Low-Frequency Equalization for Flat Bass With Reduced Latency
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Solution Overview
Problem
Existing sound systems struggle to provide uniform low-frequency performance across different listening positions in a room due to amplitude deviations caused by room acoustics, with current equalization techniques either failing to account for actual room characteristics or resulting in suboptimal solutions due to computational complexity and limited filter complexity.
Innovation Solution
A reduced latency low-frequency equalization system that uses microphones to measure impulse responses across various locations, calculates filter coefficients for subwoofers to produce flat frequency responses, and applies group delay equalization to minimize latency and sudden gains, thereby optimizing bass performance across the listening area.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If spatial averaging equalization is used to correct amplitude deviations, then low-frequency performance is improved at the average listening position, but performance at other listening positions deteriorates
Solution Approach 1:
The patent applies local quality by designing equalization filters tailored to specific listening positions rather than using a single spatial average. Each listening position receives customized filter coefficients that address its unique acoustic characteristics, ensuring optimal performance at multiple locations simultaneously
Solution Approach 2:
The patent segments the listening area into multiple discrete listening positions, each with its own equalization filter. This segmentation allows independent optimization for each position rather than compromising with an average solution that satisfies no position perfectly
2Measurement precision
If equalization filters are designed to flatten amplitude response, then frequency response uniformity is improved, but latency increases due to computational complexity
Solution Approach 1:
The patent changes the parameter of filter design by using measured impulse responses from actual listening positions to derive filter coefficients. This data-driven approach optimizes the balance between achieving flat frequency response and minimizing filter complexity, thereby reducing latency while maintaining accuracy
Solution Approach 2:
The patent replaces complex mechanical equalization adjustments with digital signal processing using measured impulse responses. By substituting physical trial-and-error adjustments with computational methods based on actual room measurements, the system achieves accurate equalization with reduced processing latency
3Measurement precision
If subwoofer output is increased to compensate for amplitude dips, then low-frequency coverage is improved, but distortion and peaks in other areas increase
Solution Approach 1:
The patent uses feedback by measuring the actual impulse responses at multiple listening positions and using these measurements to design equalization filters. This closed-loop approach ensures that compensation for amplitude dips is precisely targeted, avoiding over-compensation that would create distortion or unwanted peaks in other frequency ranges
Solution Approach 2:
The patent applies preliminary anti-action by pre-calculating equalization filters based on measured room acoustics before playback. The filters are designed to preemptively compensate for known amplitude dips without requiring excessive gain, thereby preventing distortion before it occurs
Data Source
AI summary
A frequency equalization system is provided that substantially equalizes the room frequency responses generated by at least one loudspeaker within a listening area so that the frequency responses in the listening area are substantially constant and flat within a desired frequency range with minimum signal latency. The frequency equalization system may use multiple microphones to measure the audio signals of one or more subwoofers to achieve an improved bass response that is flat across the relevant frequency range. The system employs an algorithm that is a closed-form, non-iterative, mathematical solution and features short computation time with reduced delays.