Sensor System for Real-Time Living Body Position Tracking
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing techniques for detecting the position of a living body using radio signals suffer from delays due to the need to observe signals for several seconds corresponding to vital activities like respiration, leading to prolonged result times and difficulties in tracking moving targets.
Innovation Solution
A sensor system that includes transmission and reception antenna elements, calculates complex transfer functions using linear prediction to estimate the position of a living body with reduced delay, allowing for real-time tracking by generating and processing third complex transfer functions across different periods, and utilizing these to separate noise and vital activity components effectively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If signal observation is extended to cover several seconds corresponding to respiration cycles, then measurement precision of living body position is improved, but loss of time increases due to delay in obtaining estimation results
Solution Approach 1:
The system performs preliminary calculations of complex transfer functions during a first period and stores them for later use. During the second period, these pre-calculated functions are reused through linear prediction to generate position estimates without requiring fresh multi-second observations, thus reducing delay while maintaining accuracy
Solution Approach 2:
The system dynamically adapts the observation period length based on the need for accuracy versus speed. By using linear prediction to extrapolate from shorter observation windows, the system can flexibly balance between capturing sufficient respiration cycle information and providing timely position updates
2Reliability
If signal observation period is extended to capture vital activities, then reliability of detection is improved, but productivity decreases due to slower tracking of moving targets
Solution Approach 1:
Complex transfer functions are calculated in advance during a first period and stored for subsequent reuse. This preliminary computation enables rapid position estimation during the second period without requiring extended real-time observation, thus maintaining detection reliability while improving tracking speed
Solution Approach 2:
The system creates copies of complex transfer function data from the first period and uses linear prediction to generate estimated functions for the second period. This copying approach allows multiple position estimates to be generated quickly from a single set of observations, enhancing tracking capability
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 rapid and accurate estimation of a living body's position with reduced delay, even when the target is moving, by leveraging linear prediction and frequency-specific signal processing to enhance signal separation and tracking capabilities.
Implementation Method 1
M reception signals which have been received respectively by the M reception antenna elements and include reflection signals resulting from the transmission signals transmitted respectively from the N transmission antenna elements being reflected by the living body
Implementation Method 2
a second complex transfer function calculator which calculates second complex transfer functions during a second period that is not included in the first period by performing linear prediction onto the first complex transfer functions to estimate M×N complex transfer functions in time series
Implementation Method 3
a living-body component extractor which extracts, using the first complex transfer functions and the second complex transfer functions, a living-body component complex transfer function matrix belonging to a predetermined frequency range corresponding to components affected by one or more vital activities
Data Source
AI summary
A sensor receives M reception signals including reflection signals reflected by a living body; extracts a living-body component transfer function matrix from first complex transfer functions and second complex transfer functions, the first complex transfer functions being obtained by recording an M×N complex transfer function matrix including complex transfer functions in time series, from M reception signals, the complex transfer functions each indicating characteristics of propagation between a corresponding one of transmission antenna elements and a corresponding one of reception antenna elements, the second complex transfer functions being obtained by estimating and recording M×N complex transfer functions in a second period, and outputting a position at which a spectrum function indicating a likelihood that a living body is present indicates a local maximum value, using a correlation matrix based on the living-body component complex transfer function matrix and a steering vector corresponding to each of measurement-target regions.