Shisheng Guo

Micro-motion parameters estimation in non-Gaussian noise via mutual correntropy

This paper mainly considers the parameters estimation for the micro-motion targets embedded in non-Gaussian noise with the single input multiple output (SIMO) radar. A novel estimation algorithm based on mutual correntropy is presented to derive the micro perturbation parameters by exploiting the second and higher-order knowledge of the return signals among the multiple channels. Compared with conventional Fourier transform (FT) method, it has much higher signal to noise ratio (SNR) gain. In addition, the location is derived by employing the phase comparison monopulse (PCM) technique. Finally, several numerical results are provided and discussed.

A novel noncoherent localization approach for through-the-wall radar

In this paper, we consider the target localization problem in the presence of a wall using the through-the-wall radar, which equips one transmitter and multiple receivers. We propose a novel noncoherent localization approach, exploiting the advantages of both the ellipse-cross-localization and the hyperbolic-cross-localization. Performance of the proposed approach is evaluated via numerical simulations, and the results illustrate that it has much better positioning accuracy via geometric dilution of precision (GDOP) criterion.

Multipath ghosts location and sub-aperture based suppression algorithm for TWIR

In this paper, we consider the problem of multipath ghosts location and suppression using a through-wall imaging radar (TWIR). Specifically, first, in a SAR system, a multipath model in an enclosed room is derived. Second, based on this model, we develop a multipath ghosts location method and analyze the relationship between ghosts and the locations of antenna arrays. Then, we propose a suppression method based on sub-apertures, which exploits the different locations of multipath ghosts in sub-apertures and the fusion of sub-aperture imaging results. Finally, some simulation results are provided to show the validity and superiority of the proposed algorithm.