Indoor 3-D Radar Imaging for Low-RCS Analysis

An original 3-D radar imaging system is presented for radar cross section (RCS) analysis, i.e., to identify and characterize the radar backscattering components of an object. Based on a 3-D spherical experimental setup, where the residual echo signal is more efficiently reduced in the useful zone, it is especially adapted to deal with low-RCS analysis. Due to a roll rotation, the electric field direction varies concentrically while the scattered data are collected. To overcome this issue, a specific 3-D radar imaging algorithm is developed. Based on fast regularization inversion, more precisely the minimum norm least squares solution, it manages to determine, from a single pass collection, three huge 3-D scatterer maps at once, which correspond to HH, VV, and HV polarizations at emission and reception. The algorithm is applied successfully to real X-band datasets collected in the accurate 3-D spherical experimental layout, from a metallic cone with patches and an arrow shape. It is compared with the conventional 3-D polar format algorithm where the scatterer information is irretrievably mixed-up.