Millimeter-Wave Beamforming Microphone Array for User Tracking
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Solution Overview
Problem
Current beamforming microphone arrays suffer from non-optimized beam forming parameters, leading to suboptimal beam position and coverage, and struggle to distinguish between voice and noise sources, resulting in audio dropouts and false positives.
Innovation Solution
Implementing a millimeter wave sensor system to determine user locations and adapt beamforming based on user positions, using adaptive beamforming circuits to optimize microphone array performance by adjusting beam width, angle, and range, and ignoring noise sources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If fixed beam positions are manually configured to cover likely user locations, then beam coverage area is improved, but beamforming performance deteriorates due to lower S/N ratio at significant distances
Solution Approach 1:
The patent implements dynamic beamforming that automatically adjusts beam positions and widths based on real-time detection of user locations using cameras and microphones. Instead of static pre-configured beams, the system continuously adapts beam parameters to track user movements and optimize signal capture, resolving the contradiction between coverage area and S/N ratio.
Solution Approach 2:
The system dynamically changes beamforming parameters (position, width, direction) based on detected user locations. When users are detected at specific positions, the beamforming algorithm adjusts parameters to concentrate gain in those directions, maintaining high S/N ratio while adapting coverage to actual user distribution rather than fixed predetermined areas.
2Adaptability or versatility
If dynamic beamforming algorithms are used to locate and adapt to talking users, then beamforming adaptability is improved, but false positives increase due to inability to distinguish voice from noise sources
Solution Approach 1:
The patent employs a multi-functional system that combines camera-based visual detection, microphone-based acoustic detection, and beamforming in a unified user identification framework. The system cross-references multiple data sources (visual presence, acoustic activity, spatial position) to confirm user identity and intent, reducing false positives while maintaining high adaptability to genuine user needs.
Solution Approach 2:
The system implements feedback loops where beamforming output is continuously monitored and fed back to the user detection algorithms. When noise sources are identified as false positives, the system adjusts detection thresholds and beamforming parameters accordingly, creating a self-correcting mechanism that reduces false positives while preserving adaptability to legitimate users.
3Area of stationary object
If beam width is increased to cover more user positions, then coverage area is improved, but audio clarity deteriorates due to reduced focus on specific users
Solution Approach 1:
The system dynamically adjusts beam width based on the number and distribution of detected users. When few users are present, beams are narrow and focused for high audio clarity. When multiple users are detected across different positions, the system creates multiple targeted beams or adjusts widths appropriately, maintaining clarity for each user while providing comprehensive coverage.
Solution Approach 2:
The patent implements spatially varying beam characteristics where different beam regions have different properties optimized for local conditions. Each beam is tailored to its specific target user with appropriate width and gain, rather than using a uniform beam pattern. This allows high audio clarity for individual users while maintaining coverage of multiple positions through coordinated multiple beams.
4Area of stationary object
If manual computer setup is used to configure beam positions, then initial beam coverage is improved, but system complexity and setup time increase
Solution Approach 1:
The patent implements self-service automatic configuration where the system uses its own cameras and microphones to detect user positions and automatically configure optimal beamforming parameters during initial setup and ongoing operation. No external computer or manual configuration is needed - the system performs its own calibration and optimization, reducing setup complexity while maintaining effective coverage.
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
Enhances audio clarity by focusing on specific user locations, reducing noise interference, and maintaining consistent audio quality even with user movement, while also controlling room functions like lighting and temperature.
Implementation Method 1
determine user locations... using adaptive beamforming circuits
Implementation Method 2
millimeter wave sensor system
Data Source
AI summary
A method for operating a beamforming microphone array for use in a predetermined area is provided herein, the method comprising: receiving acoustic audio signals at each of a plurality of microphones, converting the same to an electrical mic audio signal, and outputting each of the plurality of electrical mic audio signals; generating a user location data signal by a wave sensor system, and outputting the user location data signal, wherein the user location data signal includes location information of one or more people within the predetermined area; receiving both the user location data signal and plurality of echo-corrected mic audio signals at an adaptive beamforming device; and adapting one or more beams by the adaptive beamforming device based on the user location data signal and plurality of mic audio signals wherein each of the one or more beams acquires sound from one or more specific locations in the predetermined area.