Polarimetric synthetic aperture radar is expected to distinguish wet snow from bare ground. However, since both of them show surface scattering, which is sensitive to incidence angle, it often fails in the distinction in mountainous areas. In this letter, we propose an adaptive distinction method using quaternion neural networks. In the ALOS-2 data, we find a monotonic and nonlinear dependence of the degree of polarization on the incidence angle. Then, we feed multiple-incidence-angle teacher information in the learning process. The distinction results of the proposal present higher accuracy than those of the conventional Wishart distinction and a quaternion neural network without the incidence angle information.
Yuki Okamoto, Ayako Mizushima, Naoto Usami, Jun Kinoshita, Akio Higo, Yoshio Mita
2019 IEEE 32ND INTERNATIONAL CONFERENCE ON MICROELECTRONIC TEST STRUCTURES (ICMTS), 2019
We assessed potential degradation of MOSFET characteristics induced by post-processing of extra bond pads. The pads are used as stable electrical connections in repairing and test. The test structure consists of 16×16 arrayed PMOSFETs designed with 0.6 μm CMOS technology. An aluminum pad is deposited on the arrayed structure using a silicon shadow mask, and wire bonding is performed subsequently. The characteristics of Id-Vg were compared before and after the post-process. The result indicates that the post-processing does not affect the characteristics of MOSFETs, and therefore it can be used to place post-processed bond pads over an LSI chip.
International Conference on Optical MEMS and Nanophotonics, Sep 26, 2017, IEEE Computer Society
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.
2017 INTERNATIONAL CONFERENCE ON OPTICAL MEMS AND NANOPHOTONICS (OMN), 2017, IEEE
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.
Naoto Usami, Jun Kinoshita, Rimon Ikeno, Yuki Okamoto, Masaaki Tanno, Kunihiro Asada, Yoshio Mita
2017 INTERNATIONAL CONFERENCE OF MICROELECTRONIC TEST STRUCTURES (ICMTS), 2017, IEEE
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.
2016 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2016, IEEE
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.