DOA Estimation Using Perpendicular Cross-Spectra Difference
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Solution Overview
Problem
Existing direction-of-arrival (DOA) estimation methods face challenges in accurately determining the direction of sound sources in complex acoustic environments with multiple sound sources and high reverberation, often leading to erroneous angle estimates due to noise and reflections.
Innovation Solution
The method employs a processor-implemented system using a sensor array with a short-time Fourier transform and Perpendicular Cross-Spectra Difference (PCSD) to calculate impinging angles, disambiguating between possible directions based on cross-spectra terms and angular coherence metrics, effectively handling multiple sound sources and noise by transforming signals into the time-frequency domain and applying specific disambiguation techniques.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional DOA estimation methods are used in complex acoustic environments, then the system is simple to implement, but the measurement precision deteriorates due to noise and reflections
Solution Approach 1:
The patent transforms the DOA estimation problem from the time domain to the time-frequency domain using Short-Time Fourier Transform (STFT). This dimensional change allows the system to analyze signals at different frequency components separately, making it possible to identify and filter out noise and reflections that affect different frequency ranges differently, thereby improving measurement precision in complex acoustic environments
Solution Approach 2:
The patent introduces Perpendicular Cross-Spectra Difference (PCSD) as an intermediary metric to disambiguate between multiple possible DOA estimates. The PCSD serves as a mediator that helps select the correct impinging angle from multiple candidates by comparing cross-spectra relationships, thereby improving DOA estimation accuracy in the presence of noise and reflections
2Loss of information
If multiple sound sources are present, then the information content increases, but the device complexity increases due to disambiguation requirements
Solution Approach 1:
The patent segments the DOA estimation process into distinct stages: (1) STFT to divide the signal into frequency bins, (2) PCSD calculation for each frequency bin, (3) auxiliary observation computation, and (4) disambiguation using cross-spectra terms. This segmentation allows the system to handle multiple sound sources systematically by processing each frequency component independently and then integrating results, reducing overall system complexity
Solution Approach 2:
The patent changes the parameter space by transforming from time-domain signals to time-frequency domain representations. By computing DOA estimates for each frequency bin separately and then combining results, the system can resolve multiple sound sources more easily. The auxiliary observation parameter and cross-spectra terms provide additional dimensions for disambiguation without significantly increasing computational complexity
3Measurement precision
If disambiguation techniques are applied to determine correct impinging angles, then the measurement precision improves, but the calculation time increases
Solution Approach 1:
The patent performs preliminary disambiguation at each frequency bin before final DOA determination. By calculating auxiliary observations and cross-spectra terms in advance for each frequency component, the system narrows down possible impinging angles early in the processing chain. This preliminary action reduces the computational burden of final disambiguation and speeds up the overall calculation process
Solution Approach 2:
The patent extracts only the essential disambiguation information from cross-spectra terms rather than processing complete signal data. By focusing computation on specific cross-spectra relationships and auxiliary observations that are most relevant for angle disambiguation, the system achieves accurate impinging angle determination with reduced computational time compared to processing all signal parameters
Data Source
AI summary
A processor-implemented method for direction-of-arrival estimation. The method includes: receiving a plurality of input signals at a sensor array, each sensor having an angle estimator and a cross-spectra term; transforming the input signal from each of the plurality of sensors to the time-frequency domain using a short-time Fourier transform; constructing a Perpendicular Cross-Spectra Difference (PCSD) for each of the plurality of angle estimators associated with each sensor for each frequency bin and time index; calculating an auxiliary observation for each of the angle estimators; and determining an impinging angle for each of the angle estimators based on the auxiliary observation.