Adaptive Trigger Threshold for Ultrasonic Echolocation Detection
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Solution Overview
Problem
Bat detector devices face challenges in optimizing the triggering threshold for echolocation call detection due to changing environmental conditions, leading to either continuous triggering from ambient noise or missed faint echolocation calls, and the continuous computation of Fast Fourier Transforms is power-intensive and costly.
Innovation Solution
A system with a continuously adaptable trigger mechanism using a second DAC and comparator to dynamically adjust the threshold, leveraging low-cost and low-power microprocessors, allowing for efficient and economical triggering and scrubbing by comparing analog and digital signals to optimize sensitivity and minimize false triggers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If continuous Fast Fourier Transform computation is used for signal analysis, then measurement precision is improved, but use of energy increases significantly
Solution Approach 1:
The patent divides signal analysis into two separate paths: a low-power zero-crossing detection path for trigger events, and a high-precision full spectrum FFT analysis path for detailed signal characterization. This segmentation allows the system to achieve high measurement precision when needed while maintaining low power consumption during normal operation.
Solution Approach 2:
The system dynamically switches between different analysis modes based on trigger events. During normal operation, it uses the energy-efficient zero-crossing detector. When a trigger event occurs, it activates the more power-intensive FFT analysis only for that specific signal segment, thus optimizing the balance between precision and power consumption.
2Adaptability or versatility
If a fixed trigger threshold is used, then device complexity is reduced, but adaptability worsens due to changing environmental conditions
Solution Approach 1:
The system performs self-adjustment of the trigger threshold by continuously monitoring the ambient noise floor and automatically adapting the threshold level. This eliminates the need for manual calibration or complex external adjustment mechanisms, achieving high adaptability while keeping the device relatively simple.
Solution Approach 2:
The system uses feedback from the ambient noise detection to continuously adjust the trigger threshold. The noise floor measurement feeds back into the trigger level setting, allowing the system to adapt to changing environmental conditions automatically without requiring complex external control.
3Measurement precision
If the trigger threshold is set low to detect faint calls, then measurement precision is improved, but false triggers increase due to ambient noise
Solution Approach 1:
The system performs preliminary noise floor assessment before setting the trigger threshold. By measuring the ambient noise level in advance and using it to establish an appropriate threshold, the system achieves high detection sensitivity for faint calls while minimizing false triggers from ambient noise.
Solution Approach 2:
The system dynamically changes the trigger threshold parameter based on measured ambient noise conditions. When noise levels are high, the threshold is adjusted upward to reduce false triggers; when noise levels are low, the threshold can be lowered to detect fainter calls, thus optimizing detection sensitivity while minimizing false positives.
Data Source
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AI summary
Methods and apparatus for recording and analyzing echolocation calls using zero crossing and/or digital sampling (full spectrum analysis) techniques, and for optimizing trigger thresholds used to activate recording in response to detection of an echolocation call.