Adaptive Noise Suppression Filter for Spectral Doppler Systems
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Solution Overview
Problem
Existing spectral Doppler systems face challenges in effectively reducing background noise, particularly as detection depth increases, leading to degraded image and audio quality, with existing noise reduction methods being either unreliable or costly.
Innovation Solution
A method and apparatus that involves obtaining a power spectrum of Doppler signals, estimating average noise power, and designing a noise suppression filter with filter coefficients based on this power spectrum and noise power to filter out noise in real-time, effectively reducing background noise.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If simple high-pass or low-pass filter is used to remove background noise, then device complexity is reduced, but noise reduction effectiveness deteriorates because spectral distribution of Doppler signals varies in each scan
Solution Approach 1:
The patent implements dynamic filter characteristics by calculating filter coefficients based on the actual spectral distribution of each scan. The filter adapts to varying spectral characteristics through real-time computation of power spectrum and noise power estimation, making the filter responsive to changing signal conditions rather than using fixed frequency cutoffs
Solution Approach 2:
The patent changes the parameters of the filter (specifically the filter coefficients) based on the measured spectral distribution and noise power. By dynamically adjusting these parameters according to the actual signal characteristics, the filter maintains effectiveness across varying spectral conditions without requiring complex structural modifications
2Reliability
If maximum frequency estimation method is used for noise reduction, then noise reduction can be achieved, but reliability deteriorates when maximum frequency estimation is inaccurate causing severe voice distortion
Solution Approach 1:
The patent employs feedback mechanisms by continuously estimating noise power and using it to adjust filter coefficients. The system monitors the spectral distribution and noise characteristics, then feeds this information back into the filter design process to maintain optimal noise reduction while protecting against distortion from inaccurate frequency estimates
Solution Approach 2:
The patent introduces noise power estimation as an intermediary parameter that mediates between the raw spectral data and the final filter coefficients. Rather than directly using maximum frequency estimates, the system uses noise power as an intermediate step to derive filter parameters, providing a more robust pathway that reduces sensitivity to estimation errors
3Length of moving object
If detection depth increases, then measurement capability is improved, but noise level increases causing degraded image and audio quality
Solution Approach 1:
The patent performs preliminary noise power estimation and spectral analysis before applying the filter to the actual Doppler signals. By characterizing the noise properties in advance and pre-calculating appropriate filter coefficients based on the expected spectral distribution, the system prepares the optimal filtering parameters before processing deep-tissue signals with high noise content
Data Source
AI summary
Present application provides a method for suppressing noise in a spectral Doppler system, comprising the steps of: obtaining a power spectrum of Doppler signals demodulated in the spectral Doppler system, by performing spectral analysis on the Doppler signals; estimating an average noise power of the spectral Doppler system; designing a noise suppression filter by determining its filter coefficients based on the power spectrum of the Doppler signals and the estimated average noise power; filtering the Doppler signals by using the designed noise suppression filter so as to reduce the noise.