ANC Feedback Filter Selection for Acoustic Leakage Control
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Acoustic feedback between a speaker and reference microphone in active noise cancellation systems is unstable due to varying feedback path characteristics, which affects the effectiveness of noise cancellation, especially in mobile devices where user-specific parameters and device properties influence the leakage path.
Innovation Solution
A noise control circuit with a feedback control unit that selects a filter from predetermined candidates based on error calculations to generate a feedback control signal, which is subtracted from the input signal, using a filter selection unit to determine the best candidate filter for reducing acoustic feedback.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If adaptive LMS algorithms are used to model the feedback path, then feedback control accuracy is improved, but system complexity and processing burden increase significantly
Solution Approach 1:
The patent pre-calculates and stores multiple candidate filters during a characterization stage before actual noise cancellation operation. These filters are prepared in advance based on different acoustic conditions, so that during real-time operation, the system only needs to select from the pre-computed filters rather than performing complex adaptive calculations, thus reducing processing burden while maintaining accuracy
Solution Approach 2:
The patent divides the feedback path modeling into multiple discrete candidate filters representing different acoustic conditions (e.g., different ear positions, hairstyles, device orientations). Instead of using a single complex adaptive model, the system segments the problem into multiple simpler pre-computed models that can be quickly selected based on current conditions
2Device complexity
If a single feedback filter is used, then device complexity is reduced, but adaptability to different users and usage conditions deteriorates
Solution Approach 1:
The patent creates a universal solution that works across multiple users and conditions by pre-computing a set of candidate filters that cover various acoustic scenarios. The system becomes multi-functional by being able to select from these diverse filters based on the current user and usage conditions, thus achieving broad adaptability without requiring complex real-time adaptation mechanisms
Solution Approach 2:
During a prior characterization stage, the system performs comprehensive measurements and stores multiple candidate filters that account for different users, hairstyles, device positions, and acoustic conditions. This preliminary preparation enables the system to adapt to various scenarios without requiring complex real-time adjustments
3Reliability
If acoustic feedback cancellation is implemented, then noise cancellation effectiveness is improved, but processing time and computational resources increase
Solution Approach 1:
The patent performs feedback path characterization and computes all candidate filters in advance during a setup stage. This preliminary action moves the computationally intensive work away from real-time operation, so that during actual noise cancellation, the system only needs to select from pre-computed filters, dramatically reducing processing time while maintaining effectiveness
Solution Approach 2:
The patent segments the feedback cancellation process into a pre-computation phase (characterization stage) and a real-time selection phase. By dividing the workload this way, the system can achieve accurate feedback cancellation without burdening the real-time processing resources
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 accuracy of feedback control while reducing the processing burden, providing a simple and effective method to address acoustic feedback by using a stored set of filters characterized during a prior stage, thereby improving noise cancellation performance.
Implementation Method 1
the anti-noise signal will not only propagate towards a user's ear Hde (where d denotes the driver and e denotes the ear), but may also propagate on a leakage path, or feedback path Hdm (where d denotes the driver/loudspeaker and m denotes the microphone), towards the reference microphone. This is known as acoustic feedback
Implementation Method 2
Active noise cancellation or control (ANC) refers to a method of reducing noise by the addition of an anti-noise—a phase inverted noise signal—which destructively interferes with the noise
Data Source
AI summary
The present application describes techniques for noise control which utilize a feedback control unit comprising a filter, derived from one or more predetermined filter candidates, for reducing or cancelling a feedback component of a noise control signal.