NOISE REMOVAL TECHNIQUE IN NEAR-FIELD MILLIMETER-WAVE CYLINDRICAL SCANNING IMAGING SYSTEM

Abstract

The accuracy of scattering measurements in near-field millimeter-wave cylindrical scanning imaging system is often degraded by the contamination from additive noise and clutter. Thus, efficient noise and clutter removal technique is necessary to achieve accuracy improvement. This paper proposes an independent component analysis denoising algorithm, which relies on the assumption of statistical independence of the sources, where high order statistical properties are used. In the algorithm, the virtual noise components are incorporated into the independent component analysis model, which expands original one-dimensional observation to virtual multi-dimensional observations. The computationally efficient sources estimation technique is presented, based on the joint diagonalization of fourth order cumulant matrix. The high speed millimeter-wave near-field cylinder scanning imaging system is set up to verify the denoising results in the range profiles, three-dimensional scatter intensity and two-dimensional projection images. Compared with three different noise models, the results indicate that the denoising algorithm shows both feasibility and validity in the near-field millimeter-wave cylindrical scanning imaging system.