Microphone Array Sound Source Location via Time Difference Synchronization
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Solution Overview
Problem
Current systems for detecting and locating sounds in environments, such as those used in autonomous vehicles, face challenges in accurately distinguishing source sounds from background noise, particularly in noisy conditions, which can lead to inaccurate sound source identification and location determination.
Innovation Solution
A computer-implemented method utilizing a microphone array that synchronizes sound data based on time differences between receipt of source and background sounds across multiple microphones, generating an amplified source sound and determining its location to produce control signals for autonomous vehicle actions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional single microphone or simple audio processing is used, then device complexity is low, but measurement precision of sound source location is insufficient
Solution Approach 1:
The system divides the audio detection task into multiple independent microphone channels, each capturing sound from different spatial positions. By segmenting the detection function across multiple sensors arranged in an array, the system achieves improved location precision through spatial differentiation while managing complexity through modular processing of individual channel signals
Solution Approach 2:
The patent transitions from single-point audio detection to multi-dimensional spatial audio detection by arranging microphones in a two-dimensional array configuration. This dimensional expansion enables the system to determine sound source location in both azimuth and elevation, significantly improving measurement precision by adding spatial dimensions to the detection capability
2Measurement precision
If microphone array with signal processing is used, then measurement precision of sound source location is improved, but device complexity increases
Solution Approach 1:
The system extracts the target sound signal from the mixed audio input by separating it from background noise and other interfering sounds. Through signal processing techniques that isolate and extract the relevant sound source characteristics, the system improves identification accuracy while managing processing complexity through focused extraction of key signal features
Solution Approach 2:
The patent introduces intermediate signal processing stages that act as mediators between the raw microphone array input and the final sound source identification. These intermediary processing steps, including beamforming and spectral analysis, bridge the gap between raw data and interpreted results, improving measurement precision through systematic signal transformation while organizing complexity into manageable processing stages
3Reliability
If sophisticated signal processing is applied, then reliability of sound source detection in noisy conditions is improved, but loss of time for processing increases
Solution Approach 1:
The system performs preliminary signal processing operations on the microphone array input, including pre-whitening and covariance matrix calculation, before the main sound source detection algorithm executes. By preparing and pre-processing the signal data in advance, the system improves detection reliability through more robust input data while reducing the computational burden and processing time of the subsequent detection stages
Solution Approach 2:
The patent applies different processing strategies to different frequency bands and spatial regions of the audio signal. By tailoring the signal processing to local characteristics of the sound field and frequency content, the system improves detection reliability in noisy conditions through targeted processing while minimizing unnecessary computational operations, thereby reducing overall processing time
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 and precision of sound detection and location, improving safety and operational efficiency by effectively filtering background noise and identifying specific sound sources, such as emergency vehicle sirens, leading to better vehicle control and reduced wear and tear.
Implementation Method 1
determining, by the computing system, based at least in part on the sound data, a plurality of time differences. Each of the plurality of time differences can include a time difference between receipt of a source sound and receipt of a background sound at each of the plurality of microphones respectively
Data Source
AI summary
Systems, methods, tangible non-transitory computer-readable media, and devices associated with detecting and locating sounds are provided. For example, sound data associated with sounds can be received. The sounds can include source sounds and background sounds received by microphones. Based on the sound data, time differences can be determined. Each of the time differences can include a time difference between receipt of a source sound and receipt of a background sound at each of the microphones respectively. A set of the source sounds can be synchronized based on the time differences. An amplified source sound can be generated based on a combination of the synchronized set of the source sounds. A source location of the source sounds can be determined based on the amplified source sound. Based on the source location, control signals can be generated in order to change actions performed by an autonomous vehicle.