Living Body Estimation via Integrated Likelihood Spectra
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Solution Overview
Problem
Existing algorithms for detecting target objects require the number of target objects to be known, making it impossible to detect objects when the number is unknown.
Innovation Solution
An estimation device that calculates a complex transfer function representing propagation characteristics between transmission and reception antenna elements, uses likelihood spectra to estimate the presence of living bodies, and integrates these spectra to estimate the total number of living bodies present.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing detection algorithms are used, then detection capability is achieved, but the number of target objects must be known in advance
Solution Approach 1:
The patent segments the detection process into multiple independent stages: first calculating the complex transfer function from MIMO channel measurements, then computing likelihood spectra for different target numbers, integrating these spectra, and finally estimating the target number from the integrated spectrum. This segmentation allows each stage to be optimized independently and avoids the need for a single complex algorithm that requires prior knowledge of target numbers.
Solution Approach 2:
The patent changes the parameter being measured from direct target detection to likelihood spectrum analysis. By computing likelihood spectra for different target numbers and integrating them, the system transforms the detection problem into a parameter estimation problem that can be solved without knowing the target number in advance, thereby resolving the contradiction between detection accuracy and algorithm complexity.
2Adaptability or versatility
If the number of target objects is unknown, then adaptability is improved, but detection capability deteriorates
Solution Approach 1:
The patent performs preliminary calculations of likelihood spectra for multiple possible target numbers before making the final estimation. By pre-computing the likelihood spectra for different target numbers and integrating them, the system prepares all necessary information in advance, enabling reliable detection even when the actual target number is unknown. This preliminary action ensures detection reliability while maintaining adaptability.
Solution Approach 2:
The patent uses the integrated spectrum as feedback to estimate the target number. The likelihood spectra for different target numbers are computed and integrated, then the integrated spectrum is analyzed to determine which target number assumption produces the most consistent results. This feedback mechanism allows the system to adapt to unknown target numbers while maintaining high detection reliability.
3Measurement precision
If multiple antenna elements are used, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent makes the MIMO antenna system multi-functional by using it for both channel measurement and target detection. The same N transmission antennas and M reception antennas are used to obtain channel measurements, which are then processed to calculate the complex transfer function for target detection. This universality allows the system to achieve high measurement precision without proportionally increasing device complexity, as the antenna system serves multiple purposes.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables the estimation of living body information, including the number and positions of living bodies, even when the number of living bodies is unknown, with higher accuracy and without requiring prior knowledge of the number of objects.
Implementation Method 1
a complex transfer function calculator that calculates a complex transfer function representing propagation characteristics between each of N transmission antenna elements and each of M reception antenna elements, using radio waves that are transmitted in space as a reception signal
Implementation Method 2
PTL 1 discloses the capability of analyzing the eigenvalues of Doppler shift components included in wirelessly received signals
Data Source
AI summary
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.