GREST: Ghost Targets Removal Algorithm Using Multipath Angle Estimation

Abstract

In this paper, we propose an algorithm for the removal of ghost targets based on angle estimation termed GREST (Ghost targets Removal using ESTAR). In the proposed GREST, the tentative targets reports, including the azimuth angles, is obtained through the conventional 3-D coherent integrations and signal detection at first. Then two-way angles, defined as a combination of direction-of-arrival (DOA) and direction-of-departure (DOD), are estimated using the ESTAR (Estimation of Two-way Angle by MIMO Radar), which was proposed by the authors recently. Subsequently, the ghost targets are removed based on the estimated angles by comparing DOD and DOA to finalize the target reports. The ESTAR method represents a novel approach to angle estimation that yields unambiguous results, even in the case of MIMO radars with transmit sparse arrays, which are commonly utilized in the standard millimeter-wave radars. Based on these angles, it is possible to distinguish between direct and multipath propagation, thereby enabling the removal of ghost targets. In this paper, we will present the detail of the proposed GREST and demonstrate its effectiveness in removing ghost targets using experimental data acquired in a situation where multipath propagation is occurring.