Phasor-Based SNR Evaluation for Radar Physiological Signal Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional methods for monitoring physiological signals like respiration and heartbeat using radar struggle with signal-to-noise ratio (SNR) measurement due to the lack of a well-defined signature in analog-modulated signals, leading to interference from environmental noise in complex environments.
Innovation Solution
The method involves combining multiple observations of a target volume based on weight assignments derived from phasor characteristics, using ultra-wideband (UWB) radar and multiple-input multiple-output (MIMO) systems with beam-forming techniques to distinguish and enhance physiological signals, while rejecting interference by aligning signals in the in-phase and quadrature (I/Q) channel plots and applying maximum-ratio-combining (MRC) based on SNR and arc fitting errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional radar methods are used to monitor physiological signals, then the system can detect signals in simple environments, but the signal-to-noise ratio deteriorates in complex environments due to environmental noise interference
Solution Approach 1:
The patent segments the received radar signal into multiple independent observations or snapshots of the target volume. Each observation is processed separately to extract phasor characteristics, and then combined using maximum-ratio-combining. This segmentation allows the system to distinguish between consistent physiological signals and random environmental noise, improving reliability in complex environments.
Solution Approach 2:
The patent merges multiple observations of the target volume by combining their phasor characteristics using maximum-ratio-combining (MRC). The MRC algorithm weights and combines the observations based on their signal-to-noise ratios, enhancing the physiological signal while suppressing environmental noise interference. This merging process improves the overall signal quality and detection reliability.
2Measurement precision
If multiple observations are combined to improve signal quality, then the signal-to-noise ratio improves, but the computational complexity increases due to weight determination and phasor processing
Solution Approach 1:
The patent transforms the raw radar observations into phasor domain representations, changing the parameter space from time-domain signals to complex phasor characteristics (amplitude and phase). This parameter transformation simplifies the subsequent combination process by enabling the use of maximum-ratio-combining based on phasor angles and magnitudes, improving measurement precision while managing computational complexity through efficient phasor arithmetic.
3Measurement precision
If phasor characteristics are used to determine weights for combining observations, then the physiological signal detection accuracy improves, but the difficulty of detecting and measuring increases due to the need for phasor analysis
Solution Approach 1:
The patent introduces phasor characteristics as an intermediary representation between the raw radar signal and the final physiological signal detection. By converting observations into phasor domain (complex numbers representing amplitude and phase), the system creates a convenient intermediate form that simplifies the weight determination and combination process. This intermediary representation makes the measurement process more tractable while maintaining high detection accuracy.
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
This approach enhances the robustness and reliability of physiological signal detection, reducing system noise and improving signal quality by distinguishing between human physiological signals and ambient noise, even in complex environments like offices and bedrooms.
Implementation Method 1
a radar-based physiological motion sensor that can assess the physiological and psychological state of a subject
Implementation Method 2
detecting and measuring physiological signals may benefit from a phasor approach to signal to noise ratio measurement evaluation
Data Source
Figure 1
Figure 2
Figure 3
AI summary
Various sensing systems may benefit from appropriate handling of signal to noise ratios. For example, detecting and measuring physiological signals may benefit from a phasor approach to signal to noise ratio measurement evaluation. A method can include obtaining a plurality of observations of a target volume. The method can also include determining a weight for each observation of the plurality of observations of the volume. The weight can be based on a change in phasor characteristics of the observation. The method can further include combining the plurality of observations based on the weight. The method can additionally include identifying a physiological signal based on the combined observations.