‘Vector Cross-Product’ and the least-squares strategy. The improved parameter estimation approach can realize automatic parameter pairing and have a better parameter estimation performance than the previous corresponding algorithms when it works on the subspace obtained in different ways since the proposed method uses the whole signal subspace instead of a part of the signal subspace to estimate the parameters. Simulation results verify the performance improvement of the proposed algorithm.