Self-Calibrating Dipole Microphone Sensor Mismatch Compensation
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Solution Overview
Problem
Dipole microphones using low-cost omni-directional acoustic sensor pairs face challenges due to mismatched sensors, which degrade noise cancellation performance over time due to environmental factors, and the high cost of sorting and maintaining matched pairs.
Innovation Solution
A self-calibrating dipole microphone system that includes two omni-directional acoustic sensors spaced apart, a processor to generate and respond to acoustic calibration signals, and digital filtering to match sensor outputs, ensuring consistent performance by periodically adjusting filter coefficients.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If low-cost omni-directional acoustic sensor pairs are used to construct dipole microphones, then manufacturing cost is reduced, but sensor mismatch degrades noise cancellation performance over time
Solution Approach 1:
The system performs preliminary calibration by playing calibration signals through a speaker and measuring sensor responses before normal operation. This preliminary action captures sensor characteristics and computes correction factors that are stored for later use, ensuring proper matching without requiring expensive pre-sorted sensor pairs
Solution Approach 2:
The microphone system calibrates itself automatically using its own speaker and processor. The system plays calibration signals, measures its own sensor responses, computes correction factors, and stores them in memory without external intervention. This self-service capability eliminates the need for expensive external calibration equipment and manual sorting processes
Solution Approach 3:
The system changes the operational parameters of the sensors by applying correction factors to their output signals. These correction factors adjust the amplitude and phase parameters of each sensor's output based on measured characteristics, dynamically compensating for mismatches and environmental changes throughout the microphone's operation
2Reliability
If sensor matching is performed at manufacture to ensure consistent performance, then noise cancellation performance is improved, but production cost and complexity increase
Solution Approach 1:
The patent replaces the mechanical/manual sensor sorting and matching process with an automated electronic calibration system. Instead of physically measuring and sorting sensors during manufacturing, the system uses digital signal processing to measure sensor responses to calibration signals and computationally determine correction factors, substituting electronic automation for manual mechanical processes
Solution Approach 2:
The calibration process uses feedback from the sensors' responses to calibration signals. The processor measures how each sensor responds to known calibration signals played through the speaker, uses this feedback information to compute appropriate correction factors, and applies these factors to optimize sensor matching. This closed-loop feedback approach ensures accurate matching without complex manual procedures
3Manufacturing precision
If sensor matching is performed at manufacture, then initial performance is good, but environmental changes cause mismatching over time
Solution Approach 1:
The system performs calibration periodically rather than just once at manufacture. The processor can re-play calibration signals and re-compute correction factors at scheduled intervals or when triggered by specific events, allowing the system to adapt to environmental changes and maintain optimal performance throughout its operational life
Solution Approach 2:
The calibration correction factors are stored in volatile memory rather than being permanently fixed. This dynamic approach allows the correction factors to be updated as environmental conditions change, making the sensor matching adaptable rather than static. The system can adjust to temperature changes, humidity variations, and other environmental factors that affect sensor characteristics over 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
The system maintains optimal noise cancellation performance over time by adaptively matching sensor outputs, reducing the need for precise sensor matching at manufacture and minimizing the impact of environmental changes, thus lowering production costs and improving reliability in noisy environments.
Implementation Method 1
two acoustic sensors spaced a distance apart... each acoustic sensor producing an output signal in response to the acoustic calibration signal
Implementation Method 2
a sound source acoustically coupled to the acoustic sensors... activating the sound source to produce an acoustic calibration signal
Data Source
AI summary
A self calibrating dipole microphone formed from two omni-directional acoustic sensors. The microphone includes a sound source acoustically coupled to the acoustic sensors and a processor. The sound source is excited with a test signal, exposing the acoustic sensors to acoustic calibration signals. The responses of the acoustic sensors to the calibration signals are compared by the processor, and one or more correction factors determined. Digital filter coefficients are calculated based on the one or more correction factors, and applied to the output signals of the acoustic sensors to compensate for differences in the sensitivities of the acoustic sensors. The filtered signals provide acoustic sensor outputs having matching responses, which are subtractively combined to form the dipole microphone output.