Smart Audio Device Localization Without Clock Synchronization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods for locating audio devices, particularly smart audio devices, face challenges in irregular and asymmetric environments where devices are not homogeneous or synchronized, requiring known test stimuli and sample synchrony, and are not robust to measurement errors.
Innovation Solution
The method utilizes direction of arrival (DOA) and time of arrival (TOA) data between pairs of audio devices to minimize a non-linear optimization problem, allowing for the localization of audio devices in an environment without the need for synchronized clocks or known test stimuli, using beamforming, steered power response, and structured signal methods.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If known test stimuli and sample synchrony are used for device localization, then measurement precision is improved, but device complexity and ease of operation deteriorate due to requiring synchronized clocks and coordinated test signal transmission
Solution Approach 1:
Each audio device independently performs localization measurements using its own microphone array and processing capabilities. Devices autonomously determine their positions relative to others without requiring external coordination or synchronized test signals, eliminating the need for complex synchronization infrastructure while maintaining measurement precision through self-contained DOA estimation systems
Solution Approach 2:
The system performs preliminary calibration by having each device store its own microphone array geometry and characteristics in advance. This pre-stored information enables devices to immediately begin localization measurements without requiring real-time synchronization or external calibration signals, resolving the contradiction between measurement precision and operational complexity
2Adaptability or versatility
If audio devices are deployed in irregular and asymmetric environments, then adaptability is improved, but measurement precision deteriorates due to random distribution and asynchrony
Solution Approach 1:
The system explicitly handles asymmetric and irregular device distributions by removing assumptions of symmetric or regular layouts. Each device independently estimates directions of arrival from other devices using its own microphone array geometry, and the optimization algorithm processes the resulting asymmetric DOA data without requiring symmetric environmental conditions, thereby maintaining measurement precision in adaptable, irregular deployments
Solution Approach 2:
The system dynamically adapts to varying environmental configurations by allowing devices to be added, removed, or repositioned without requiring re-synchronization or recalibration. The independent DOA estimation and optimization approach enables the system to automatically adjust to dynamic, irregular layouts while maintaining localization accuracy through real-time processing of current device positions and orientations
3Reliability
If robustness to measurement errors is improved, then reliability is enhanced, but device complexity increases due to requiring multiple measurement methods and optimization algorithms
Solution Approach 1:
The system merges multiple measurement approaches by combining direction of arrival estimation from microphone arrays with optimization algorithms that process DOA data from multiple device pairs. This integration of complementary methods相互 reinforce each other, providing robust error correction through cross-validation while distributing processing complexity across all devices in the network rather than concentrating it in a single controller
Solution Approach 2:
The optimization algorithm uses feedback from multiple independent DOA measurements to iteratively refine position and orientation estimates. Each device's measurements serve as feedback that validates and corrects the estimates of other devices, creating a self-correcting system that enhances reliability through mutual verification while distributing the computational burden across the entire device network
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
Enables accurate localization of audio devices in complex environments by estimating their positions and orientations, even when devices are randomly distributed and asynchronous, improving robustness to measurement errors.
Implementation Method 1
obtain direction of arrival (DOA) data corresponding to sound emitted by at least a first smart audio device of an audio environment and received by at least a second smart audio device of the audio environment
Implementation Method 2
obtain time of arrival (TOA) data corresponding to sound emitted by at least one audio device of the audio environment and received by at least one other audio device of the audio environment
Implementation Method 3
sound emitted by at least a first smart audio device of an audio environment and received by at least a second smart audio device
Implementation Method 4
using beamforming, steered power response, and structured signal methods
Implementation Method 5
using beamforming, steered power response, and structured signal methods
Data Source
AI summary
A method may involve: receiving direction of arrival (DOA) data corresponding to sound emitted by at least a first smart audio device of the audio environment that includes a first audio transmitter and a first audio receiver, the DOA data corresponding to sound received by at least a second smart audio device of the audio environment that includes a second audio transmitter and a second audio receiver, the DOA data corresponding to sound emitted by at least the second smart audio device and received by at least the first smart audio device; receiving one or more configuration parameters corresponding to the audio environment, to one or more audio devices, or both; and minimizing a cost function based at least in part on the DOA data and the configuration parameter(s), to estimate a position and an orientation of at least the first smart audio device and the second smart audio device.