Naoto Usami

Imaging devices for near-infrared wavelengths on silicon large scale integration (LSI) are very attractive for secure applications. We here demonstrate an LSI-compatible hybrid IR detector by integrating PbS quantum dots the surface of silicon.

We propose an arrayed test structure to assess the damages of metal-oxide-semiconductor field-effect transistors (MOSFETs) exposed under back-side LSI processes, such as by Focused Ion Beam (FIB). Back-side process with FIB is becoming essential to analyze and repair modern LSI chips, to avoid processing through many metal layers with dense wiring and dummy patterns. To access transistors from back-side, however, FET active region must be cropped out and that may cause damage to transistor characteristics. Our test structure consists of 2-D-arrayed MOSFETs. The impact by the back-side process on various conditions can be visualized as I-V characteristics change. The test structure was used with several FIB back-side processes and visualized the damages as threshold shift. The measurement indicated the importance of mixture of fast-and-isotropic etching and slow-and-anistoropic etching to miminimize electrical damage.

In this paper, we propose an effective wet snow mapping method with focus on the incident angle of microwave. Surface scattering is dominant for both wet snow and bare ground. However, it is expected that the characteristic of the wet snow scattering is different from the bare ground one according to the variation of dielectric constant. At the same time, surface scattering characteristics, especially depolarization, also depend on the incident angle. First, we evaluate numerically the degree of polarization of horizontal incident wave as an example with a simplified integral equation model (IEM). We also examine real data of full polarimetric synthetic aperture radar (PoISAR). The results shows that the degree of polarization depends on the difference of incident angles rather that of dielectric constants. Then we conduct wet-snow mapping by supervised learning with teacher areas for large / small incident angles and snow / bare ground. The mapping result agrees well with the estimation by optical data. It is found important to take into account the incident angle in snow mapping.

Previously, we have proposed a successful land classification method using a quaternion neural network (QNN) to process parameters based on Stokes vector representation. In this method. the activation function used in the QNN is anisotropic and is applied to input quaternions of which elements are separately and independently processed. In this paper, considering the isotropy of Poincare-sphere space, we propose a new isotropic activation function. Experimental results show that the QNN with the proposed activation function achieves more accurate land classification.

Reconfigurable circular-polarized antennas are expected to improve ground penetrating radars (GPRs) utilizing high-density arrayed and complexly switched antennas. This report presents a wideband reconfigurable circular-polarized single-feed antenna. It comprises a waveguide and a T-shaped probe. We switch its polarization type by changing the bias state of two PIN diodes on the "f-probe. Simulation results show that the 3-dB axial ratio bandwidth of the proposed antenna is 29% at 7.5GHz center frequency. The results also show that the main-polarized beam width is 70 degree in the 3-dB axial ratio bandwidth.