Mitsubishi Denki Kabushiki Kaisha

Panasonic Intellectual Property Management Co., Ltd.

Hitachi, Ltd.

Matsushita Electric Industrial Co., Ltd.

Panasonic Corporation

Nippon Paper Industries Co., Ltd.

Renesas Technology Corp.

Panasonic Intellectual Property Corporation of America

Taiyo Yuden Co., Ltd.

Hitachi Power Solutions Co., Ltd.

Sumitomo Rubber Industries Limited

Hitachi Medical Corporation

Lintec Corporation

Hitachi Engineering & Services Co., Ltd.

Hitachi Industrial Products, Ltd.

Takeshi Nakayama

Yasushi Terada

Naoki Honma

Shoichi Iizuka

Yoshikazu Miyawaki

Kazuo Kobayashi

Shinichi Kobayashi

Tomoshi Futatsuya

Nobuyuki Shiraki

Yoshiyuki Saito

Masanori Hayashikoshi

Dai Sasakawa

Masahiro Ishii

Mitsushi Abe

Tetsuo Fujigaki

Toshiyuki Asahi

Eiji Takahashi

Hiroshi Ikeda

Shinichi Tanimoto

Yukihiro Fukumoto

Kouichi Ishino

Natsuo Ajika

Osamu Shibata

Masaaki Mihara

Masanori Matsumoto

Yuichi Kunori

Yasushi Hayasaka

Motonobu Iizuka

Ryuya Ando

Hiroshi Onoda

Manabu Aoki

Daisaku Kitagawa

Atsushi Fukunaga

Masanori Takahashi

Satoshi Takaichi

Yoshihiro Yasui

Seiichi Nakatani

Takashi Morimoto

Koichi Hirano

Takeshi Fujii

Atsushi Ohba

Shinji Sato

Akira Nakajima

Seiji Karashima

Takashi Ichiryu

Kazumasa Ide

Yukihiro Ishimaru

Hideki Iwaki

Tousaku Nishiyama

Kenji Noguchi

Hiroshi Suenaga

Yoshimasa Yoshimura

Hiroyuki Watanabe

Makoto Ohi

Kazuo Nishihama

Kuniharu Osakabe

Koji Asai

Kosuke Takaki

Atsushi Fukumoto

Akihisa Miyazoe

Hiroshi Kanno

Takashi Kono

Takayuki Tsukamoto

Yoshiyuki Yamamoto

Akira Sugawara

Takashi Hashimoto

Kazuhiro Watanabe

Tsutomu Sakata

Masahiro Morita

Yasuhiro Sugaya

Tetsuyoshi Ogura

Atsushi Yamashita

Tomihiro Hashizume

Masaaki Harada

Takeshi Nakatani

Kazuhiro Eguchi

Hiroshi Tanaka

Takeshi Kajimoto

Tsuyoshi Ikushima

Masanari Koguchi

Naoki Komatsu

Masaaki Katsumata

Masaaki Endo

Takahiro Mabuchi

Makoto Matsumoto

Daisuke Kori

Katsumasa Miki

Shinji Kawai

Kohei Masuda

Nobuyuki Yamazaki

Masato Yamaguchi

Sumiko Miyazaki

Yasushi Inoue

Tomoo Chiba

Takafumi Kawasaki

Yoshiyuki Wasada

Yoshio Hamadate

Tsutomu Yamamoto

Junichi Shimamura

Yuji Osaki

A sensor includes: a complex transfer function calculator that calculates a complex transfer function representing propagation characteristics between each N transmission antenna element and each M reception antenna element, using radio waves transmitted as a reception signal in a space where at least one living body is present from each N transmission antenna element and received by each M reception antenna element; a spectrum calculator that: calculates likelihood spectra, each indicating a likelihood of presence of each living body, by an estimation algorithm for estimating the presence from living body information that is a living body component in the complex transfer function, using different values as the number of the at least one living body; and calculates an integrated spectrum by integrating the likelihood spectra calculated; and an estimator that estimates living body information indicating at least the number of living bodies, and outputs the living body information estimated.

Estimation device, estimation method, and recording medium

An estimation device includes: M transmission antenna elements each transmitting a first transmission signal; N transmitter-receivers each including a reception antenna element and receiving, over a predetermined period, a first reception signal including a reflection signal that is the first transmission signal reflected by a first living body, using the reception antenna element; a memory storing training signals that are second reception signals obtained by causing the N transmitter-receivers to preliminarily receive second reception signals including reflection signals that are second transmission signals transmitted from the M transmission antenna elements to a second living body and reflected therefrom; a first vector calculator calculating a first vector for each training signal and each first reception signal by respective predetermined methods; and a circuit identifying the first living body or estimating an orientation of the first living body by a predetermined method, using correlation coefficients calculated from the first vectors.

Estimation device and estimation method

A sensor includes: a living body component extractor that receives a signal transmitted from each transmitting station and influenced by a living body, and extracts a signal component influenced by the living body; a position spectrum function calculator that calculates as many position spectrum functions as the number of combinations of transmitting stations and receiving stations, the position spectrum functions each being calculated from the signal component and corresponding to a likelihood of a position of the living body; a weight function calculator that calculates as many weight functions as the number of combinations, the weight functions each representing reliability of a position spectrum function; an integrated position spectrum function calculator that outputs an integrated position spectrum function using the position spectrum functions and the weight functions; and a position estimator that estimates the position of the living body by detecting a maximum value from the integrated position spectrum function.

Sensor and position estimation method

A sensor includes: a complex transfer function calculator calculating complex transfer functions; a living body component extractor extracting living body information; a correlation matrix calculator calculating a target correlation matrix from the living body information; a noise information storage recording a noise correlation matrix; a first headcount information calculator calculating first headcount information that is a tentative number of persons present in the predetermined space, based on the target correlation matrix and a threshold calculated from the noise correlation matrix; a MUSIC spectrum calculator estimating position candidates for the living bodies, using the target correlation matrix, and outputting likelihood spectra indicating likelihoods of the respective living bodies being present in corresponding positions; and a second headcount information calculator estimating second headcount information that is a more accurate number of living bodies or positions from position information that is based on the likelihood spectra and can include the position candidates.

Sensor

A sensor includes: a correlation matrix calculator which calculates a correlation matrix from biological information extracted using reception signals obtained by receiving, in a predetermined period, signals transmitted to a predetermined space; a first number information calculator which calculates first number information; a MUSIC spectrum calculator which estimates a candidate of a position of at least one living body and outputs a likelihood spectrum; and a second number information calculator which estimates a position or second number information, which is a total number of living bodies with an increased degree of likelihood, from first position information possibly including a plurality of position candidates.

An estimation method is provided which includes: calculating a plurality of complex transfer functions, based on reception signals respectively received by N reception antenna elements during a predetermined period, the complex transfer functions each representing propagation characteristics between a transmission antenna element and the N reception antenna elements; extracting a variation component corresponding to each of the N reception antenna elements, from the calculated complex transfer functions, the variation component being caused by a living body; calculating a correlation matrix based on the variation component corresponding to each of the N reception antenna elements; calculating eigenvalues of the correlation matrix calculated in the calculating of the correlation matrix; and estimating the number of living bodies in a predetermined method, using the eigenvalues calculated in the calculating of the eigenvalues.

Estimation method, estimation device, and program

The present invention intends to provide an acid type carboxylated cellulose nanofiber having a high viscosity in a low shear region, or to provide an acid type carboxylated cellulose nanofiber having a very short fiber length, and the acid type carboxylated cellulose nanofiber has a carboxy group at least in part of a constituent unit constituting a cellulose molecular chain, wherein a viscosity of water dispersion with a content from 0.95 to 1.05% by mass is 400 Pa&#xb7;s or higher at a shear velocity from 0.003 to 0.01 sat 30&#xb0; C., or an average fiber length is from 50 to 500 nm and a ratio of fibers having a fiber length of 300 nm or shorter is 50% or higher.

Acid type carboxylated cellulose nanofiber

An estimating method includes: measuring and receiving reception signals including a reflected signal reflected by a moving body, for a first period equivalent to a cycle of movement of the moving body; calculating first complex transfer functions indicating propagation characteristics, from the reception signals measured in the first period; calculating second complex transfer functions having reduced components corresponding to fluctuations, from the first complex transfer functions; extracting moving body information corresponding to a component related to the moving body by extracting moving body information corresponding to a predetermined frequency range of the second complex transfer functions calculated; and estimating a direction in which the moving body is present using the moving body information.

Radar estimating method, device and medium to extract living body vector information

An estimation method includes: transmitting transmission signals using M transmission antenna elements; receiving reception signals by N reception antenna elements; calculating, from the reception signals, a first matrix whose components are complex transfer functions indicating propagation characteristics between the transmission antenna elements and the reception antenna elements; estimating, using the first matrix, a position and an orientation of a living body relative to an estimation device; when the estimated position is in a first identification region and the estimated orientation is in a predetermined range from a first direction, identifying the living body based on time waveforms of the reception signals and a first training signal which is obtained in advance in the first identification region and corresponds to the living body; and adding, as an identification region for identifying the first living body identified, a new identification region based on an estimated position of the first living body identified.

Estimation method and device to identify next position of a living body

An estimation method for estimating target region information relating to a target region by using an estimation device that estimates information including a position of a living body by using a radio wave includes: acquiring first information relating to lengths of a planar shape of the target region; acquiring second information relating to an installation state of a transmission antenna and a reception antenna included in the estimation device; acquiring third information relating to a trajectory defined by a plurality of positions of the living body estimated by the estimation device when the living body moves along a predetermined path in the target region; and performing at least one of (1) estimation of the planar shape by correcting the first information and (2) estimation of the installation state by correcting the second information based on the first, second, and third information acquired, as the estimation of the target region information.

Estimation method, estimation device, and recording medium

An estimation method according to the present disclosure includes: extracting, from a plurality of calculated complex transfer functions, living body components respectively corresponding to N reception antenna elements and affected by a living body; calculating a correlation matrix based on the extracted living body components respectively corresponding to the N reception antenna elements; computing one or more eigenvalues of the calculated correlation matrix; estimating a credibility of an estimation result of estimating the position or the direction of a living body in a target space, using the one or more computed eigenvalues and living body count information indicating a value indicating a total number of living bodies in the target space; and estimating the position or the direction of the living body via a predetermined method, based on the correlation matrix, according to the credibility of the estimation result.

A sensor includes: a transmission signal generator including N transmission antenna elements that respectively transmit N transmission signals to a predetermined range in which a living body is possibly present, where N is a natural number greater than or equal to 3; a receiver including M reception antenna elements that respectively receive N reception signals including one or more reflected signals, where M is a natural number greater than or equal to 3, the one or more reflected signals being one or more of the N transmission signals transmitted by the N transmission antenna elements that is reflected or scattered by the living body; circuitry; and memory. The circuitry estimates traveling of the living body, and/or the posture and/or action of the living body at the position of the living body.

Sensor, estimating device, estimating method, and recording medium

An estimating device includes: a transmission antenna; a transmission signal generator that generates a multicarrier signal; a transmitter that outputs the multicarrier signal to the transmission antenna; a reception antenna; a receiver that measures reception signals including a reflected signal which is the transmitted multicarrier signal that has been reflected or dispersed by the moving body; a complex transfer function calculator that calculates, from the measured reception signals, a plurality of complex transfer functions indicating propagation characteristics between a transmission antenna element and a reception antenna element; a moving body correlation matrix calculator that calculates, for each of subcarriers, a moving body correlation matrix from the complex transfer functions; a subcarrier integrator that integrates the moving body correlation matrices; and an estimation processor that estimates the direction or position in which the moving body is present, using the integrated moving body correlation matrix obtained by the integration.

Estimating device and estimating method

An estimation device includes: a living body information extraction unit that extracts living body information which is a component corresponding to one or more living bodies in a space; an eigenvector calculation unit that calculates one or more eigenvectors of a living body correlation matrix obtained from the living body information; a first position estimation unit that estimates, using the living body correlation matrix, positions of the one or more living bodies and at least one false image, according to a predetermined position estimation method; a second steering vector output unit that extracts, from first steering vectors stored in a storage, and outputs as second steering vectors, first steering vectors corresponding to the positions estimated; and a second position estimation unit that estimates at least one of the position and the number of the one or more living bodies, using the one or more eigenvectors and the second steering vectors.

Estimation device, living body count estimation device, estimation method, and recording medium

Complex transfer functions indicating characteristics of propagation between transmission antenna elements and N reception antenna elements are calculated from reception signals received by the N reception antenna elements during a predetermined period. Components affected by vital activity are extracted from the calculated complex transfer functions. A correlation matrix is calculated from changed components affected by vital activity. A steering vector for regions divided from a target region is calculated. A living-body signal intensity vector is estimated by performing compressed sensing for an unknown value that is the living-body signal intensity vector using a correlation matrix vector and an extended steering vector. The number of components constituting the living-body signal intensity vector and having a value of at least a predetermined threshold is estimated to be the number of living bodies, and positions of regions corresponding to the components are estimated to be estimated positions of the living bodies.

Estimating method and estimating device

Growing community of inventors

Hyogo, Japan

Takeshi Nakayama